bluuebunny/crossref_metadata_2025_split huggingface dataset:
Photobehaviours guided by simple photoreceptor systems
Authors: Brodrick Emelie , Jékely Gáspár 
Published: August 2023

AbstractLight provides a widely abundant energy source and valuable sensory cue in nature. Most animals exposed to light have photoreceptor cells and in addition to eyes, there are many extraocular strategies for light sensing. Here, we review how these simpler forms of detecting light can mediate rapid behavioural responses in animals. Examples of these behaviours include photophobic (light avoidance) or scotophobic (shadow) responses, photokinesis, phototaxis and wavelength discrimination. We review the cells and response mechanisms in these forms of elementary light detection, focusing on aquatic invertebrates with some protist and terrestrial examples to illustrate the general principles. Light cues can be used very efficiently by these simple photosensitive systems to effectively guide animal behaviours without investment in complex and energetically expensive visual structures.
Multifocal neuropathy and Horner’s syndrome due to disseminated pyomyositis in an intravenous drug user
Authors: de Souza Aaron , Liew Brian Z. 
Published: August 2023

Abstract
Background
The formation of abscesses with necrosis within large, striated muscles leads to pyomyositis, a condition relatively rarely encountered outside the tropics. Intravenous drug users and other immunocompromised individuals are predisposed toward this infection, which may occur due to local or haematogenous spread of infection to skeletal muscles previously damaged by trauma, exercise, or rhabdomyolysis.

Methods
We report a young male intravenous drug user with rhabdomyolysis due to use of a synthetic opioid, in whom disseminated pyomyositis was detected following evaluation for sciatic and radial neuropathies and Horner’s syndrome and review available reports of peripheral nerve dysfunction in the setting of this uncommon infection. We searched online databases to identify all published reports on adult patients with pyomyositis complicated by peripheral nerve dysfunction.

Conclusions
Peripheral nerve dysfunction may rarely occur via local spread of infection or compression from abscesses.
The dysregulation of miRNAs in epilepsy and their regulatory role in inflammation and apoptosis
Authors: Xie Guoping , Chen Huan , He Chan , Hu Siheng , Xiao Xue , Luo Qunying 
Published: August 2023

AbstractEpilepsy is a neurological disorder that impacts millions of people worldwide, and it is characterized by the occurrence of recurrent seizures. The pathogenesis of epilepsy is complex, involving dysregulation of various genes and signaling pathways. MicroRNAs (miRNAs) are a group of small non-coding RNAs that play a vital role in the regulation of gene expression. They have been found to be involved in the pathogenesis of epilepsy, acting as key regulators of neuronal excitability and synaptic plasticity. In recent years, there has been a growing interest in exploring the miRNA regulatory network in epilepsy. This review summarizes the current knowledge of the regulatory miRNAs involved in inflammation and apoptosis in epilepsy and discusses its potential as a new avenue for developing targeted therapies for the treatment of epilepsy.
How to train your pre-trained GAN models
Authors: Park Sung-Wook , Kim Jun-Yeong , Park Jun , Jung Se-Hoon , Sim Chun-Bo 
Published: August 2023

AbstractGenerative Adversarial Networks (GAN) show excellent performance in various problems of computer vision, computer graphics, and machine learning, but require large amounts of data and huge computational resources. There is also the issue of unstable training. If the generator and discriminator diverge during the training process, the GAN is subsequently difficult to converge. In order to tackle these problems, various transfer learning methods have been introduced; however, mode collapse, which is a form of overfitting, often arises. Moreover, there were limitations in learning the distribution of the training data. In this paper, we provide a comprehensive review of the latest transfer learning methods as a solution to the problem, propose the most effective method of fixing some layers of the generator and discriminator, and discuss future prospects. The model to be used for the experiment is StyleGAN, and the performance evaluation uses Fréchet Inception Distance (FID), coverage, and density. Results of the experiment revealed that the proposed method did not overfit. The model was able to learn the distribution of the training data relatively well compared to the previously proposed methods. Moreover, it outperformed existing methods at the Stanford Cars, Stanford Dogs, Oxford Flower, Caltech-256, CUB-200–2011, and Insect-30 datasets.
Sea-lice regulation in salmon-farming countries: how science shape policies for protecting wild salmon
Authors: Vormedal Irja 
Published: August 2023

