Miracle-dz/UniFAR-FTUs huggingface dataset:
Filogenia de Lysiloma (Fabaceae), un género restringido a Megaméxico con especies atípicas en las Antillas y Florida

Antecedentes y Objetivos: Lysiloma es un género neotropical de la familia Fabaceae que comprende ocho especies, seis de las cuales se distribuyen ampliamente en México y dos más que ocurren en las Antillas y La Florida. Lysiloma es frecuente en los bosques secos de Megaméxico. Un estudio filogenético previo incluyó tres especies de Lysiloma y Hesperalbizia occidentalis. Ambos géneros están estrechamente relacionados, pero su divergencia tiene un apoyo débil. Nuestros objetivos fueron probar la monofilia del género, evaluar las relaciones de grupo hermano dentro del género y estimar los tiempos de divergencia. Métodos: Se realizó un análisis filogenético basado en caracteres morfológicos, marcadores moleculares (ETS, matK y trnK), así como un análisis combinado (morfología + moléculas). Las matrices de datos se analizaron tanto individualmente como concatenadas (enfoque de evidencia total) con inferencia Bayesiana y máxima parsimonia. Además, los tiempos de divergencia molecular se estimaron a partir del conjunto de datos ETS con un modelo de reloj bayesiano relajado lognormal no correlacionado. Resultados clave: El análisis morfológico respalda la monofilia del Lysiloma con Hesperalbizia como grupo hermano. Sin embargo, los análisis moleculares individuales y combinado no proporcionan resolución para aclarar las relaciones entre Hesperalbizia occidentalis, Lysiloma sabicu y el núcleo de Lysiloma. El análisis de evidencia total (incluida la morfología) respalda la monofilia de Lysiloma, pero con un bajo soporte. Según nuestro modelo de reloj molecular, el clado Lysiloma+Hesperalbizia se separó de otros miembros de la tribu Acacieae+Ingeae hace unos 32 millones de años y la diversificación del núcleo del Lysiloma se produjo a lo largo del Mioceno.Conclusiones: Lysiloma+Hesperalbizia es un clado de divergencia temprana de las tribus Acacieae+Ingeae. Existen suficientes diferencias morfológicas para reconocer ambos linajes. Los caracteres morfológicos utilizados informalmente para la delimitación taxonómica parecen haber evolucionado de manera homoplásica. El clado de Lysiloma y Hesperalbizia se separó de otros miembros de la tribu Acacieae+Ingeae en el Oligoceno, pero la diversificación del núcleo del género coincidió con la expansión del bosque seco a principios del Mioceno.
Access and benefit‐sharing DNA Componentry for plant synthetic biology: Bioparts expressed in plant chassis

This is an open access article under the terms of the Creative Commons AttributionNonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. © 2021 The Authors. Plants, People, Planet © New Phytologist Foundation 1Law Futures Centre, Griffith University, Nathan, Queensland, Australia 2CSIRO Synthetic Biology Future Science Platform, Brisbane, Queensland, Australia
Too Long to Wait: South Asian Migrants’ Experiences of Accessing Health Services in Australia

Background: Migrants settling in a new country experience multiple complexity to navigate health systems and ways of living. In South Asia, migrating to developed countries for better life opportunities has been the ongoing trend and migration to Australia has significantly increased in recent years. The lower utilisation services and higher risks of chronic diseases among South Asian migrants has been an ongoing challenge for the health system to tackle and little is known why these groups of population do not access services. This study aimed to explore the factors influencing experiences of accessing health services by South Asian migrants in Australia. Methods: Using mixed method design, 62 online surveys and 14 in-depth interviews were conducted with participants from four countries of South Asia - Nepal, India, Bhutan, and Sri Lanka. Participants were recruited using a purposive snowball sampling approach following the standard ethical process. Survey data were analysed descriptively in SPSS to derive relationships between variables. Interview data were recorded, transcribed, and analysed thematically. Results: South Asian migrants experienced various complexities while accessing health services in Australia. Experiences of accessing health services highlighted a number of factors; long waiting periods to access public health services, expensive nature of private health services and communication problems due to socio-cultural differences. While these migrants have comparatively better experiences about the services in Australia than in their home country, they have expectations for affordable, timely, respectful, and culturally friendly services. South Asian migrants shared the possibility of making services accessible to them by investing more resources in the health sectors, so they can receive the expected quality of care in public settings. Conclusions: Limited evidence is available to understand the factors leading to lower utilisation of services and higher risks of chronic diseases among South Asian migrants. So, this study highlighted numbers of social, cultural, financial, and institutional factors that are critical to design appropriate health service strategies. This study recommended incorporating a collaborative and culturally competent model of care to increase access to services which can further help to reduce existing disparities in health outcomes among migrant populations.
Impacts of climate projections on water balance and implications on olive crop in Minas Gerais

