Miracle-dz/UniFAR-FTUs huggingface dataset:
Psychosocial Outcomes as Motivations for Visiting Nearby Urban Green Spaces

High-density urban living means that urban green spaces are important nodes of contact with nature. This study examines expected outcomes that motivate people to seek green spaces in urban settings. A sample of Swiss residents were presented with Shin, Kwon, Hammitt, and Kim's (2005) psychosocial outcomes scale and asked which activities they choose to undertake in nearby natural areas. The most important motivations for visiting nearby green spaces were related to restoration, with social bonding as a desirable side benefit. There were few observable differences between urban and rural residents and level of education attained. Older people are motivated to visit nearby green spaces by the wish to seek social contact while younger people are motivated by the wish to seek escape and to reflect. This study contributes to the understanding of the psychosocial outcomes that residents expect from engaging in an activity in an urban green space.
Benchmark problems for dust radiative transfer

When verifying a sophisticated numerical code, it is a usual practice to compare the results with reliable solutions obtained by other means. This work provides such solutions for the wavelength dependent dust radiative transfer problem. We define a set of benchmark problems in spherical geometry and solve them by three radiative transfer codes which implement different numerical schemes. Results for the dust temperature and emerging spectra agree to better than 0.1%, and can be used as benchmark solutions for the verification of the dust radiative transfer codes.
Shifts in soil organic carbon for plantation and pasture establishment in native forests and grasslands of South America

The replacement of native vegetation by pastures or tree plantations is increasing worldwide. Contradictory effects of these land use transitions on the direction of changes in soil organic carbon (SOC) stocks, quality, and vertical distribution have been reported, which could be explained by the characteristics of the new or prior vegetation, time since vegetation replacement, and environmental conditions. We used a series of paired‐field experiments and a literature synthesis to evaluate how these factors affect SOC contents in transitions between tree‐ and grass‐dominated (grazed) ecosystems in South America. Both our field and literature approaches showed that SOC changes (0–20 cm of depth) were independent of the initial native vegetation (forest, grassland, or savanna) but strongly dependent on the characteristics of the new vegetation (tree plantations or pastures), its age, and precipitation. Pasture establishment increased SOC contents across all our precipitation gradient and C gains were greater as pastures aged. In contrast, tree plantations increased SOC stocks in arid sites but decreased them in humid ones. However, SOC losses in humid sites were counterbalanced by the effect of plantation age, as plantations increased their SOC stocks as plantations aged. A multiple regression model including age and precipitation explained more than 50% (p < 0.01) of SOC changes observed after sowing pastures or planting trees. The only clear shift observed in the vertical distribution of SOC occurred when pastures replaced native forests, with SOC gains in the surface soil but losses at greater depths. The changes in SOC stocks occurred mainly in the silt+clay soil size fraction (MAOM), while SOC stocks in labile (POM) fraction remained relatively constant. Our results can be considered in designing strategies to increase SOC storage and soil fertility and highlight the importance of precipitation, soil depth, and age in determining SOC changes across a range of environments and land‐use transitions.
The good, the bad and their kins: Identifying questions with negative scores in StackOverflow

A rapid increase in the number of questions posted on community question answering (CQA) forums is creating a need for automated methods of question quality moderation to improve the effectiveness of such forums in terms of response time and quality. Such automated approaches should aim to classify questions as good or bad for a particular forum as soon as they are posted based on the guidelines and quality standards defined/listed by the forum. Thus, if a question meets the standard of the forum then it is classified as good else we classify it as bad. In this paper, we propose a method to address this problem of question classification by retrieving similar questions previously asked in the same forum, and then using the text from these previously asked similar questions to predict the quality of the current question. We empirically validate our proposed approach on the set of StackOverflow data, a massive CQA forum for programmers, comprising of about 8M questions. With the use of these additional text retrieved from similar questions, we are able to improve the question quality prediction accuracy by about 2.8% and improve the recall of negatively scored questions by about 4.2%. This improvement of 4.2% in recall would be helpful in automatically flagging questions as bad (unsuitable) for the forum and will speed up the moderation process thus saving time and human effort.
Brain-grounding of semantic vectors improves neural decoding of visual stimuli

Developing algorithms for accurate and comprehensive neural decoding of mental contents is one of the long-cherished goals in the field of neuroscience and brain-machine interfaces. Previous studies have demonstrated the feasibility of neural decoding by training machine learning models to map brain activity patterns into a semantic vector representation of stimuli. These vectors, hereafter referred as pretrained feature vectors, are usually derived from semantic spaces based solely on image and/or text features and therefore they might have a totally different characteristics than how visual stimuli is represented in the human brain, resulting in limiting the capability of brain decoders to learn this mapping. To address this issue, we propose a representation learning framework, termed brain-grounding of semantic vectors, which fine-tunes pretrained feature vectors to better align with the neural representation of visual stimuli in the human brain. We trained this model this model with functional magnetic resonance imaging (fMRI) of 150 different visual stimuli categories, and then performed zero-shot brain decoding and identification analyses on 1) fMRI and 2) magnetoencephalography (MEG). Interestingly, we observed that by using the brain-grounded vectors, the brain decoding and identification accuracy on brain data from different neuroimaging modalities increases. These findings underscore the potential of incorporating a richer array of brain-derived features to enhance performance of brain decoding algorithms.
The Diploma Disease: Education, Qualification, and Development