Abstract
The proliferation of sea lice from aquaculture may substantially aggravate the decline in marine survival of wild salmons. In some countries, this risk has motivated regulators to adopt more precautionary policies; in other countries, however, regulators have disputed the need for stricter regulation. This article compares the sea-lice regulations of Norway, Scotland, Ireland, and Canada (British Columbia), showing how varying interpretations of the science on farm–wild interactions have shaped efforts to scale up regulatory measures for mitigating health hazards and mortality risks for wild salmon. In Norway and Scotland, scientific consensus has expedited cooperation between research and governing institutions and facilitated ambitious policy reforms. In Ireland and Canada, by contrast, scientific controversy around the scale of farm-lice impacts on wild salmon populations has led to conflict and disagreement between researchers and policymakers, and to failure of reform attempts desired by wild salmon stakeholders.
From complexity to clarity: how directed acyclic graphs enhance the study design of systematic reviews and meta-analyses
Authors: Dijk Stijntje W. , Caulley Lisa M. , Hunink Myriam , Labrecque Jeremy 
Published: August 2023

AbstractWhile frameworks to systematically assess bias in systematic reviews and meta-analyses (SRMAs) and frameworks on causal inference are well established, they are less frequently integrated beyond the data analysis stages. This paper proposes the use of Directed Acyclic Graphs (DAGs) in the design stage of SRMAs. We hypothesize that DAGs created and registered a priori can offer a useful approach to more effective and efficient evidence synthesis. DAGs provide a visual representation of the complex assumed relationships between variables within and beyond individual studies prior to data analysis, facilitating discussion among researchers, guiding data analysis, and may lead to more targeted inclusion criteria or set of data extraction items. We illustrate this argument through both experimental and observational case examples.
Development of statistical regression and artificial neural network models for estimating nitrogen, phosphorus, COD, and suspended solid concentrations in eutrophic rivers using UV–Vis spectroscopy
Authors: Lyu Yanping , Zhao Wenpeng , Kinouchi Tsuyoshi , Nagano Tadahiro , Tanaka Shigeo 
Published: August 2023

AbstractRiver water quality monitoring is crucial for understanding water dynamics and formulating policies to conserve the water environment. In situ ultraviolet–visible (UV–Vis) spectrometry holds great potential for real-time monitoring of multiple water quality parameters. However, establishing a reliable methodology to link absorption spectra to specific water quality parameters remains challenging, particularly for eutrophic rivers under various flow and water quality conditions. To address this, a framework integrating desktop and in situ UV–Vis spectrometers was developed to establish reliable conversion models. The absorption spectra obtained from a desktop spectrometer were utilized to create models for estimating nitrate-nitrogen (NO3-N), total nitrogen (TN), chemical oxygen demand (COD), total phosphorus (TP), and suspended solids (SS). We validated these models using the absorption spectra obtained from an in situ spectrometer. Partial least squares regression (PLSR) employing selected wavelengths and principal component regression (PCR) employing all wavelengths demonstrated high accuracy in estimating NO3-N and COD, respectively. The artificial neural network (ANN) was proved suitable for predicting TN in stream water with low NH4-N concentration using all wavelengths. Due to the dominance of photo-responsive phosphorus species adsorbed onto suspended solids, PLSR and PCR methods utilizing all wavelengths effectively estimated TP and SS, respectively. The determination coefficients (R2) of all the calibrated models exceeded 0.6, and most of the normalized root mean square errors (NRMSEs) were within 0.4. Our approach shows excellent efficiency and potential in establishing reliable models monitoring nitrogen, phosphorus, COD, and SS simultaneously. This approach eliminates the need for time-consuming and uncertain in situ absorption spectrum measurements during model setup, which may be affected by fluctuating natural and anthropogenic environmental conditions.
On the Notion of Observers
Authors: Pawluszewicz Ewa , Molaei Mohammad Reza 
Published: August 2023

