Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatiotemporal Dynamics of Vibrio Communities and Abundance in Dongshan Bay, South of China

The Vibrio genus inhabit estuarine and marine ecosystem throughout the world and can cause severe infections in humans and animals. Previous studies have demonstrated the dynamics of Vibrio at both community and population levels and assessed the close relationship between environmental factors and Vibrio diversity and abundance, such as temperature, salinity, and dissolved oxygen. It is also generally believed that aquaculture is the fastest-growing food sector, which is also applying great environmental impacts on microbial communities in aquatic ecosystems. However, our understanding of the spatiotemporal quantification of Vibrio throughout the four seasons in the aquaculture zone and response to environmental factors remains poor. To explore the spatiotemporal distribution and abundance of the Vibrio community with their related environmental factors and detect the relationships among them, we collected 10 seawater sites spanning four seasons across the whole year in Dongshan Bay for investigating the Vibrio community dynamics. Marked differences in diversity and abundance of the Vibrio community were observed between seasons, which were mainly driven by temperature, dissolved oxygen, nitrate, and nitrite. qPCR analysis showed that Vibrio abundance was most abundant in the summer (5.37 × 106 copies/L), compared with the autumn (4.58 × 106 copies/L), spring (1.18 × 106 copies/L), and winter (1.55 × 104 copies/L). A total of 22 Vibrio operational taxonomic units (OTUs) and 28 species were identified by universal bacteria 16S rRNA gene and cultivation methods, with Vibrio fortis the dominant in these aquaculture areas. To summarize, our present study is one of the few studies to research the occurrence of Vibrio in marine aquaculture of South China, and the results indicate that Vibrio are widely distributed in aquaculture environment and that a further risk assessment is needed to be conducted.
Climate Conditions on the Tibetan Plateau During the Last Glacial Maximum and Implications for the Survival of Paleolithic Foragers

Environmental conditions on the Tibetan Plateau (TP) during the last glacial maximum (LGM) are poorly known. Existing studies of environmental proxies and climate model simulations are contradictory, with interpretations varying between cold-dry and cold-wet environmental conditions which differentially influenced lake volumes, loess deposition and vegetation communities across the TP. Genetic and archaeological studies suggest anatomically modern paleolithic foragers initially occupied the TP between 60 and 30 ka, and may have seasonally occupied the TP during the LGM. Hence, a better understanding for LGM environmental conditions is needed in order to estimate whether paleolithic foragers could have survived on the TP during the extreme LGM cold stage. Here we report the investigation of lacustrine sediments and beach deposits within two paleoshorelines around Dagze Co on the southern TP, ∼22 and ∼42 m higher than the present lake level. Optical age estimates suggest the sediments were deposited during the LGM and mid-Holocene, respectively. TraCE-21 climate model simulation results suggest that net annual LGM precipitation in the Dagze Co basin was lower than the mid-Holocene, but about the same as that of the past 1,000 years. Combining the optical age estimates with TraCE-21 and CAM4 climate model simulation results, we deduce that increased summer precipitation and glacier meltwater supply, combined with decreased lake surface evaporation, produced LGM lake levels ∼22 m higher than present. We also synthesized paleoenvironmental records reported across the TP spanning the LGM. This synthesis suggests that the LGM climate in the northern TP was cold and dry, but that some of the southern TP was cold and wet. These relatively wetter LGM conditions in the southern TP may have favored the growth of cold-resistant plants which, in turn, may have supported larger herbivore populations, and provided food for paleolithic foragers. We conclude that seasonal or short-term human occupation of the TP during the LGM was thus more likely in the southern TP than in the north.
A Linguistic-Based Method that Combines Polarity, Emotion and Grammatical Characteristics to Detect Fake News in Portuguese

In the last decades, the dissemination of News through digital media has increased the information accessibility previously offered by traditional channels. Despite their benefits, digital media have exacerbated an old problem: the spread of Fake News, (i.e., false News intentionally published). Faced with this scenario, the linguistic approaches to automatic Fake News detection use information that can be directly extracted from the News' text. Several methods based on these approaches use grammatical classification and sentiment analysis over News writing in Portuguese. However, as far as it was possible to observe in the related literature, these methods are limited to the identification of polarity of sentiment (i.e., positive, neutral or negative) existing in the text. Although polarity classification be an effective method for a wide range of natural language processing applications, it does not address language nuances (e.g., emotions such as anger, sadness, etc.) that can provide evidence that a text contains false information. Hence, this study proposes an extended method that, in addition to the grammatical classification and polarity based sentiment analysis, also uses the analysis of emotions to detect Fake News written in Portuguese. The extended method showed promising results in experimental data, obtaining accuracy greater than 92%. In average, the proposed method overcame polarity and gramatical classification based methods in 1.4 percentage points.
Standardized Testing, Use of Assessment Data, and Low Reading Performance of Immigrant and Non-immigrant Students in OECD Countries