Schools used to be for educating people, for developing minds and characters. Today, as jobs depend more and more on certificates, degrees and diplomas, schooling has become more and more a ritualized process of qualification-earning. Professor Dore traces the underlying causes of this change through the educational histories of Britain, Japan, Sri Lanka and Kenya, showing how the late development effect makes what is a worrying problem for the rich countries in the North a disaster for the poorer countries of the South.
Advanced Deep Operator Networks to Predict Multiphysics Solution Fields in Materials Processing and Additive Manufacturing

Unlike classical artificial neural networks, which require retraining for each new set of parametric inputs, the Deep Operator Network (DeepONet), a lately introduced deep learning framework, approximates linear and nonlinear solution operators by taking parametric functions (infinite-dimensional objects) as inputs and mapping them to complete solution fields. In this paper, two newly devised DeepONet formulations with sequential learning and Residual U-Net (ResUNet) architectures are trained for the first time to simultaneously predict complete thermal and mechanical solution fields under variable loading, loading histories, process parameters, and even variable geometries. Two real-world applications are demonstrated: 1- coupled thermo-mechanical analysis of steel continuous casting with multiple visco-plastic constitutive laws and 2- sequentially coupled direct energy deposition for additive manufacturing. Despite highly challenging spatially variable target stress distributions, DeepONets can infer reasonably accurate full-field temperature and stress solutions several orders of magnitude faster than traditional and highly optimized finite-element analysis (FEA), even when FEA simulations are run on the latest high-performance computing platforms. The proposed DeepONet model's ability to provide field predictions almost instantly for unseen input parameters opens the door for future preliminary evaluation and design optimization of these vital industrial processes.
MUSICAL METER ESTIMATION AND MUSIC TRANSCRIPTION

This paper concerns the segmentation and automatic transcription of acoustic musical signals. First, a method is proposed for estimating the temporal structure of music, the musical meter. The method consists of an acoustic analysis front-end and of a subsequent probabilistic model which performs joint estimation of the meter at three time scales: beat (tactus), measure, and tatum pulse levels. Secondly, musicological models are described which utilize musical information to improve transcription accuracy.
Rat hepatic 3 alpha-hydroxysteroid dehydrogenase: expression of cDNA and physiological function in bile acid biosynthetic pathway.

3 alpha-Hydroxysteroid dehydrogenase (3 alpha-HSD) [EC 1.1. 1.213]2 plays important multifunctional roles in metabolizing steroid hormones, polycyclic aromatic hydrocarbons, and prostaglandins and also in transforming the steroid nucleus for the biosynthesis of bile acids from cholesterol in liver. To gain insight into the details and physiological functions of 3 alpha-HSD in the bile acid biosynthetic pathway, cDNA clones of 3 alpha-HSD were isolated from rat liver lambda phage cDNA libraries by using specific antibodies to 3 alpha-HSD purified from rat liver. Transfection of the 3 alpha-HSD cDNA in Simian COS7 cells resulted in the expression of an immunoreactive protein to the antibodies against the purified enzyme, and the transfected cells exhibited activities for not only 7 alpha-hydroxy-5 beta-cholestan-3-one, the intermediate of bile acid biosynthesis, but also steroid hormones and 9,10-phenanthrenequinone. Northern blot analysis on poly(A)+ RNA by selective use of different cDNA fragments of the 5'-untranslated region, the coding region, and the 3'-untranslated region as probes revealed three hybridizable bands, 3.6, 2.7, and 2.5 kb, in liver and four bands, 3.6, 2.7, 2.5, and 1.8 kb, in ovary. Of these, the 2.7- and 1.8-kb bands were predominant in liver and ovary, respectively. Northern hybridization analysis also revealed that the coding region of the various sizes of mRNA seemed to be common. Southern blot analysis of genomic DNA by the selective use of the cDNA fragments as probes indicated that the various mRNA species were derived from a single gene, probably due to an alternative splicing mechanism. (ABSTRACT TRUNCATED AT 250 WORDS)
Attacking with Something That Does Not Exist: Low-Rate Flood with 'Proof of Non-Existence' Can Exhaust DNS Resolver CPU