AbstractBy considering the idea and the notion of observers of dynamical systems, it is shown that relative semidynamical systems can be a suitable model for inserting an observer as a realistic fact to systems theory. Multi-dimensional observers and their affect on semidynamical systems are considered. Locally distinguishable semidynamical systems are introduced, and it is proved that this property preserves under relative conjugate relations which preserves observers. For an application of the role of observer relative topological entropy for relative semidynamical systems on compact relative topological spaces are considered.
The Geometry of Riemannian Curvature Radii
Authors: Bellini Eugenio 
Published: August 2023

AbstractWe study the geometric structures associated with curvature radii of curves with values on a Riemannian manifold (M, g). We show the existence of sub-Riemannian manifolds naturally associated with the curvature radii and we investigate their properties. In the particular case of surfaces these sub-Riemannian structures are of Engel type. The main character of our construction is a pair of global vector fields $$f_1,f_2$$

f
1

,

f
2

, which encodes intrinsic information on the geometry of (M, g).
Did You Commit a Crime There? Investigating the Visual Exploration Patterns of Guilty, Innocent, Honest, and Dishonest Subjects When Viewing a Complex Mock Crime Scene
Authors: Colasanti Marco , Melis Giulia , Monaro Merylin , Ricci Eleonora , Bosco Francesca , Rossi Michela , Biondi Silvia , Verrocchio Maria Cristina , Di Domenico Alberto , Mazza Cristina , Roma Paolo 
Published: August 2023

AbstractPrevious studies with the eye-tracking technology have predominantly tracked eye parameters in response to a single simple stimulus, and have generated interesting - sometimes inconsistent - results in research on deceptive behavior. The present study analyzed visual patterns in response to a complex image, to investigate potential differences in eye fixation between guilty versus innocent, and honest versus dishonest participants.One hundred and sixty participants were assigned to one of four experimental groups, defined by the parameters of honesty (dishonesty) and guilt (innocence), and asked to complete a computer-based task, looking at neutral and target images (i.e., images of the mock crime scene). RealEye software was used to capture participants’ eye movements when viewing the images.The findings revealed significant differences in eye movements between the four experimental groups in the pictures in which the area where the crime took place was clearly visible. Dishonest and guilty participants recorded fewer and shorter fixations in the area of the image where the crime took place than those who entered the crime scene but did not commit the crime. No differences between groups emerged in the visual patterns in response to neutral images, confirming that the number and duration of fixations in response to the target images may be attributed to the experimental condition.
HyNet: A novel hybrid deep learning approach for efficient interior design texture retrieval
Authors: Chen Junming , Shao Zichun , Cen Caichun , Li Jiaqi 
Published: August 2023

AbstractInterior designers are suffering from a lack of intelligent design methods. This study aims to enhance the accuracy and efficiency of retrieval textures for interior design, which is a crucial step toward intelligent design. Currently, interior designers rely on repetitive tasks to obtain textures from websites, which is ineffective as a interior design often requires hundreds of textures. To address this issue, this study proposes a hybrid deep learning approach, HyNet, which boosts retrieval efficiency by recommending similar textures instead of blindly searching. Additionally, a new indoor texture dataset is created to support the application of artificial intelligence in this field. The results demonstrate that the proposed method’s ten recommended images achieve a high accuracy rate of 91.41%. This is a significant improvement in efficiency, which can facilitate the design industry’s progression towards intelligence. Overall, this study offers a promising solution to the challenges facing interior designers, and it has the potential to significantly enhance the industry’s productivity and innovation.
Distance-based affective states in cellular automata pedestrian simulation
Authors: Bandini Stefania , Briola Daniela , Dennunzio Alberto , Gasparini Francesca , Giltri Marta , Vizzari Giuseppe 
Published: August 2023

