Miracle-dz/UniFAR-FTUs huggingface dataset:
A mechanical approach to explain cortical folding phenomena in healthy and diseased brains

The development of the human brain with its characteristically folded surface morphology remains an intensively discussed topic. Impressive advancements in different fields of research have enhanced the understanding of the brain. However, the mechanism that underlies the folding process in healthy and diseased brains remains undetermined. Here, we hypothesize that growth induced mechanical instabilities drive folding. Using the nonlinear field theories of continuum mechanics supplemented by the theory of finite growth [1], we model the human brain as a bi‐material with the cerebral cortex, a morphogenetically growing outer layer of gray matter, and the subcortex, a strain‐driven growing inner core of white matter [2]. This approach integrates the two popular but competing hypotheses that cortical folding is either driven by differential growth or by axon elongation. Through systematic sensitivity analyses, we identify the critical process parameters of cortical folding and quantify their impact on brain morphology. We further simulate phenomena causing malformations like lissencephaly and polymicrogyria [3], which are associated with neurological disorders, including severe retardation, epilepsy, schizophrenia, and autism. Understanding the mechanisms of cortical folding during brain development might facilitate the diagnostics and treatment of malformed brains. (© 2014 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Exploration of the Relationship between Multiple Anthropometric Data and Obesity and Prediction of Obesity using a Linear Regression Model

Obesity prevalence has risen sharply in the United States from 1987 to the present, and there is merely a sign that obesity rates are declining. Obesity is associated with numerous medical and psychological abnormalities and the economic expenditures of individuals. What factors affect obesity has been widely discussed, while still has no conclusion. This article provides a study using the linear regression model to analyze the relationship between some anthropometric data and obesity and predict obesity. A linear regression model including 252 observations and 15 variables is constructed for discovering the relationship and predicting obesity. Some improvements are also pointed out to increase the accuracy of the model. A primary linear regression model is built by R-studio. Moreover, LASSO is used to remove outliers to improve the model. The accuracy is verified to prove the practicality of the model. The study can facilitate the study of forecasting obesity by using anthropometric measurement data and provide a reference for other researchers who are interested in this topic. Moreover, the regression model enables the public to become familiar with their obesity status simply by measuring the circumference of their body parts, contributing to a lower risk of obesity-related diseases.
Association Schemes: Designed Experiments, Algebra and Combinatorics

1. Association schemes 2. The Bose-Mesner algebra 3. Combining association schemes 4. Incomplete-block designs 5. Partial balance 6. Families of partitions 7. Designs for structured sets 8. Groups 9. Posets 10. Subschemes, quotients, duals and products 11. Association schemes on the same set 12. Where next? 13. History and references.
Open Research Online On the asymmetry of Nathair Facula, Mercury

Nathair Facula is the largest and most spectrally distinct of nearly 200 ‘bright red ’ spots (faculae) on Mercury ’ s surface, most of which are accepted to be deposits from explosive volcanic eruptions. Like most of Mercury ’ s faculae, it hosts a non-circular central pit (in this case nearly 40 km wide and 3 km deep). However, the center of this facula does not coincide with its central pit ’ s midpoint. Quantitative analysis of two sets of spectral data shows that the facula ’ s midpoint is offset by 10 – 30 km northwards or northeastwards, and probably lies outside the pit. The pit area is almost certainly a ‘compound vent ’ , within which the locus of eruption has migrated between eruptive episodes. The asymmetry of the facula and the texture of the vent floor are consistent with the most energetic and/or the most recent eruptions having occurred from the northeastern part of the compound vent, but evidence that the center point of the facula lies outside the vent indicates that it may be necessary to invoke an additional factor such as asymmetric eruption fountains.
A Study on the Optimal Ratio of Research and Development Investment in the Energy Sector: An Empirical Analysis in South Korea