Minas Gerais apresenta-se vulneravel as mudancas climaticas com impactos no balanco hidrico e alteracoes nas areas destinadas ao cultivo de diversas culturas. Atualmente, a oliveira se mostra como uma alternativa de renda para os agricultores mineiros especialmente os do sul do estado. No entanto, nao se tem informacoes sobre as areas com maior aptidao ao seu plantio, assim como as possiveis implicacoes das mudancas climaticas. O objetivo deste estudo foi verificar o impacto das projecoes climaticas no balanco hidrico e no zoneamento agroclimatico para a cultura da oliveira em Minas Gerais baseado nas condicoes de clima atual (1980-2011) e futuro considerando-se diferentes projecoes de mudancas climaticas, para tres periodos (2011-2040, 2041-2070 e 2071-2100). Para o clima atual, Minas Gerais apresentou 37% de area apta, 15% de area marginal e 48% de area inapta ao cultivo de oliveira. Para o periodo de 2071-2100 apenas 4% foram classificadas como aptas, 6% como marginal e 90% como inapta. As projecoes de mudancas climaticas, tanto em temperatura quanto em precipitacao, irao afetar o cultivo de oliveira reduzindo substancialmente a area apta ao seu cultivo, no estado.
Fraud Detection: A Study of AdaBoost Classifier and K-Means Clustering

Fraud is a problem which can affect the economy greatly. Billions of dollars are lost because of fraud cases. These problems can occur through credit cards, insurance and bank accounts. Currently there have been many studies for preventing fraud. Machine learning techniques have helped in analysing fraud detection. These include many supervised and unsupervised models. Neural networks can be used for fraud detection. The dataset for the present work was collected from a research collaboration between Worldline and the Machine Learning Group of Université Libre de Bruxelles on the topic of big data mining and fraud detection. It consists of the time and amount of various transactions of European card holders during the month of September in 2013. This paper gives an analysis of the past and the present models used for fraud detection and presents a study of using K-Means Clustering and AdaBoost Classifier by comparing their accuracies.
Optimization of a Depiction Procedure for an Artificial Intelligence-Based Network Protection System Using a Genetic Algorithm

The current demand for remote work, remote teaching and video conferencing has brought a surge not only in network traffic, but unfortunately, in the number of attacks as well. Having reliable, safe and secure functionality of various network services has never been more important. Another serious phenomenon that is apparent these days and that must not be discounted is the growing use of artificial intelligence techniques for carrying out network attacks. To combat these attacks, effective protection methods must also utilize artificial intelligence. Hence, we are introducing a specific neural network-based decision procedure that can be considered for application in any flow characteristic-based network-traffic-handling controller. This decision procedure is based on a convolutional neural network that processes the incoming flow characteristics and provides a decision; the procedure can be understood as a firewall rule. The main advantage of this decision procedure is its depiction process, which has the ability to transform the incoming flow characteristics into a graphical structure. Graphical structures are regarded as very efficient data structures for processing by convolutional neural networks. This article’s main contribution consists of the development and improvement of the depiction process using a genetic algorithm. The results presented at the end of the article show that the decision procedure using an optimized depiction process brings significant improvements in comparison to previous experiments.
Happiness Begets Money: Emotion and Engagement in Live Streaming