AbstractCellular Automata have successfully been successfully applied to the modeling and simulation of pedestrian and crowd dynamics. In particular, the investigated scenarios have often been focused on the evaluation of medium–high population density situations, in which the motivation of pedestrians to reach a certain location overcomes their tendency to naturally respect proxemic distances. The global COVID-19 outbreak, though, has shown that sometimes it is crucial to contemplate how proxemic tendencies are emphasized and amplified by the affective state of the individuals involved in the scenario, representing an important factor to take into consideration when investigating the behaviour of a crowd. In this paper we present a research effort aimed at integrating results of quantitative analyses regarding the effects of affective states on the perception of distances maintained by different types of pedestrians with the modeling of pedestrian movement choices in a cellular automata framework.
Pulse ideotypes for abiotic constraint alleviation in Australia
Authors: Rao Shiwangni , Silva-Perez Viridiana , Armstrong Roger , Tefera Abeya Temesgen , Brand Jason , Riffkin Penny , Rosewarne Garry 
Published: August 2023

Abstract
Background
Pulses are cultivated across a range of soil and climatic conditions that often have many abiotic constraints to production. Whilst water stress has been identified as the greatest constraint in Australian pulse cultivation, other limitations include heat, frost, nutrient deficiency, and a variety of soil physiochemical constraints. Several studies on various pulses have examined shoot and root architecture and their ability to mitigate specific abiotic constraints. However, these studies have been conducted independently of each other, and there is a lack of amalgamated information combining both shoot and root responses that can address production constraints.

Scope
This review examines the shoot and root system architecture of key pulses used for human consumption grown in Australia including chickpea, lentil, faba bean, field pea and lupin; and where possible it provides a comparison with relevant research from other crops, especially cereals. It examines research conducted on adaptations to drought, waterlogging, temperature extremes, soil chemical toxicities and high soil strength.

Conclusion
The review utilises a physiological framework to identify trait combinations that define theoretical ideotypes of pulse crops that would be better able to mitigate abiotic constraints currently limiting Australian pulse productivity. This framework can be extended directly to other similar environments globally or be used to develop new ideotypes that are better adapted to a wider range of regions within Australia.
Prediction of the Maximum Amplitude of Solar Cycle 25 Using the Ascending Inflection Point
Authors: Aparicio A. J. P. , Carrasco V. M. S. , Vaquero J. M. 
Published: August 2023

AbstractIn this work, we predict the maximum amplitude (using the 13-month smoothed Solar Influences Data Analysis Center (SILSO) Sunspot Number, version 2) of Solar Cycle 25 using as a predictor the slope of the inflection point during the ascending part of the cycle. After a description of the data and methodology employed in this work, we obtain a value of 131 ± 32 for the maximum amplitude of Solar Cycle 25. Finally, we discuss this result in the context of the current debate on the prediction of solar activity and compare it with other predictions of Solar Cycle 25 obtained by other methods.
A Continuation Technique for Maximum Likelihood Estimators in Biological Models
Authors: Cassidy Tyler 
Published: August 2023

AbstractEstimating model parameters is a crucial step in mathematical modelling and typically involves minimizing the disagreement between model predictions and experimental data. This calibration data can change throughout a study, particularly if modelling is performed simultaneously with the calibration experiments, or during an on-going public health crisis as in the case of the COVID-19 pandemic. Consequently, the optimal parameter set, or maximal likelihood estimator (MLE), is a function of the experimental data set. Here, we develop a numerical technique to predict the evolution of the MLE as a function of the experimental data. We show that, when considering perturbations from an initial data set, our approach is significantly more computationally efficient that re-fitting model parameters while producing acceptable model fits to the updated data. We use the continuation technique to develop an explicit functional relationship between fit model parameters and experimental data that can be used to measure the sensitivity of the MLE to experimental data. We then leverage this technique to select between model fits with similar information criteria, a priori determine the experimental measurements to which the MLE is most sensitive, and suggest additional experiment measurements that can resolve parameter uncertainty.
Temperature Evolution, Material Flow, and Resulting Mechanical Properties as a Function of Tool Geometry during Friction Stir Welding of AA6082
Authors: Laska Aleksandra , Sadeghi Behzad , Sadeghian Behzad , Taherizadeh Aboozar , Szkodo Marek , Cavaliere Pasquale 
Published: August 2023