The necessity for energy research and development (ER&D) is increasing as greenhouse gases and climate change are becoming global issues. To support sustainable economic growth through ER&D, it is necessary to examine the optimal ratio of ER&D investment to total R&D investment to maximize economic growth. However, there are no studies on the appropriate level of ER&D in total R&D investment for economic growth. This study attempts to empirically estimate the optimal ratio of ER&D investment to maximize gross domestic product (GDP) in South Korea. We utilized the Cobb-Douglas production function for our econometric model and corrected the autocorrelation problem using the Cochrane-Orcutt iterative procedure. Our results showed that both, ER&D and non-ER&D have positive correlations with GDP. The optimal ratio of ER&D is derived as 13.23%, which indicates that the current ratio of Korean ER&D should be revised upward. Further, ER&D investment in the private sector needs to be increased to achieve the optimal ratio because the current statistics in Korea describes that private companies in the energy industry invest much less in R&D than the government. Based on the results, we suggest government strategies to enhance ER&D investment in the private sector as well as the public sector.
Love Language Over Time: An Analysis of Self-Presentation in Dating by Comparing Historical Personal Ads and Contemporary Dating App Biographies

This research focused on the biographies of dating apps which are space-limited and self-written and therefore give insight in what users find crucial to mention about themselves and their wishes for possible partners. The content of the biographies was compared to the content of personal ads, collected and analysed between 1947 and 1985, providing insight in self-presentation in mate search through time. The method relied on biographies which were collected in The Netherlands in 2021 from three dating apps: Tinder, Bumble, and Lexa. Profiles of men and women aged 18 to 37 looking for a heterosexual partner were selected. The texts were analysed on mentions of intention, lifestyle, personality, and appearance and on usage of negation and emoji. The personal ads collection was composed and annotated by researcher Wil Zeegers, according to similar content themes. Comparisons were made between men and women, between age 18 to 27 and 28 to 37, and between dating applications. Historical analyses was done between men and women. Results include that intentions differ per dating app. Personality self-description increased over time, number of requests peaked in late personal ads. Appearance description were more frequent in personal ads, probably because dating apps allow for photographs. The most important lifestyle element in early personal ads was religion, while later ads and dating app biographies focused mostly on interests. In conclusion, this research gives insight in how description of identity and projected partner in personal ads and dating app biographies can be used as indicator for mate choice criteria and how this can give insight in societal values.
Embedded dual switched‐capacitor based continuous input current switched‐inverter for renewable energy application

This study presents a high voltage gain embedded dual switched-capacitor-based continuous input current impedance source inverter for renewable energy applications. Renewable energy resources have low-output voltage generation capability, and the converter needs to operate on the extreme duty cycle for high voltage requirements. To achieve high voltage gain, a conventional impedance source inverter needs to operate on a high duty cycle, which leads to the reduction in modulation index. Operating at a reduced value of modulation index leads to poor inversion operation with poor output power quality. In order to take care of this issue, an embedded dual switched-capacitor-based inverter is presented for high voltage gain in low shoot-through duty cycle. The proposed inverter is suitable for DC–AC power conversions such as solar photovoltaic where a low-input voltage is available, and it needs to be converted into high DC–AC output voltages. Anatomisation of operating principle, steady-state analysis, passive design criteria, and comparison are discussed. The proposed inverter also has less capacitor voltage stress, less diode current stress, and higher efficiency than other impedance-source inverters. The operation of the proposed inverter is verified through simulations and experimental results with a 600 W prototype.
Cell Migration and Invasion

Focal adhesions (FAs) are intra and extracellular multiprotein complexes that act as attachment points between the plasma membrane of a cell and its surrounding extracellular matrix (ECM). FAs localize to a narrow z range on the ventral side of cells. Therefore, imaging them is challenging without specialized microscopy techniques and equipment that is not conducive with high-throughput imaging. This application note demonstrates that the Agilent BioTek Cytation C10 confocal imaging reader, combined with the Agilent BioTek Gen5 microplate reader and imager software, can reliably image and identify FAs in a high-throughput, 96-well format. This expanded throughput provides new possibilities to screen cancer drugs targeted for FAs.
Analyzing the Performance of High Dimensional Nonparanormal Graphical Models with RNA-Seq Data

