Miracle-dz/UniFAR-FTUs huggingface dataset:
Distinguishing Interpersonal and Ideological Prosociality: Introducing the Construct of Ideological Prosociality

Prosociality refers to dispositions and behaviors intended to benefit others, and the present study assumed that these dispositions reflect people’s values. Much of the research on prosociality has examined prosociality in what can be called the interpersonal domain, e.g., helping others. I propose that prosociality also exists in the ideological domain. People hold prosocial values that concern collectives, not specific individuals. Multilevel analyses of data collected in Wave 8 of the European Social Survey (44,000 respondents in 23 countries) found positive relationships between ideological prosocial values and attitudes toward immigrants, refugees, and gays and lesbians, attitudes about the environment and climate change, social benefits, and income equality. Moreover, these relationships remained significant after controlling for participants’ sex, age, income, education, political orientation, and happiness. In contrast, relationships between these attitudes and interpersonal prosocial values were either negative or not significant.
Towards Minimizing the $R$ Metric for Measuring Network Robustness

With the prevalence of cyber-attacks on infrastructure networks such as the Internet backbone, measuring the robustness of network topologies has become a critical issue. To this end, a metric called ‘<inline-formula><tex-math notation="LaTeX">$R$</tex-math></inline-formula>’ has been proposed and widely used. ‘<inline-formula><tex-math notation="LaTeX">$R$</tex-math></inline-formula>’ assumes that an attack on a network consists of <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula> rounds of node removals with one node removed each round, where <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula> is the number of nodes in the network. Since the value of <inline-formula><tex-math notation="LaTeX">$R$</tex-math></inline-formula> depends on the sequence of node removals, finding the sequence minimizing <inline-formula><tex-math notation="LaTeX">$R$</tex-math></inline-formula> becomes an interesting problem, denoted as Min-R hereafter. Although many heuristic approaches have been proposed for Min-R, there has been no optimal polynomial-time algorithm given so far, nor is Min-R proved NP-hard. To fill this gap, this paper presents the following fundamental results. First, to minimize <inline-formula><tex-math notation="LaTeX">$R$</tex-math></inline-formula>, a node needs to be always removed from the largest connected component of the current network in each round. Second, the Min-R problem has an Optimal Substructure, which allows it to be solved by Dynamic Programming in exponential time instead of the naive factorial time on general graphs. Finally, an efficient and optimal logarithmic-time algorithm is given for Min-R on path graphs, with its complexity and optimality proved.
How Ride‐Sharing Is Shaping Public Transit System: A Counterfactual Estimator Approach

The new sharing economy model has introduced a dramatic, disruptive impact on the traditional industries by matching the demand and supply in real time. In this study, we examine how the entry of Uber, a ride‐sharing services digital platform, brings new disruptive changes in public transportation operations. Significant debate has surrounded whether the new ride‐sharing model siphoned riders from public transit or made public transit feasible for more riders, but no consensus has been reached. One reason could be that the commonly used difference‐in‐differences empirical strategy fails to account for time‐varying unobserved confounders. To address this issue, we introduce a class of counterfactual estimators (CEs) to strengthen our causal identification and perform diagnostic tests to validate model assumptions for each CE. A significant drop in passenger trips with buses is found after Uber entry from both the conventional two‐way fixed effects model and the CEs. Moreover, we provide empirical evidence that the entry of Uber has not significantly affected public demand response transportation, which indicates that Uber is not directly competing with other transportation services that aim to solve the “last‐mile problem. ” Last, our additional analyses suggest that the effect of Uber entry is not uniform for different urban areas. All these empirical findings can be coherently explained in our framework of the substitution effect of Uber.
Characterization and Molecular Docking of Kaolin Based Cellulosic Film for Extending Ophthalmic Drug Delivery