Live streaming offers an unprecedented opportunity for content creators (broadcasters) to deliver their content to consumers (viewers) in real time. In a live stream, viewers may send virtual gifts (tips) to the broadcaster and engage with likes and chats free of charge. These activities reflect viewers’ underlying emotion and are likely to be affected by the broadcaster’s emotion. This article examines the role of emotion in interactive and dynamic business settings such as live streaming. To account for the possibility that broadcaster emotion, viewer emotion, and viewer activities influence each other, the authors estimate a panel vector autoregression model on data at the minute level from 1,450 live streams. The results suggest that a happier broadcaster makes the audience happier and begets intensified viewer activities, in particular tips. In addition, broadcasters reciprocate viewer engagement with more smiles. Further analyses suggest that these effects are pronounced only after a live stream has been active for a while, and they manifest only in streams by broadcasters who have more experience, receive more tips, or are more popular in past live streams. These results help platforms and broadcasters optimize marketing interventions such as broadcaster emotion enhancement in live streaming and quantify the financial returns.
Genetic Variability and Population Structure of Ethiopian Sesame (Sesamum indicum L.) Germplasm Assessed through Phenotypic Traits and Simple Sequence Repeats Markers

Ethiopia is one of the centers of genetic diversity of sesame (Sesamum indicum L.). The sesame genetic resources present in the country should be explored for local, regional, and international genetic improvement programs to design high-performing and market-preferred varieties. This study’s objective was to determine the extent of genetic variation among 100 diverse cultivated sesame germplasm collections of Ethiopia using phenotypic traits and simple sequence repeat (SSR) markers to select distinct and complementary genotypes for breeding. One hundred sesame entries were field evaluated at two locations in Ethiopia for agro-morphological traits and seed oil content using a 10 × 10 lattice design with two replications. Test genotypes were profiled using 27 polymorphic SSR markers at the Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences. Analysis of variance revealed significant (p ≤ 0.05) entry by environment interaction for plant height, internode length, number of secondary branches, and grain yield. Genotypes such as Hirhir Kebabo Hairless-9, Setit-3, Orofalc ACC-2, Hirhir Humera Sel-6, ABX = 2-01-2, and Setit-1 recorded grain yield of >0.73 ton ha−1 with excellent performance in yield component such as oil yield per hectare. Grain yield had positive and significant (p < 0.01) associations with oil yield (r = 0.99), useful for simultaneous selection for yield improvement in sesame. The SSR markers revealed gene diversity and polymorphic information content values of 0.30 and 0.25, respectively, showing that the tested sesame accessions were genetically diverse. Cluster analysis resolved the accessions into two groups, while population structure analysis revealed four major heterotic groups, thus enabling selection and subsequent crossing to develop breeding populations for cultivar development. Based on phenotypic and genomic divergence, the following superior and complementary genotypes: Hirhir Humera Sel-6, Setit-3, Hirhir Kebabo Hairless Sel-4, Hirhir Nigara 1st Sel-1, Humera-1 and Hirhir Kebabo Early Sel-1 (from cluster II-a), Hirhir kebabo hairless-9, NN-0029(2), NN0068-2 and Bawnji Fiyel Kolet, (from cluster II-b). The selected genotypes will serve as parents in the local breeding program in Ethiopia.
Cloning and training collective intelligence with generative adversarial networks

Vagan Terziyan, Faculty of Information technology, University of Jyväskylä, Jyväskylä, Finland. Email: vagan.terziyan@jyu.fi Abstract Industry 4.0 and highly automated critical infrastructure can be seen as cyber‐physical‐ social systems controlled by the Collective Intelligence. Such systems are essential for the functioning of the society and economy. On one hand, they have flexible infrastructure of heterogeneous systems and assets. On the other hand, they are social systems, which include collaborating humans and artificial decision makers. Such (human plus machine) resources must be pre‐trained to perform their mission with high efficiency. Both human and machine learning approaches must be bridged to enable such training. The importance of these systems requires the anticipation of the potential and previously unknown worst‐case scenarios during training. In this paper, we provide an adversarial training framework for the collective intelligence. We show how cognitive capabilities can be copied (“cloned”) from humans and trained as a (responsible) collective intelligence. We made some modifications to the Generative Adversarial Networks architectures and adapted them for the cloning and training tasks. We modified the Discriminator component to a so‐called “Turing Discriminator”, which includes one or several human and artificial discriminators working together. We also discussed the concept of cellular intelligence, where a person can act and collaborate in a group together with their own cognitive clones.
Environmental Conditions, and Phenolic Compounds Potential in the Leaves of Vitis Tiliifolia