This study investigates the nonparanormal transformation of data and how it relates to the problem of gene regulatory network inference. Speciﬁcally, it investigates several graph estimation methods with an applied nonparanormal transformation to RNA-Seq data as compared to a greedy hill-climbing approach. These experiments are conducted in a high-dimensional setting, where the number of genes highly outweighs the number of samples (a common setting in computational biology). Results show that the nonparanormal approach severely underperforms in this setting as compared to the greedy approach, however further trials with a variety in parameter selection are required for conclusive results.
CLASSIFICATION OF THE POOR IN SUMATERA AND JAVA ISLAND USING NAIVE BAYES ALGORITHM AND NAIVE BAYES ALGORITHM BASED ON

The poverty rate in Indonesia is still quite high, due to the large population and uneven development and economic center. With a large population and an archipelagic country that stretches from west to east, it is not easy for the government to level the economy in order to reduce poverty in Indonesia. This study was conducted to classify the poverty rate in districts on the island of Sumatra and Java using Nave Bayes and Nave Bayes based on Particle Swarm Optimization. Thus, it is hoped that the central government and local governments can monitor the implementation of programs in order to reduce poverty rates, especially in districts with high poverty rates. Based on research conducted on the classification of the poor in districts on the island of Sumatra and Java with confusion matrix testing and validation validation techniques using the Naïve Bayes algorithm, the accuracy rate is 59.75% and AUC 0.768 is included in a good classification. While the results of the classification using the Naïve Bayes algorithm based on Particle Swarm Optimization produces an accuracy rate of 82.93% and AUC of 0.849 is included in a good classification. From the results of this study, it can be said that Al-Qur'an Naïve Bayes is a good technique for classification in data mining, and for maximum results using Particle Swarm Optimization.
— GNSS-free navigation Resilient and accurate vessel positioning with radar and digital elevation models

To increase resilience against disturbance and adversarial actions, it is important to consider positioning solutions that do not rely on external technology. This requires mapping of onboard sensor data to a global position, either as prior knowledge or by building a map on the go. The latter is known as Simultaneous Localization And Mapping (SLAM), where a family of algorithms uses sensor data to build a map in real time and position the sensor within the map. Compared to using a Digital Elevation Model (DEM)-based model, SLAM could have the benefit of being less sensitive to the detailedness of underlying data while also adapting to changes more quickly. SLAM has been previously applied to radar data in a maritime setting [5], but as there is no geographical reference to tie the SLAM map to the physical world, a SLAM algorithm would not be able to provide global positioning without additional localization sensors. Even with good initialization, SLAM is prone to drift unless combined with known global reference points. In this paper, we propose the use of DEMs, for the reasons outlined below.
Tracking tree history to understand better natural dynamics of old-growth forest stands

Zsó a Szegleti Doctoral School of Environmental Sciences, Hungarian University of Agriculture and Life Sciences https://orcid.org/0000-0002-6937-3062 Ákos Vig Gödöllő Campus, Hungarian University of Agriculture and Life Sciences Adrienne Ortmann-Ajkai Department of Hydrobiology, Institute of Biology, University of Pécs https://orcid.org/0000-0002-66772666 Szilárd Czóbel Institute of Plant Sciences and Environmental Protection, University of Szeged https://orcid.org/00000002-7954-4515 Ferenc Horváth (  horvath.ferenc@ecolres.hu ) Institute of Ecology and Botany, Centre for Ecological Research https://orcid.org/0000-0002-13171269
PERVERSE SHEAVES AND coO -ACTIONS

where t· x denotes the action of t on x. The set Xw is known to be a locally-closed c* -stable algebraic subvariety of X isomorphic to an affine space. The pieces Xw form a cell decomposition X = UWEW XW ' W E W, the socalled Bialynicki-Birula decomposition. We assume this decomposition to be an algebraic stratification of X (the closure of a cell may not be a union of cells, in general). Let . cw be the intersection cohomology complex on the closure of a cell Xw extended by 0 to the whole of X. The hypercohomology H·. cw has a natural structure of a graded H' (X, C)-module. Further, for any x, YEW, there is a natural morphism of graded spaces:
Improve power density with a baby boost converter in a PFC circuit