Ophthalmic delivery of dexamethasone can control inflammation and also some forms of uveitis. But it is effective therapeutically over a short period of time and frequent instillation is required. Hydroxypropyl methylcellulose matrix films containing dexamethasone were prepared by casting method in presence and absence of particulate kaolin for extending ophthalmic drug delivery. Fourier-transform infrared spectroscopy confirmed the complexation of dexamethasone and kaolin in the film via formation of hydrogen bond and the observed shouldering at 1032 cm-1 increased with corresponding higher amount of kaolin binding. Differential scanning calorimetry thermogram resulted in almost complete amorphization of dexamethasone in the film. X-ray diffractogram demonstrated almost disappearance of kaolinite diffraction and the reduced order of dexamethasone crystal lattice in all the film formulations. Submicrons, tubular and nano-fibrous morphology of the kaolin and drug particles were seen in the scanning electron microscope images of the film. Relatively extended diffusion controlled drug release and ophthalmic permeation behavior were observed with the increase of kaolin loading in the film. Stable complex facilitated the sustained ophthalmic delivery of dexamethasone and prolonged anti-inflammatory activity. Molecular docking study also revealed the complex formation of dexamethasone with kaolin and hydroxypropyl methyl cellulose to understand the fitting and stable configuration of drug-carrier interaction. Kaolin-based hydroxypropyl methyl cellulose hydrogel film containing dexamethasone as a model drug can enhance the corneal residence time for anti-inflammation for an extended period of time.
Extracellular Vesicles in Human Milk

Milk supports the growth and development of infants. An increasing number of mostly recent studies have demonstrated that milk contains a hitherto undescribed component called extracellular vesicles (EVs). This presents questions regarding why milk contains EVs and what their function is. Recently, we showed that EVs in human milk expose tissue factor, the protein that triggers coagulation or blood clotting, and that milk-derived EVs promote coagulation. Because bovine milk, which also contains EVs, completely lacks this coagulant activity, important differences are present in the biological functions of human milk-derived EVs between species. In this review, we will summarize the current knowledge regarding the presence and biochemical composition of milk EVs, their function(s) and potential clinical applications such as in probiotics, and the unique problems that milk EVs encounter in vivo, including survival of the gastrointestinal conditions encountered in the newborn. The main focus of this review will be human milk-derived EVs, but when available, we will also include information regarding non-human milk for comparison.
Realistic Smile Expression Recognition Approach Using Ensemble Classifier with Enhanced Bagging

: A robust smile recognition system could be widely used for many real-world applications. Classification of a facial smile in an unconstrained setting is difficult due to the invertible and wide variety in face images. In this paper, an adaptive model for smile expression classification is suggested that integrates a fast features extraction algorithm and cascade classifiers. Our model takes advantage of the intrinsic association between face detection, smile, and other face features to alleviate the over-fitting issue on the limited training set and increase classification results. The features are extracted taking into account to exclude any unnecessary coefficients in the feature vector; thereby enhancing the discriminatory capacity of the extracted features and reducing the computational process. Still, the main causes of error in learning are due to noise, bias, and variance. Ensemble helps to minimize these factors. Combinations of multiple classifiers decrease variance, especially in the case of unstable classifiers, and may produce a more reliable classification than a single classifier. However, a shortcoming of bagging as the best ensemble classifier is its random selection, where the classification performance relies on the chance to pick an appropriate subset of training items. The suggested model employs a modified form of bagging while creating training sets to deal with this challenge (error-based bootstrapping). The experimental results for smile classification on the JAFFE, CK+, and CK+48 benchmark datasets show the feasibility of our proposed model.
Multiclass Cucumber Leaf Diseases Recognition Using Best Feature Selection