The wild vine Vitis tiliifolia is found in Mexico, Central América, and the Caribbean region. In the Veracruz State, in Mexico, grows in several municipalities and is used for nutritional and therapeutic purposes. The geographical distribution and environment where this Vitis grow has not been recorded. The leaves of V. tiliifolia are rich in phenolic compounds but potential areas with vines of high phenolic compounds are unknown. An agroecological zoning model to identify potential areas for the cultivation and development of this species was performed. Potential areas having wild vines of high phenolic compounds in the leaves were also determined. The model included 95 vine georeferences, obtained from four municipalities of central Veracruz. These were analyzed with maximum entropy modeling, mapped with ArcMap software, and correlated with the phenolic compounds found in leaves collected in the georeferenced areas. A zoning map was produced, with a potential area of ​​2763.72 km2, which included the states of San Luis Potosi, Hidalgo, Veracruz, Puebla, Oaxaca, and Chiapas. Agroclimatic variables of seasonality of temperature, precipitation, and organic matter in the soil were the most important for the development of this species. In the state of Veracruz, vines with the potential of high phenolic content were found in 29 municipalities with characteristics suitable for its cultivation. The highest phenolic content potential was found at altitudes between 1000 and 2000 meters in the municipalities of Huatusco and Cosautlán in the State of Veracruz.
Integral field spectroscopy of luminous infrared main-sequence galaxies at cosmic noon

We present the results of an integral field spectroscopy survey of a sample of dusty (ultra) luminous infrared galaxies (U/LIRGs) at 2 < z < 2.5 using KMOS on the Very Large Telescope. The sample has been drawn from Herschel deep field surveys and benefits from ancillary multiwavelength data. Our goal is to investigate the physical characteristics, kinematics, and the drivers of star formation in the galaxies whose contribution dominates the peak of the cosmic star formation density. Two-thirds of the sample are main-sequence galaxies in contrast to the starburst nature of local U/LIRGs. Our kinematic study, unique in its focus on z ∼ 2 dusty star-forming galaxies, uses the H α emission line to find that ∼40 per cent appear to be isolated discs based on the ratio of rotational velocity to the velocity dispersion, suggesting steady-state mechanisms are sufficient to power the large star formation rates (SFRs). The ratio of obscured to unobscured star formation indicates the sample of galaxies experiences less dust obscuration compared to intermediate and local counterparts, while also hosting cooler dust than local U/LIRGs. In addition to H α we detect [N ii] 6583 Å in our targets and show the gas-phase metallicities do not exhibit the metal deficiency of local U/LIRGs. These results indicate that, despite their extreme IR luminosity, the underlying mechanisms driving the massive SFRs found at cosmic noon are due to scaled up disc galaxies as opposed to mergers.
Supporting industrial processes by monitoring and visualizing collaborations

In modern dynamic industrial engineering collaboration contexts, professionals such as the facilitators or meeting coordinators, are required to guide participants before, during and after a collaborative process in order to evaluate individual and group performances and the levels of idea generation, discussion, etc. This paper presents a collaboration support system, REGALMINER, that is able to capture, process, monitor and also visualize metadata from collaboration data streams taking advantage of text mining and information retrieval techniques like sentiment analysis (a.k.a. opinion mining) and keyword extraction. The analysis produces a set of scores that represent various meeting indicators that can be used to monitor and evaluate the dynamics of an ongoing collaborative process and to provide automatic interventions to enhance its effectiveness and efficiency. Information visualization techniques are used to present the results of the analysis to the participants of the current collaborative process or to the meeting coordinator, who supervises the meeting at runtime preventing the occurrence of deviations with respect to the meeting agenda and to make necessary interventions.
Prenatal and postnatal transfer of perfluoroalkyl substances from mothers to their offspring