NSEC3 is a proof of non-existence in DNSSEC, which provides an authenticated assertion that a queried resource does not exist in the target domain. NSEC3 consists of alphabetically sorted hashed names before and after the queried hostname. To make dictionary attacks harder, the hash function can be applied in multiple iterations, which however also increases the load on the DNS resolver during the computation of the SHA-1 hashes in NSEC3 records. Concerns about the load created by the computation of NSEC3 records on the DNS resolvers were already considered in the NSEC3 specifications RFC5155 and RFC9276. In February 2024, the potential of NSEC3 to exhaust DNS resolvers' resources was assigned a CVE-2023-50868, confirming that extra iterations of NSEC3 created substantial load. However, there is no published evaluation of the attack and the impact of the attack on the resolvers was not clarified. In this work we perform the first evaluation of the NSEC3-encloser attack against DNS resolver implementations and find that the NSEC3-encloser attack can still create a 72x increase in CPU instruction count, despite the victim resolver following RFC5155 recommendations in limiting hash iteration counts. The impact of the attack varies across the different DNS resolvers, but we show that with a sufficient volume of DNS packets the attack can increase CPU load and cause packet loss. We find that at a rate of 150 malicious NSEC3 records per second, depending on the DNS implementation, the loss rate of benign DNS requests varies between 2.7% and 30%. We provide a detailed description and implementation the NSEC3-encloser attack along with evaluation against five popular DNS resolver implementations. We also develop the first analysis how each NSEC3 parameter impacts the load inflicted on the victim resolver during NSEC3-encloser attack.
Pluralism, Change, and Corporate Community

ed out of its concrete relations and/or roles can be coherently thouqht of as a functioning self, and that such a "self " can be a decision maker. The self that decides in Rawls' position is decidedly isolated from its social attributes, and the framework which emerges from the theory is a peculiarly atemporal, rationally constructed frame imposed from above upon the contingencies of real life existence and isolated from historically changing conditions. 2. That these philosophers provide a unified perspective is assumed in this article, but this claim is defended at some length in Rosenthal (1986). 3. This use of the pragmatists is basically the same as that utilized by Rosenthal (1986) as well in other books and articles by Buchholz and Rosenthal. 4. Deconstructionist theory, like pragmatism, rejects the ideal of the organization as a smoothly running machine. Likewise, it recognizes that total consensus within an organization, far from being the ideal goal, threatens its very well being (Hassard, 1993). But while deconstruction like pragmatism turns to the relational ingredients of corporate dynamics, each does so in very different ways. While pragmatism turns to the pluralistic features of community and the importance of diversity and conflict in the dynamics of community growth, deconstruction turns to what has been called the "prevalence of creative confusion" (Gergen, 1989). And while pragma tism turns to the sense of community in which even the most dissenting voice enters into the ongoing dynamics of community life with the adjustments and accommodations this requires, deconstruction turns to a dynamic tension between empowerment and disempowerment in order for organizations to sustain themselves. Understanding corporate dynamics in terms of power tensions and creative confusion versus a pluralistic community of voices in communicative interaction are quite different end-products offered respectively by deconstruction and pragmatism as results of a shared rejection of abstract rationality, mechanistic conformity, and other modernist views inherent in traditional theories of the corporation. In short, the different approaches represent the "politics of power" versus the "politics of community. "
Galaxy merger challenge: A comparison study between machine learning-based detection methods

Various galaxy merger detection methods have been applied to diverse datasets. However, it is difficult to understand how they compare. We aim to benchmark the relative performance of machine learning (ML) merger detection methods. We explore six leading ML methods using three main datasets. The first one (the training data) consists of mock observations from the IllustrisTNG simulations and allows us to quantify the performance metrics of the detection methods. The second one consists of mock observations from the Horizon-AGN simulations, introduced to evaluate the performance of classifiers trained on different, but comparable data. The third one consists of real observations from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) survey. For the binary classification task (mergers vs. non-mergers), all methods perform reasonably well in the domain of the training data. At $0.1<z<0.3$, precision and recall range between $\sim$70\% and 80\%, both of which decrease with increasing $z$ as expected (by $\sim$5\% for precision and $\sim$10\% for recall at $0.76<z<1.0$). When transferred to a different domain, the precision of all classifiers is only slightly reduced, but the recall is significantly worse (by $\sim$20-40\% depending on the method). Zoobot offers the best overall performance in terms of precision and F1 score. When applied to real HSC observations, all methods agree well with visual labels of clear mergers but can differ by more than an order of magnitude in predicting the overall fraction of major mergers. For the multi-class classification task to distinguish pre-, post- and non-mergers, none of the methods offer a good performance, which could be partly due to limitations in resolution and depth of the data. With the advent of better quality data (e.g. JWST and Euclid), it is important to improve our ability to detect mergers and distinguish between merger stages.
Parent Involvement: Investigating the Parent-Child Relationship in Millennial College Students