Agriculture is an important research area in the field of visual recognition by computers. Plant diseases affect the quality and yields of agriculture. Early-stage identificationof crop disease decreases financial losses and positively impacts crop quality. The manual identification of crop diseases, which aremostly visible on leaves, is a very time-consuming and costly process. In this work, we propose a new framework for the recognition of cucumber leaf diseases. The proposed framework is based on deep learning and involves the fusion and selection of the best features. In the feature extraction phase, VGG (Visual Geometry Group) and Inception V3 deep learning models are considered and fine-tuned. Both fine-tuned models are trained using deep transfer learning. Features are extracted in the later step and fused using a parallel maximum fusion approach. In the later step, best features are selected using Whale Optimization algorithm. The best-selected features are classified using supervised learning algorithms for the final classification process. The experimental process was conducted on a privately collected dataset that consists of five types of cucumber disease and achieved accuracy of 96.5%. A comparison with recent techniques shows the significance of the proposed method.
Basin evolution in response to flat-slab subduction in the Altiplano

This paper assesses models for basin formation in the Altiplano. New magnetostratigraphy, palynology, and 40Ar/39Ar and U–Pb geochronology from the central Corque Syncline show that the 7.4 km thick section was deposited between 36.7 and 18.7 Ma. The base of the section post-dates exhumation in both the Western and Eastern cordilleras, precluding deposition in a classic retroarc foreland basin setting. Rotated palaeomagnetic vectors indicate counterclockwise rotation of 0.8° (myr)−1 since the early Oligocene. Detrital zircon provenance data confirm previous interpretations of Eocene–early Oligocene derivation from the Western Cordillera and a subsequent switch to an Eastern Cordilleran source. Flexural modelling indicates that loads consistent with palaeoelevation estimates cannot account for all the subsidence. Rather, the timing and magnitude of subsidence is consistent with Eocene emplacement and Oligocene–early Miocene re-steepening of a flat slab. Integration of the magmatic, basin and deformation history provides a coherent model of the effects of flat-slab subduction on the overriding plate. In this model, basin formation in the upper plate was controlled by flat-slab subduction, with subsidence enhanced in front of the zone of flat-slab subduction, but reduced over the crest of the flat slab. We conclude that the Altiplano was conditioned for plateau formation by Eocene–Oligocene flat-slab subduction. Supplementary material: Supplemental Tables S1–S10 are available at https://doi.org/10.6084/m9.figshare. c.5664345 Thematic collection: This article is part of the Fold-and-thrust belts collection available at: https://www.lyellcollection. org/cc/fold-and-thrust-belts
La participación de las cinasas de proteínas activadas por mitógenos en la señalización por hormonas en Arabidopsis thaliana L.

Los módulos de señalización mediados por cinasas de proteína activadas por mitógenos o MAPK (Mitogen-Activated Protein Kinases, por sus siglas en inglés), participan en la transducción de distintos tipos de señales mediante la fosforilación de diversos sustratos como las enzimas, componentes estructurales, factores transcripcionales e incluso otras cinasas. Estos módulos están conformados por miembros de tres familias de proteinas diferentes, denominadas MAPK, MEK o MAPKK (MAP cinasa cinasa) y MEKK o MAPKKK (MAP cinasa cinasa cinasa), que se activan de manera secuencial por la fosforilación de residuos de aminoácidos localizados en el dominio de activación. Mediante cascadas de MAPK las células responden a distintos tipos de estrés, además, se ha demostrado que las hormonas vegetales también ejercen su efecto en los programas de crecimiento y desarrollo de las plantas a través de estas mismas vías de señalización. En este trabajo se presenta un panorama general de los diversos mecanismos de señalización por hormonas en Arabidopsis thaliana L. , en los que están involucradas cascadas de señalización de MAPK.
Calendar anomalies in African stock markets

Abstract In this paper, we investigate the day of the week and the month of the year effects in African stock markets, both in the Gregorian and the Hijri calendars. Specifically, we investigate Monday effect, Friday effect, January effect and Ramadan effect, from January 2009 to December 2019, using OLS regression with robust standard errors. January is the first month of the Gregorian calendar, while Ramadan is the 9th and the most sacred month of the lunar calendar, used in Muslim countries. The results obtained show the existence of Monday effect in BRVM and Namibia, Friday effect in Kenya and Namibia, January effect in Botswana and Zambia, December effect in Botswana, BRVM and Egypt and Ramadan effect in Tunisia.
Climate change impacts on sea-ice ecosystems and associated ecosystem services