Abstract Perfluoroalkyl and polyfluoroalkyl substances (PFASs) are anthropogenic substances of increasing concerns. Their widespread uses and strong persistence in the environment have led to inevitable exposure for humans. They accumulate in mothers and then are transferred to infants through placenta and breastfeeding, causing diverse potential health risks. Based on more than 100 articles published from 2000 to date, this review summarizes current knowledge on prenatal and postnatal transfer of PFASs from mothers to fetuses/infants. Transplacental transfer efficiencies (RCM) differ among individual PFASs, depending on the alkyl chain length, the function groups, and the branching position in the molecule, and showing enantioselectivity for chiral 1 m-PFOS. Transfer efficiency from serum to breast milk (TEBS/MS) is lower than RCM, but PFAS exposure of infants through breastfeeding in the first month was assessed to be greater than that through transplacental transfer during the entire gestation period. Based on the latest promulgated reference doses, infants would face potential health risks. To our knowledge, this is the first review on the prenatal and postnatal mother-to-offspring transfer of PFASs at congeneric, isomeric, and enantiomeric levels. It provides a better understanding of the critical environmental health issue of PFASs in fetuses and infants, which deserves greater attention throughout society. Graphical abstract
In “defense” of Podarcis latastei, an Italian insular endemic species (Squamata: Lacertidae)

Based on genetic and morphological evidence, Senczuk et al. (2019) formally raised the Podarcis populations from the Western Pontine Islands, previously classified as several subspecies of P. siculus, to species rank, i.e. Podarcis latastei (Bedriaga, 1879). This taxonomic change was not accepted in the checklist of the European herpetofauna by Speybroeck et al. (2020), recently published on Amphibia-Reptilia. In this note we respond to the reasons given by Speybroeck and colleagues and support the validity of Podarcis latastei as an endemic Italian species.
A Minimum Error Probability NOMA Design

Non-orthogonal multiple access (NOMA) enables massive connectivity and achieves high spectral efficiency. The vast majority of the NOMA literature has adopted the ideal information rate as performance metric assuming perfect successive interference cancellation (SIC) without any error propagation, which, however, may lead to NOMA designs adverse to SIC. In this paper, we take into account imperfect SIC and practical modulation schemes for power-domain NOMA design. To characterize the error propagation, we derive the bit error rates (BERs) of the users for arbitrary-order quadrature amplitude modulation (QAM) schemes. Then, we propose a minimum error probability NOMA (MEP-NOMA) design, minimizing the average BER of the users via power allocation. Considering the complicated error probability expressions of the MEP-NOMA design, we derive lower and upper bounds on the average BER, based on which a simple closed-form power allocation is obtained. We show that the proposed power allocation minimizes both the lower and upper bounds on the average BER for a sufficiently large power budget and provides near-optimal error performance. On this basis, we theoretically prove the superiority of MEP-NOMA over existing OMA and NOMA schemes in terms of error performance. Comprehensive numerical results are provided to verify the accuracy of the error probability analysis of the considered practical NOMA scheme with imperfect SIC and to demonstrate the efficacy of the proposed MEP-NOMA design.
Dependence-Cognizant Locking Improvement for the Main Memory Database Systems

The traditional lock manager (LM) seriously limits the transaction throughput of the main memory database systems (MMDB). In this paper, we introduce dependence-cognizant locking (DCLP), an efficient improvement to the traditional LM, which dramatically reduces the locking space while offering efficiency. With DCLP, one transaction and its direct successors are collocated in its context. Whenever a transaction is committed, it wakes up its direct successors immediately avoiding the expensive operations, such as lock detection and latch contention. We also propose virtual transaction which has better time and space complexity by compressing continuous read-only transactions/operations. We implement DCLP in Calvin and carry out experiments in both multicore and shared-nothing distributed databases. Experiments demonstrate that, in contrast with existing algorithms, DCLP can achieve better performance in many workloads, especially high-contention workloads.