Miracle-dz/UniFAR-FTUs huggingface dataset:
Distribution, ecology and status of an endemic shrew, Crocidura thomensis, from São Tomé

The São Tomé white-toothed shrew Crocidura thomensis is endemic to the island of São Tomé in the Gulf of Guinea. This species was discovered in 1886 and since then has been recorded from fewer than 10 locations. This paper summarizes all published and unpublished information on C. thomensis. The species is currently listed by the IUCN as ‘Insufficiently Known’, but using the new IUCN Red List Categories is re-classified as ‘Vulnerable B1 + 2c’. Threats to the survival of C. thomensis include deforestation, plantation redevelopment and predation by introduced mammals.
Modélisation des processus d’acquisition syntaxique par jeux de langage entre agents artificiels (Modeling Syntactic Acquisition by Language Games between Artificial Agents )

Dans cet article, nous présentons une modélisation de la situation d’acquisition de la syntaxe de sa langue maternelle par un enfant inspirée des “jeux de langages” de Luc Steels. Le modèle suppose que l’enfant a accès à une représentation sémantique des énoncés qui lui sont adressés, et qu’il doit réagir en désignant la tête syntaxique de ces énoncés. Nous décrivons des expériences exploitant des données du corpus CHILDES et mettant en jeu un processus d’acquisition simple mais efficace.
Local structure of DNA toroids reveals curvature-dependent intermolecular forces

In viruses and cells, DNA is closely packed and tightly curved thanks to polyvalent cations inducing an effective attraction between its negatively charged filaments. Our understanding of this effective attraction remains very incomplete, partly because experimental data is limited to bulk measurements on large samples of mostly uncurved DNA helices. Here we use cryo electron microscopy to shed light on the interaction between highly curved helices. We find that the spacing between DNA helices in spermine-induced DNA toroidal condensates depends on their location within the torus, consistent with a mathematical model based on the competition between electrostatic interactions and the bending rigidity of DNA. We use our model to infer the characteristics of the interaction potential, and find that its equilibrium spacing strongly depends on the curvature of the filaments. In addition, the interaction is much softer than previously reported in bulk samples using different salt conditions. Beyond viruses and cells, our characterization of the interactions governing DNA-based dense structures could help develop robust designs in DNA nanotechnologies.
DUKUNGAN KELUARGA DAN HUBUNGANNYA DALAM PROSES PENYEMBUHAN LUKA DIABETES MELLITUS GRADE I-III DI RSUD WATES KULON PROGO

Diabetes mellitus (DM) merupakan penyakit metabolik yang ditandai dengan peningkatan kadar gula darah. Penyakit DM dapat mengakibatkan komplikasi jangka panjang berupa luka diabetik yang sulit disembuhkan. Beberapa faktor yang memperburuk kondisi luka diantaranya adalah masalah psikologis yang membutuhkan dukungan dari orang terdekat. Dukungan keluarga sebagai salah satu bagian dari dukungan sosial yang merupakan bentuk interaksi antar individu yang memberikan rasa nyaman secara fisik dan psikologi. Tujuan Penelitian ini adalah untuk mengetahui hubungan dukungan keluarga dengan proses penyembuhan luka DM grade I-III. Metode penelitian ini menggunakan metode analitik observasional melalui pendekatan studi cohort (prospektif). Dengan jumlah sampel sebanyak 30 orang yang mencakup pasien rawat inap, rawat jalan, dan home care. Analisis data menggunakan uji korelasi spearman untuk menilai suatu hubungan antar variabel. Hasil Penelitian diperoleh dukungan keluarga yang kurang baik (56,7%), kondisi luka grade III (83,3%), dan kategori regenerasi (90,0%). Terdapat hubungan dukungan keluarga dengan proses penyembuhan luka DM grade I-III di RSUD Wates Kulon Progo (ρ =0,028 < α =0,05). Kesimpulan : dukungan keluarga merupakan faktor penting dalam proses penyembuhan Luka DM.
The Face Module Emerged in a Deep Convolutional Neural Network Selectively Deprived of Face Experience

Can we recognize faces with zero experience on faces? This question is critical because it examines the role of experiences in the formation of domain-specific modules in the brain. Investigation with humans and non-human animals on this issue cannot easily dissociate the effect of the visual experience from that of the hardwired domain-specificity. Therefore the present study built a model of selective deprivation of the experience on faces with a representative deep convolutional neural network, AlexNet, by removing all images containing faces from its training stimuli. This model did not show significant deficits in face categorization and discrimination, and face-selective modules automatically emerged. However, the deprivation reduced the domain-specificity of the face module. In sum, our study provides undisputable evidence on the role of nature versus nurture in developing the domain-specific modules that domain-specificity may evolve from non-specific experience without genetic predisposition, and is further fine-tuned by domain-specific experience.
Mediator Med23 Regulates Adult Hippocampal Neurogenesis