A rigorous synthesis of the sea-ice ecosystem and linked ecosystem services highlights that the sea-ice ecosystem supports all 4 ecosystem service categories, that sea-ice ecosystems meet the criteria for ecologically or biologically significant marine areas, that global emissions driving climate change are directly linked to the demise of sea-ice ecosystems and its ecosystem services, and that the sea-ice ecosystem deserves specific attention in the evaluation of marine protected area planning. The synthesis outlines (1) supporting services, provided in form of habitat, including feeding grounds and nurseries for microbes, meiofauna, fish, birds and mammals (particularly the key species Arctic cod, Boreogadus saida, and Antarctic krill, Euphausia superba, which are tightly linked to the sea-ice ecosystem and transfer carbon from sea-ice primary producers to higher trophic level fish, mammal species and humans); (2) provisioning services through harvesting and medicinal and genetic resources; (3) cultural services through Indigenous and local knowledge systems, cultural identity and spirituality, and via cultural activities, tourism and research; (4) (climate) regulating services through light regulation, the production of biogenic aerosols, halogen oxidation and the release or uptake of greenhouse gases, for example, carbon dioxide. The ongoing changes in the polar regions have strong impacts on sea-ice ecosystems and associated ecosystem services. While the response of sea-ice–associated primary production to environmental change is regionally variable, the effect on ice-associated mammals and birds is predominantly negative, subsequently impacting human harvesting and cultural services in both polar regions. Conservation can help protect some species and functions. However, the key mitigation measure that can slow the transition to a strictly seasonal ice cover in the Arctic Ocean, reduce the overall loss of sea-ice habitats from the ocean, and thus preserve the unique ecosystem services provided by sea ice and their contributions to human well-being is a reduction in carbon emissions.
Randomized controlled trial of once-per-week intermittent fasting for health improvement: the WONDERFUL trial

Abstract Aims Low-density lipoprotein cholesterol (LDL-C) predicts heart disease onset and may be reduced by intermittent fasting. Some studies, though, reported that fasting increased LDL-C; however, no study evaluated LDL-C as the primary endpoint. This randomized controlled trial evaluated the effect of low-frequency intermittent fasting on LDL-C and other biomarkers. Methods and results Adults aged 21–70 years were enrolled who were not taking a statin, had modestly elevated LDL-C, had ≥1 metabolic syndrome feature or type 2 diabetes, and were not taking anti-diabetic medication (N = 103). Water-only 24-h fasting was performed twice weekly for 4 weeks and then once weekly for 22 weeks; controls ate ad libitum. The primary outcome was 26-week LDL-C change score. Secondary outcomes (requiring P ≤ 0.01) were 26-week changes in homeostatic model assessment of insulin resistance (HOMA-IR), Metabolic Syndrome Score (MSS), brain-derived neurotrophic factor (BDNF), and MicroCog general cognitive proficiency index (GCPi). Intermittent fasting (n = 50) and control (n = 53) subjects were, respectively, aged 49.3 ± 12.0 and 47.0 ± 9.8 years, predominantly female (66.0% and 67.9%), and overweight (103 ± 24 and 100 ± 21 kg) and had modest LDL-C elevation (124 ± 19 and 128 ± 20 mg/dL). Drop-outs (n = 12 fasting, n = 20 control) provided an evaluable sample of n = 71 (n = 38 fasting, n = 33 control). Intermittent fasting did not change LDL-C (0.2 ± 16.7 mg/dL) vs. control (2.5 ± 19.4 mg/dL; P = 0.59), but it improved HOMA-IR (−0.75 ± 0.79 vs. −0.10 ± 1.06; P = 0.004) and MSS (−0.34 ± 4.72 vs. 0.31 ± 1.98, P = 0.006). BDNF (P = 0.58), GCPi (P = 0.17), and weight (−1.7 ± 4.7 kg vs. 0.2 ± 3.5 kg, P = 0.06) were unchanged. Conclusions A low-frequency intermittent fasting regimen did not reduce LDL-C or improve cognitive function but significantly reduced both HOMA-IR and MSS. Trial registration clinicaltrials.gov, NCT02770313.
Shielding of Cosmic Radiation by Fibrous Materials