In the year 2000, server front end power-supply units (PSUs) – with an AC input to a 12-V/48-V DC rail – achieved around 10 W/in3 of power density, with about 85% peak efficiency [1]. Today, so many server PSUs can meet 80 Plus Platinum (94% peak) and 80 Plus Titanium (96% peak) requirements [2] that the latter requirement, along with very high power density (>90 W/ in3), are both now becoming minimum requirements.
Occurrence of Spot Blotch in Spring Barley Caused by Bipolaris sorokiniana Shoem. in South-Eastern Kazakhstan

In Kazakhstan, barley (Hordeum vulgare L.) is the second most important cereal crop after wheat, with an annual production of approximately 1.9 million tons. The study aimed to characterize Bipolaris sorokiniana isolates obtained from barley fields surveyed. A total of 21 diseased leaves showing spot blotch symptoms were collected from experimental plots located close to the Kazakh Research Institute of Agriculture and Crop Production, where the spring barley Arna cultivar was planted in June 2020. The overall strategy for control of spring barley blotch in the Almaty region of Kazakhstan should include the determination of the aggressiveness of the pathogen isolates to better understand the biology of the diseases and ultimately proper control strategy. Pathogenicity of B. sorokiniana isolates was made on barley seedlings in vitro. Inoculated seedlings showed clear symptoms of B. sorokiniana, and therefore, Koch's postulates were fulfilled by reisolating the pathogen from artificially inoculated seedlings and identifying it based on standard morphology criteria. Further investigation is needed to understand the impact of B. sorokiniana on barley production in Kazakhstan.
Simultaneous Ultraviolet and X-Ray Spectroscopy of the Seyfert 1 Galaxy NGC 5548. I. Physical Conditions in the Ultraviolet Absorbers

We present new UV spectra of the nucleus of the Seyfert 1 galaxy NGC 5548, which we obtained with the Space Telescope Imaging Spectrograph at high spectral resolution, in conjunction with simultaneous Chandra X-Ray Observatory spectra. Taking advantage of the low UV continuum and broad emission-line fluxes, we have determined that the deepest UV absorption component covers at least a portion of the inner, high-ionization narrow-line region (NLR). We find nonunity covering factors in the cores of several kinematic components, which increase the column density measurements of N V and C IV by factors of 1.2-1.9 over the full-covering case; however, the revised columns have only a minor effect on the parameters derived from our photoionization models. For the first time, we have simultaneous N V and C IV columns for component 1 (at -1040 km s-1) and find that this component cannot be an X-ray warm absorber, contrary to our previous claim based on nonsimultaneous observations. We find that models of the absorbers based on solar abundances severely overpredict the O VI columns previously obtained with the Far Ultraviolet Spectroscopic Explorer and present arguments that this is not likely due to variability. However, models that include either enhanced nitrogen (twice solar) or dust, with strong depletion of carbon in either case, are successful in matching all of the observed ionic columns. These models result in substantially lower ionization parameters and total column densities compared to dust-free solar-abundance models and produce little O VII or O VIII, indicating that none of the UV absorbers are X-ray warm absorbers.
Improved Zebra Finch Brain Transcriptome Using Both Short and Long Read RNA-seq Methods