Mammalian Mediator (Med) is a key regulator of gene expression by linking transcription factors to RNA polymerase II (Pol II) transcription machineries. The Mediator subunit 23 (Med23) is a member of the conserved Med protein complex and plays essential roles in diverse biological processes including adipogenesis, carcinogenesis, osteoblast differentiation, and T-cell activation. However, its potential functions in the nervous system remain unknown. We report here that Med23 is required for adult hippocampal neurogenesis in mouse. Deletion of Med23 in adult hippocampal neural stem cells (NSCs) was achieved in Nestin-CreER:Med23flox/flox mice by oral administration of tamoxifen. We found an increased number of proliferating NSCs shown by pulse BrdU-labeling and immunostaining of MCM2 and Ki67, which is possibly due to a reduction in cell cycle length, with unchanged GFAP+/Sox2+ NSCs and Tbr2+ progenitors. On the other hand, neuroblasts and immature neurons indicated by NeuroD and DCX were decreased in number in the dentate gyrus (DG) of Med23-deficient mice. In addition, these mice also displayed defective dendritic morphogenesis, as well as a deficiency in spatial and contextual fear memory. Gene ontology (GO) analysis of hippocampal NSCs revealed an enrichment in genes involved in cell proliferation, Pol II-associated transcription, Notch signaling pathway and apoptosis. These results demonstrate that Med23 plays roles in regulating adult brain neurogenesis and functions.
An Attempt at a Unified Theory of the Neocortical Microcircuit in Sensory Cortex

The neocortex performs a wide range of functions, including working memory, sensory perception, and motor planning. Despite this diversity in function, evidence suggests that the neocortex is made up of repeating subunits (“macrocolumns”), each of which is largely identical in circuitry. As such, the specific computations performed by these macrocolumns are of great interest to neuroscientists and AI researchers. Leading theories of this microcircuit include models of predictive coding, hierarchical temporal memory (HTM), and Adaptive Resonance Theory (ART). However, these models have not yet explained: (1) how microcircuits learn sequences input with delay (i.e., working memory); (2) how networks of columns coordinate processing on precise timescales; or (3) how top-down attention modulates sensory processing. I provide a theory of the neocortical microcircuit that extends prior models in all three ways. Additionally, this theory provides a novel working memory circuit that extends prior models to support simultaneous multi-item storage without disrupting ongoing sensory processing. I then use this theory to explain the functional origin of a diverse set of experimental findings, such as cortical oscillations.
It's Time to Revisit LRU vs. FIFO

We revisit the question of the effectiveness of the popular LRU cache eviction policy versus the FIFO heuristic which attempts to give an LRU like behavior. Several past works have considered this question and commonly stipulated that while FIFO is much easier to implement, the improved hit ratio of LRU outweighs this. We claim that two main trends call for a reevaluation: new caches such as front-ends to cloud storage have very large scales and this makes managing cache metadata in RAM no longer feasible; and new workloads have emerged that possess different characteristics. We model the overall cost of running LRU and FIFO in a very large scale cache and evaluate this cost using a number of publicly available traces. Our main evaluation workload is a new set of traces that we collected from a large public cloud object storage service and on this new trace FIFO exhibits better overall cost than LRU. We hope that these observations reignite the evaluation of cache eviction policies under new circumstances and that the new traces, that we intend to make public, serve as a testing ground for such work.
Understanding science communication in human genetics using text mining

We conducted the first systematic text mining review of online media coverage of genome-wide association studies (GWAS) and analyzed trends in media coverage, readability, themes, and mentions of ethical, legal, and social issues (ELSI). Over 5,000 online news articles published from 2005 to 2018 all over the world were included in analyses. Our results show that while some GWAS attract a great deal of online interest many are not reported on, and that those that are covered are described in language too complex to be understood by the general public. Ethical issues are largely unaddressed, while suggestions for translation are increasing over time. Our review identifies areas that need to improve to increase the effectiveness and accuracy of the communication of genetic research findings in online media. We have also developed a website where all results described below can be explored interactively: https://jjmorosoli.shinyapps. io/newas/.
Computer vision approach to characterize size and shape phenotypes of horticultural crops using high-throughput imagery