Cosmic radiation belongs to the challenges engineers have to deal with when further developing space travel. Besides the severe risks for humans due to high-energy particles or waves, the impact of cosmic radiation on electronics and diverse materials cannot be neglected, even in microsatellites or other unmanned spacecraft. Here, we explain the different particles or waves found in cosmic radiation and their potential impact on biological and inanimate matter. We give an overview of fiber-based shielding materials, mostly applied in the form of composites, and explain why these materials can help shielding spaceships or satellites from cosmic radiation.
TECHNOLOGICAL AGNOSTICISM AND CLIMATE CHANGE: PLATFORM CULTURE ON
 TECHNOLOGY FORUM WHIRLPOOL

This paper explores the (limited) discussion of climate change within energy debates on Australian technology forum Whirlpool. These discussions are characterised by $2 , which is an attitude that no technology is $2 or $2 than any other because different technologies have different applications depending on the requirement. By completing a thematic analysis of all Whirlpool replies within four threads centred on energy debates (n = 3,101), I observed Whirlpool contributors depoliticise energy technologies by removing climate change as a factor when considering technology choices. Overall, I found that when technological agnosticism was expressed within these debates, it intersected with issues concerning the $2 , $2 , $2 , and $2 of technology and pushed against concerns regarding climate change. I argue that the prevalence of technological agnosticism within these debates is not an example of climate change denial per se but a reflection of Whirlpool’s platform culture which valorises traits of $2 such as rationality and neutrality (Massanari, 2017). I conclude by comparing Whirlpool’s platform culture to Reddit and suggest that future research ought to explore how particular platform cultures shape energy debates and ultimately, attitudes and action towards climate change.
Optimal Combinations of Chemotherapy and Radiotherapy in Low-Grade Gliomas: A Mathematical Approach

Low-grade gliomas (LGGs) are brain tumors characterized by their slow growth and infiltrative nature. Treatment options for these tumors are surgery, radiation therapy and chemotherapy. The optimal use of radiation therapy and chemotherapy is still under study. In this paper, we construct a mathematical model of LGG response to combinations of chemotherapy, specifically to the alkylating agent temozolomide and radiation therapy. Patient-specific parameters were obtained from longitudinal imaging data of the response of real LGG patients. Computer simulations showed that concurrent cycles of radiation therapy and temozolomide could provide the best therapeutic efficacy in-silico for the patients included in the study. The patient cohort was extended computationally to a set of 3000 virtual patients. This virtual cohort was subject to an in-silico trial in which matching the doses of radiotherapy to those of temozolomide in the first five days of each cycle improved overall survival over concomitant radio-chemotherapy according to RTOG 0424. Thus, the proposed treatment schedule could be investigated in a clinical setting to improve combination treatments in LGGs with substantial survival benefits.
One Hundred Years of Insulin

The 1923 Nobel Prize in Physiology or Medicine was awarded jointly to Canadian physician Frederick Grant Banting (1891-1941) and Scottish biochemist and physiologist John James Macleod (1876-1935) “for the discovery of insulin”. It was a remarkable finding since diabetes mellitus was an untreatable and often lethal disease until then. Much has been written about Banting and Macleod’s breakthrough research conducted at the University of Toronto starting in November 1920, including the key roles played by their trustworthy assistants, medical student Charles Best and biochemist James Collip. On the other hand, much less has been written about the pioneering research of Romanian physiologist Nicolae Paulescu (1869-1931), whose work on the metabolic effects of canine pancreatic extracts predates that of Banting and Macleod but was interrupted by World War I. Should Best, Collip, or Paulescu have also shared the Nobel Prize?