This paper investigates the effects of standardized testing and publication of achievement data on low reading performance for immigrant and non-immigrant students in 30 OECD countries. The paper aims to test hypotheses derived from a principal-agent framework. According to this theoretical perspective, standardized assessments alone should not be associated with reading performance. Instead, the model proposes that the provision of the results to the principle (parents and education authorities) is associated with higher student performance, as this reduces the information asymmetry between principal (parents and educational authorities) and agent (teachers and schools). The results of our analyses of PISA 2009 and 2015 reading data from 422.172 students show that first, the use of standardized achievement tests alone was not associated with the risk of low performance. Second, making the results of standardized tests available to the public was associated with a decreased risk of low reading performance among all students, and, third, particularly among first generation immigrant students. These results were robust across various modeling approaches. In accordance with the predictions from the principal-agent framework, our findings suggest that the mere implementation of standardized assessments has no effects on low performance. Testing along with the public provision of the testing results, which decreases the information asymmetry between schools and teachers on the one hand and parents and education authorities on the other, was associated with a decreased risk of low performance, with the effect being stronger for immigrant students.
Using Synthesized Data to Train Deep Neural Net with Few Data

As Computer-Assisted Surgery (CAS) getting popular, more and more research has been conducted to help surgeons operate. We aim at the semantic segmentation in the endoscopy surgery scenario because semantic segmentation is the first step for a computer to grasp what shows up in the vision of an endoscope. However, modern Deep Learning algorithms need myriads of training data. Since data of the endoscopy surgery scene is relatively scarce, the performance of existing algorithms is thus rather limited. Therefore, we tried to solve the problem of training a semantic segmentation network with few data in this work. We propose a proof-of-concept system offering the ability to enlarge the dataset and improve the performance. The system aims to synthesize a pair of training data in a single pass and provides a sufficient amount of data to train a network. We evaluated our method using the dataset provided by MICCAI 2018 Robotic Scene Segmentation Sub-Challenge. Our method yielded 11.79% mIoU improvement in recognizing anatomical objects and 2.2% mIoU in recognizing surgical instruments. Recognizing anatomical objects accurately would definitely benefit CAS. Preliminary results suggest our method helps the classifier become more robust and accurate even if not having large amount of data.
Developmental Genes and Malformations in the Hypothalamus

The hypothalamus is a heterogeneous rostral forebrain region that regulates physiological processes essential for survival, energy metabolism, and reproduction, mainly mediated by the pituitary gland. In the updated prosomeric model, the hypothalamus represents the rostralmost forebrain, composed of two segmental regions (terminal and peduncular hypothalamus), which extend respectively into the non-evaginated preoptic telencephalon and the evaginated pallio-subpallial telencephalon. Complex genetic cascades of transcription factors and signaling molecules rule their development. Alterations of some of these molecular mechanisms acting during forebrain development are associated with more or less severe hypothalamic and pituitary dysfunctions, which may be associated with brain malformations such as holoprosencephaly or septo-optic dysplasia. Studies on transgenic mice with mutated genes encoding critical transcription factors implicated in hypothalamic-pituitary development are contributing to understanding the high clinical complexity of these pathologies. In this review article, we will analyze first the complex molecular genoarchitecture of the hypothalamus resulting from the activity of previous morphogenetic signaling centers and secondly some malformations related to alterations in genes implicated in the development of the hypothalamus.
First Case Report on Quantification of Antimicrobial Use in Corporate Dairy Farms in Pakistan

Intensive livestock farming has become indispensable to meet the rapidly increasing demand for animal-based nutrition in low- and middle-income countries (LMICs) where antimicrobials are frequently used for treatment and prophylactic or metaphylactic purposes. However, very little is known about the trends of antimicrobial use (AMU) in dairy animals in LMICs. The objective of this study was to quantify AMU in two large commercial dairy farms in Pakistan. A retrospective study was conducted at two large corporate commercial dairy farms located in Punjab province for the year 2018. AMU was calculated using three metrics: active ingredient (AI; kg) and milligrams per population unit (mg/PU; mg/kg), which quantifies the amount of AI used, and antimicrobial treatment incidence (ATI; DDDA/1,000 cow-days), which estimates the per-day number of treatments to 1,000 cows. Total on-farm AMU was found to be 138.34 kg, 65.88 mg/kg, and 47.71 DDDA/1,000 cow-days. Measured in ATI, aminoglycosides (11.05 DDDA/1,000 cow-days), penicillins (8.29 DDDA/1,000 cow-days), and tetracyclines (8.1 DDDA/1,000 cow-days) were the most frequently used antimicrobial classes. A total of 42.46% of all the antimicrobials used belonged to the critically important antimicrobials for human medicine as defined by the World Health Organization. Considerably high AMU was found compared to other farm-level studies across the world. This was the first study to quantify AMU in the dairy industry in Pakistan. Our results showed that corporate commercial dairy management practices are associated with increased antimicrobial consumption and highlight the need for antimicrobial stewardship programs to encourage prudent use of antimicrobials in commercial dairy.
Adverse Childhood Experiences: The Protective and Therapeutic Potential of Nature