For many horticultural crops, variation in quality (e.g., shape and size) contribute significantly to the crop’s market value. Metrics characterizing less subjective harvest quantities (e.g., yield and total biomass) are routinely monitored. In contrast, metrics quantifying more subjective crop quality characteristics such as ideal size and shape remain difficult to characterize objectively at the production-scale due to the lack of modular technologies for high-throughput sensing and computation. Several horticultural crops are sent to packing facilities after having been harvested, where they are sorted into boxes and containers using high-throughput scanners. These scanners capture images of each fruit or vegetable being sorted and packed, but the images are typically used solely for sorting purposes and promptly discarded. With further analysis, these images could offer unparalleled insight on how crop quality metrics vary at the industrial production-scale and provide further insight into how these characteristics translate to overall market value. At present, methods for extracting and quantifying quality characteristics of crops using images generated by existing industrial infrastructure have not been developed. Furthermore, prior studies that investigated horticultural crop quality metrics, specifically of size and shape, used a limited number of samples, did not incorporate deformed or non-marketable samples, and did not use images captured from high-throughput systems. In this work, using sweetpotato (SP) as a use case, we introduce a computer vision algorithm for quantifying shape and size characteristics in a high-throughput manner. This approach generates 3D model of SPs from two 2D images captured by an industrial sorter 90 degrees apart and extracts 3D shape features in a few hundred milliseconds. We applied the 3D reconstruction and feature extraction method to thousands of image samples to demonstrate how variations in shape features across sweetptoato cultivars can be quantified. We created a sweetpotato shape dataset containing sweetpotato images, extracted shape features, and qualitative shape types (U.S. No. 1 or Cull). We used this dataset to develop a neural network-based shape classifier that was able to predict Cull vs. U.S. No. 1 sweetpotato with 84.59% accuracy. In addition, using univariate Chi-squared tests and random forest, we identified the most important features for determining qualitative shape (U.S. No. 1 or Cull) of the sweetpotatoes. Our study serves as the first step towards enabling big data analytics for sweetpotato agriculture. The methodological framework is readily transferable to other horticultural crops, particularly those that are sorted using commercial imaging equipment.
Plant traits predict impact of invading species: an analysis of herbaceous vegetation in the subtropics

The need to predict potential invasion impact of plant species is important for setting weed-management priorities and determining quarantine restrictions for newly imported plant material. We analysed the naturalised plant component of a herbaceous plant community in sub-tropical eucalypt woodlands subjected to various disturbances associated with agricultural activities. The native and naturalised plant species did not differ in the proportions of different life forms, although life-history differed, with the naturalised group having more annual and biennial, and relatively fewer perennial species. We classified the naturalised assemblage into high-and low-impact species and compared the plant-trait and habitat characteristics of the two groups. Low-impact species covered a range of levels of habitat specialisation whereas high-impact species tended to have moderate to low levels of specialisation and to be less tolerant of grazing. Seven traits were found to be significantly associated with impact. Stepwise regression indicated a high level of redundancy in the data, owing to attributes being correlated. For all species, four attributes were significant in determining impact: very wide lateral spread, C4 photosynthesis, tall height and large leaves. For forbs, only two attributes (large seeds, adhesion/ingestion mode of seed dispersal) were significant in the overall model. We identified the following eight functional types amongst the naturalised species: (i) high-impact C4 lawn grasses, (ii) high-impact C4 bulky tussock grasses, (iii) moderate-impact annual grasses, (iv) moderate-impact tall annual forbs, (v) moderate-impact spreading forbs, (vi) moderate-impact woody forbs, (vii) low-impact legumes and (viii) low-impact small ruderals. In the subtropical woodland environment perennial C4 grasses appear to present the greatest invasive threat to herbaceous native communities, whereas forbs of wide lateral spread, with large animal-dispersed seeds are also problematic. The results support a case for limiting further importation of horticultural and forage material into Australia.
Integrating Animal Husbandry With Crops and Trees

Per capita intake of animal protein is expected to increase globally through 2050, and the rate of increase will be more in developing or emerging economies than in developed countries. Global meat consumption between 1980 and 2050 is projected to increase from 133 million to 452 million tons, and 86% (279 million tons) of the increase will occur in developing countries. Animal-based agricultural systems occupy 45% of the global land area and contribute a large proportion of agricultural emissions. In addition to being a major source of nitrous oxide (N2O), methane (CH4), and other greenhouse gases (GHGs), livestock also use 8% of the global water withdrawal. The animal sector is dominated by resource-poor and small landholders of developing countries. Adverse effects of livestock on the environment are caused by the way animal husbandry is practiced, in no small part because animals are not integrated with other agricultural and forestry-based practices. Thus, improving and sustaining the livestock sector is critical to advancing the Sustainable Development Goals (SDGs) of the United Nations, especially SDG #1 (No Poverty), SDG #2 (Zero Hunger), SDG #6 (Clean Water and Sanitation), and SDG #13 (Climate Action). Separating raising of livestock from cultivating seasonal crops and perennial trees has decoupled the biogeochemical/biogeophysical cycling of carbon (C), water (H2O), nitrogen (N), phosphorus (P), and sulfur (S). This decoupling is a causative factor of the increase in emissions of N2O and CH4, eutrophication and contamination of water resources, degradation of rangelands, and decline in its biodiversity. Therefore, identifying and adopting systems that integrate livestock with crops and trees are critical for reducing the environmental footprint of animal-based dietary products. Incorporating pastures/forages in the rotation cycle along with controlled grazing, called ley farming, and agroforestry, such as alley cropping, are examples of integrated farming systems. Other strategies of reducing the environmental footprint comprise the following: reducing enteric fermentation by precision feeding and matching dietary protein to animal need, processing CH4 and N2O emissions for other uses, and managing manure and other animal waste prudently. Other important considerations are adopting multiple GHG perspectives and minimizing gas swapping, reducing wastage of animal products, decreasing the use of antibiotics, and restoring rangeland for sequestration of atmospheric CO2 as soil organic matter.
Ultra-Low Latency SSDs' Impact on Overall Energy Efficiency