There is evidence of a surge in parent involvement in postsecondary education, and some scholarship suggests that this high level of parent involvement may inhibit epistemological development. Despite these claims, there is little empirical evidence on the level or impact of parent involvement during the college years. The aim of this research was to understand the level and type of college student initiated parent involvement. Results suggest that, although the majority of participants did not involve their parents in decision making, many participants did, but the type of parent involvement ranged from confrontation to thinking about parental expectations. Epistemological orientation was not related to level of parent involvement but did predict type of parent involvement. Theoretical implications are discussed.
EMPLOYEE EMPOWERMENT IN THE GREEK CONTEXT

Purpose – The purpose of the article is to examine the validity and reliability of Spreitzer's and Menon's instruments in a culturally diverse environment. To test whether individualized measures of Hofstede's cultural dimensions are related to employee empowerment in the Greek context.Design/methodology/approach – To investigate the multidimensional nature of the empowerment construct and the discriminant validity and reliability of its basic dimensions principal component analysis with varimax rotation is conducted. Furthermore, correlation analysis is employed to examine the relationship between empowerment, power distance and uncertainty avoidance and to compare current with existing findings. The analysis is based on valid responses from 154 Greek employed students to self‐administered surveys.Findings – Overall, the results of the present study are congruent with the literature in the area, confirming the usefulness of a view of empowerment characterized by the dimensions of perceived control (or im.
Effect of leupeptin on the autophagic vacuolar system of rat hepatocytes. Correlation between ultrastructure and degradation of membrane and cytosolic proteins.

Injection of leupeptin (an inhibitor of lysosomal cathepsins B, H, and L) to nonstarved rats causes an expansion of the autophagic vacuolar (AV) system in hepatocytes. Readily identifiable cytoplasmic constituents were seen within the AVs shortly after the administration. Later, the contents of the AVs seemed to reach more advanced stages of degradation. Liver AVs were purified by a one-step centrifugation of a crude mitochondrial lysosomal fraction in a discontinuous metrizamide gradient after exposing the rats to leupeptin for varying periods of time. Leupeptin caused alterations of the AV fraction that were time dependent. Initially, i.e., after 30 minutes of leupeptin exposure, mature (secondary) lysosomes clearly dominated over nascent AVs. The situation was reversed when fractionation was performed 1 or 2 hours following the injection of leupeptin. Now, the AVs were more frequent than the mature lysosomes. Later, the proportion of mature lysosomes was again larger. An increase in dense bodies was noted after 16 hours of leupeptin treatment. The proteolytic capacity of the AVs at different stages of maturation was measured after labeling liver proteins with an injection of L-1-14C-leucine 16 hours before sacrifice. AVs were purified after varying times of exposure to leupeptin. The proteolysis decreased greatly 1 to 2 hours following the injection of leupeptin but never ceased. On the other hand, lipolysis seemed unaffected by leupeptin using a similar experimental protocol as for proteolysis. If the animals were subjected to more lasting exposure to leupeptin before fractionation, proteolysis increased, displaying a peak higher than control, occurring after approximately 4 hours. The degradation gradually returned to control values after 16 hours. A catch-up in proteolysis was thus observed. The time course of proteolysis was reflected in the protein content in the AV fraction. After an initial increase that coincided with the lowered proteolysis, it returned to control level. Marker enzyme activities for endoplasmic reticulum and mitochondria (G6Pase and succinate-cytochrome c reductase) followed the same pattern. The AV content of the cytosolic enzymes lactate dehydrogenase and aldolase reached as high as 2.30 and 2.80% of the values in the homogenate during the 1st hour of leupeptin exposure. From these data the half-lives of the enzymes were calculated. They were: for aldolase, 43 hours; for LDH, 68 hours. This suggests that AVs account for a substantial proportion of degradation not only of organelles but also of soluble cytosolic enzymes.
Identifying the genomic determinants of aging and longevity in human population studies: Progress and challenges

Human lifespan variation is mainly determined by environmental factors, whereas the genetic contribution is 25–30% and expected to be polygenic. Two complementary fields go hand in hand in order to unravel the mechanisms of biological aging: genomic and biomarker research. Explorative and candidate gene studies of the human genome by genetic, transcriptomic, and epigenomic approaches have resulted in the identification of a limited number of interesting positive linkage regions, genes, and pathways that contribute to lifespan variation. The possibilities to further exploit these findings are rapidly increasing through the use of novel technologies, such as next‐generation sequencing. Genomic research is progressively being integrated with biomarker studies on aging, including the application of (noninvasive) deep phenotyping and omics data – generated using novel technologies – in a wealth of studies in human populations. Hence, these studies may assist in obtaining a more holistic perspective on the role of the genome in aging and lifespan regulation.