AbstractThe friction stir welding process was simulated for joining AA6082 aluminum alloy with the use of the computational fluid dynamics method. Two different tool geometries were used—a tapered cylindrical pin (simple pin) and a hexagonal pin with grooves (complex pin). The analysis of the simulations performed was discussed in terms of temperature evolution during the process, total heat input, residual stresses and material flow. Simulations revealed that a 5% higher temperature, equal to maximum 406 °C, was provided when using the complex pin than with the simple pin. Higher temperature and higher shear stresses during the welding with the complex pin caused the introduction of higher residual stresses in the weld. Experimental results on the produced welds allowed observation of the microstructure of the joints, hardness tests in cross sections and tensile strength tests. Due to the higher temperature during the process with the complex pin and the more efficient recrystallization process, grain refinement in the SZ was more pronounced. The average grain size in the stir zone for the weld produced with the complex pin was equal to 11 ± 1 µm, and in the case of the simple pin 14 ± 1 µm. The presented hardness profiles revealed that the weld produced with a complex pin had higher hardness in the stir zone, equal to 89.5 ± 1.3 HV, which is consistent with the Hall-Petch relationship. The obtained UTS values corresponded to the joint efficiency of 72.5 ± 4.9% and 55.8 ± 8.6% for the weld produced with the complex pin and the simple pin.
A Critical Assessment Regarding Two-Temperature Models: An Investigation of the Different Forms of Two-Temperature Models, the Various Ultrashort Pulsed Laser Models and Computational Methods
Authors: Alexopoulou Vasiliki E. , Markopoulos Angelos P. 
Published: August 2023

AbstractNowadays, lasers are used in a wide variety of manufacturing processes, such as cutting, sintering and welding. The evolution of laser technologies has led to the creation of ultrashort pulsed lasers, with a pulse duration below 10 ps, which have the ability, on the contrary with the conventional lasers, to stimulate separately the electrons and the lattice. Thus, two different temperatures, the electron temperature and the lattice temperature appear. This cannot be described by the classical Fourier heat equations and thus the Two-Temperature Model (TTM) has been proposed. In the TTM, a heat equation that describes the electron temperature is conjugated with a heat equation that describes the lattice temperature. Except from the correct implementation of the heat equations, other factors that should be taken into consideration during the development of the TTM simulation are the correct and accurate modelling of the ultrashort pulsed laser and the appropriate selection of the computational method regarding the targets of each specific study. The aim of this review paper is not only to present the current literature regarding the different TTMs, ultrashort pulsed laser models and computational methods, but also to create mind maps that will help the researcher to choose the most appropriate TTM and computational method regarding the targets of each specific study. Moreover, in this review paper, recommendations for future work are given, regarding the more accurate and realistic modelling of the laser source.
Wrightia vietnamensis (Apocynaceae), a new species from Vietnam
Authors: Hazell Emily C. , Baines Richard A. , Nguyen Van Dzu , Francis Jessica V. , Middleton David J. 
Published: August 2023

SummaryA new species of Wrightia (Apocynaceae) from Vietnam, Wrightia vietnamensis Hazell & D.J.Middleton, is described and illustrated. Seed was collected on a Vietnamese led international collaborative expedition and grown on in the Temperate House at the Royal Botanic Gardens, Kew. When it matured and flowered, it was found to be an undescribed species. The species is currently only known from one karst limestone locality. This restricted distribution conforms to regional patterns of speciation and endemism in the genus whereby species restricted to karst limestone have very restricted distributions and those found on other soil types have wider distributions.