Recent technological advancements have enabled a generation of Ultra-Low Latency (ULL) SSDs that blurs the performance gap between primary and secondary storage devices. However, their power consumption characteristics are largely unknown. In addition, ULL performance in a block device is expected to put extra pressure on operating system components, signiﬁcantly affecting energy efﬁciency of the entire system. In this work, we empirically study overall energy efﬁciency using a real ULL storage device, Optane SSD , a power meter, and a wide range of IO workload behaviors. We present a comparative analysis by laying out several critical observations related to idle vs. active behavior, read vs. write behavior, energy proportionality, impact on system software, as well as impact on overall energy efﬁciency. To the best of our knowledge, this is the ﬁrst published study of a ULL SSD’s impact on the system’s overall power consumption, which can hopefully lead to future energy-efﬁcient designs.
PracExtractor: Extracting Configuration Good Practices from Manuals to Detect Server Misconfigurations

Conﬁguration has become ever so complex and error-prone in today’s server software. To mitigate this problem, software vendors provide user manuals to guide system admins on conﬁguring their systems. Usually, manuals describe not only the meaning of conﬁguration parameters but also good practice recommendations on how to conﬁgure certain parameters. Unfortunately, manuals usually also have a large number of pages, which are time-consuming for humans to read and understand. Therefore, system admins often do not refer to manuals but rely on their own guesswork or unreliable sources when setting up systems, which can lead to conﬁguration errors and system failures. To understand the characteristics of conﬁguration recommendations in user manuals, this paper ﬁrst collected and studied 261 recommendations from the manuals of six large open-source systems. Our study shows that 60% of the studied recommendations describe speciﬁc and checkable speciﬁca-tions instead of merely general guidance. Moreover, almost all (97%) of such speciﬁcations have not been checked in the systems’ source code, and 61% of them are not equivalent to the default settings. This implies that additional checking is needed to ensure the recommendations are correctly applied. Based on our characteristic study, we build a tool called PracExtractor, which employs Natural Language Processing (NLP) techniques to automatically extract conﬁguration recommendations from software manuals, converts them into speciﬁcations, and then uses the generated speciﬁcations to detect violations in system admins’ conﬁguration settings. We evaluate PracExtractor with twelve widely-deployed software systems, including one large commercial system from a public company. In total, PracExtractor automatically extracts 338 recommendations and generates
Multiplex PCR Assays for the Detection of One Hundred and Thirty Seven Serogroups of Shiga Toxin-Producing Escherichia coli Associated With Cattle

Escherichia coli carrying prophage with genes that encode for Shiga toxins are categorized as Shiga toxin-producing E. coli (STEC) pathotype. Illnesses caused by STEC in humans, which are often foodborne, range from mild to bloody diarrhea with life-threatening complications of renal failure and hemolytic uremic syndrome and even death, particularly in children. As many as 158 of the total 187 serogroups of E. coli are known to carry Shiga toxin genes, which makes STEC a major pathotype of E. coli. Seven STEC serogroups, called top-7, which include O26, O45, O103, O111, O121, O145, and O157, are responsible for the majority of the STEC-associated human illnesses. The STEC serogroups, other than the top-7, called “non-top-7” have also been associated with human illnesses, more often as sporadic infections. Ruminants, particularly cattle, are principal reservoirs of STEC and harbor the organisms in the hindgut and shed in the feces, which serves as a major source of food and water contaminations. A number of studies have reported on the fecal prevalence of top-7 STEC in cattle feces. However, there is paucity of data on the prevalence of non-top-7 STEC serogroups in cattle feces, generally because of lack of validated detection methods. The objective of our study was to develop and validate 14 sets of multiplex PCR (mPCR) assays targeting serogroup-specific genes to detect 137 non-top-7 STEC serogroups previously reported to be present in cattle feces. Each assay included 7–12 serogroups and primers were designed to amplify the target genes with distinct amplicon sizes for each serogroup that can be readily identified within each assay. The assays were validated with 460 strains of known serogroups. The multiplex PCR assays designed in our study can be readily adapted by most laboratories for rapid identification of strains belonging to the non-top-7 STEC serogroups associated with cattle.