Zebra finch ( Taeniopygia guttata ) is a representative songbird species that has been widely studied to investigate the neurobiological basis of vocal learning, a rare trait shared in only a few species including human. In December 2019, an updated zebra finch genome annotation (bTaeGut1_v1.p) was released from Ensembl database and is substantially more comprehensive than the first version published in 2010. In this study, we utilized the publicly available RNA-seq data generated from Illumina-based short-read method and PacBio single-molecule real-time (SMRT) long-read method to assess the bird transcriptome. To analyze the high-throughput RNA-seq data, we adopted a hybrid bioinformatic approach combining short and long read pipelines to investigate the new bird annotation for the first time. From our analysis, we added 220 novel genes and 8,134 transcript variants to the Ensembl annotation, and predicted a new proteome based on the refined annotation. Our results provide additional resources for future studies of zebra finches and other songbirds utilizing this improved annotation.
A multiobjective response surface approach for improved water quality planning in lakes and reservoirs

Improved data collection techniques as well as increasing computing power are opening up new opportunities for the development of sophisticated models that can accurately reproduce hydrodynamic and biochemical conditions of water bodies. While increasing model complexity is considered a virtue for scientific purposes, it is a definite disadvantage for management (engineering) purposes, as it limits the model applicability to what‐if analysis over a few, a priori defined interventions. In the recent past, this has become a significant limitation, particularly considering recent advances in water quality rehabilitation technologies (e.g., mixers or oxygenators) for which many design parameters have to be decided. In this paper, a novel approach toward integrating science‐oriented and engineering‐oriented models and improving water quality planning is presented. It is based on the use of a few appropriately designed simulations of a complex process‐based model to iteratively identify the multidimensional function (response surface) that maps the rehabilitation interventions into the objective function. On the basis of the response surface (RS), a greater number of interventions can be quickly evaluated and the corresponding Pareto front can be approximated. Interesting points on the front are then selected and the corresponding interventions are simulated using the original process‐based model, thus obtaining new decision‐objective samples to refine the RS approximation. The approach is demonstrated in Googong Reservoir (Australia), which is periodically affected by high concentrations of manganese and cyanobacteria. Results indicate that significant improvements could be observed by simply changing the location of the two mixers installed in 2007. Furthermore, it also suggests the best location for an additional pair of mixers.
Indian Petrochemical Industry Challenges and Opportunities

: Petro-chemical industries ought to be regarded as the most significant branches of industry necessary for fulfillment of human needs. The energy and organic chemicals consumptions are growing (7% per annum) incessantly due to rapid increase of world's population with improved standards of living. The increasing energy demands, gradual depletion of fossil fuels and hence rise of crude oils price are foremost motivations for exploration of renewable resources for sustainable production of electricity, heat, fuels, organic chemicals and polymers. Therefore, new manufacturing concepts are continuously evolving to produce an array of bio-fuels and multitude of bio-products from biomass. These complex processing technologies are analogous to today's integrated petroleum refinery and petrochemical industries commonly known as bio-refinery. Furthermore, the article provides an overview of hydrocarbon biorefinery for production of hydrocarbon fuels and building block chemicals from biomass.
The relationships of family income and caste-status with religiousness: Mediation role of intolerance of uncertainty

The relationship between lower socioeconomic status (SES) and religiousness is well known; however, its (psychological mediation) mechanism is not clear. In the present study, we studied the mediation role of intolerance of uncertainty (IU; a personality measure of self-uncertainty) in the effect of SES on religiousness and its dimensions (i.e., believing, bonding, behaving, and belonging), in two different samples (students sample, N = 868, and community sample, N = 250), after controlling the effects of factors like age, sex, handedness, and self-reported risk-taking. The results showed that IU mediated the effects of lower family income and lower caste status (in students’ sample only) on religiousness and its dimensions; higher caste status had a direct effect on religiousness (and its dimensions), and; among the sub-factors of IU, only prospective IU affected religiousness. Thus, along with showing that IU is a mediator of the effects of lower family income and lower caste status on religiousness, the present study supports the contention that religiousness is a latent variable that varied factors can independently initiate. Moreover, the present study suggests a nuanced model of the relationship between the hierarchical caste system and religiousness.