Adverse childhood experiences (ACEs) are prevalent in many western populations. Large studies have put the likelihood of having at least one ACE above 50% of the general population. ACEs and the associated experience of chronic stress, moreover, have been consistently linked with a variety of negative physical and psychological health outcomes across the lifespan from behavioral problems and cognitive difficulties early on, to greater chance of suffering from a mental health disorder and engaging in self destructing behaviors. The literature puts forward several protective factors, such as mother-child relations, parental health, and community engagement. In this perspective paper we put forward the potential of regular nature engagement as a possible additional protective factor. Nature’s therapeutic potential has been well documented, for many psychopathologies and mental health difficulties. Yet studies looking at the protective and therapeutic potential of nature with people with ACEs are remarkably limited in numbers. In this perspective piece we conduct a search of the literature to find previous applications of nature as a protective or therapeutic intervention for people with ACEs. We highlight the gap in the current literature, and put forward various mechanisms of action that justify a closer exploration of this area in further research.
Impact of Lower Limb Active Movement Training in Individuals With Spastic Type Cerebral Palsy on Neuromuscular Control Outcomes: A Systematic Review

Background: Cerebral Palsy (CP) is a non-progressive neurological condition that results in motor impairment which increases proximally to distally along the lower extremity (i.e., greatest impairment at the ankle). Consequently, motor impairment and reduced voluntary muscle activation results in reduced neuromuscular control of the lower limb in this population. CP rehabilitation traditionally aims to improve movement proficiency for functional activities, such as walking, by using a range of active movement modalities that require volitional effort; however, the underlying neural mechanisms of improved control and function remain unknown. The primary purpose of this study was to systematically determine the efficacy of lower limb active movement interventions to improve neuromuscular control in individuals with CP. Methodology: A search for studies involving an active lower limb intervention and neurophysiological outcome measures in individuals with CP was performed in five electronic databases. Studies were assessed for methodological quality using the Downs and Black assessment tool. Results: Nine of 6,263 articles met the inclusion criteria. Methodological quality of all studies was poor, ranging from 2 to 27 out of a possible score of 32 points on the Downs and Black assessment tool. The study interventions varied extensively in modality and prescription as well as in the outcome measures used. Conclusions: Whether active movement improves neuromuscular control of the lower limb in CP is unclear due to high variability in intervention protocols and selected outcomes measures. Future active intervention studies must carefully consider the selection of neurophysiological outcome measures.
Vehicle Connectivity and Automation: A Sibling Relationship

The evolution of scientific advances has often been characterized by the amalgamation of two or more technologies. With respect to vehicle connectivity and automation, recent literature suggests that these two emerging transportation technologies can and will jointly and profoundly shape the future of transportation. However, it is not certain how the individual and synergistic benefits to be earned from these technologies is related to their prevailing levels of development. As such, it may be considered useful to revisit the primary concepts of automation and connectivity, and to identify any current and expected future synergies between them. Doing this can help generate knowledge that could be used to justify investments related to transportation systems connectivity and automation. In this discussion paper, we attempt to address some of these issues. The paper first reviews the technological concepts of systems automation and systems connectivity, and how they prospectively, from an individual and collective perspective, impact road transportation efficiency and safety. The paper also discusses the separate and common benefits of connectivity and automation, and their possible holistic effects in terms of these benefits where they overlap. The paper suggests that at the current time, the sibling relationship seems to be lopsided: vehicle connectivity has immense potential to enhance vehicle automation. Automation, on the other hand, may not significantly promote vehicle connectivity directly, at least not in the short term but possibly in the long term. The paper argues that future trends regarding market adoption of these two technologies and their relative pace of advancement or regulation, will shape the future synergies between them.
Using Word Embeddings to Learn a Better Food Ontology

Food ontologies require significant effort to create and maintain as they involve manual and time-consuming tasks, often with limited alignment to the underlying food science knowledge. We propose a semi-supervised framework for the automated ontology population from an existing ontology scaffold by using word embeddings. Having applied this on the domain of food and subsequent evaluation against an expert-curated ontology, FoodOn, we observe that the food word embeddings capture the latent relationships and characteristics of foods. The resulting ontology, which utilizes word embeddings trained from the Wikipedia corpus, has an improvement of 89.7% in precision when compared to the expert-curated ontology FoodOn (0.34 vs. 0.18, respectively, p value = 2.6 × 10–138), and it has a 43.6% shorter path distance (hops) between predicted and actual food instances (2.91 vs. 5.16, respectively, p value = 4.7 × 10–84) when compared to other methods. This work demonstrates how high-dimensional representations of food can be used to populate ontologies and paves the way for learning ontologies that integrate contextual information from a variety of sources and types.
Next best view planning with an unstructured representation

High-quality observations of the real world are crucial for creating realistic scene imitations and performing structural analysis. Observations can be used to produce 3D printed replicas of small-scale scenes (e.g., a toy bunny), conduct inspections of largescale infrastructure (e.g., a building) or integrated into virtual environments that provide immersive experiences for our entertainment and training robotic systems. Scenes are observed by obtaining point measurements using a sensor from multiple views. These views can be chosen by a human operator or planned using knowledge of existing measurements or an a priori scene model. The challenge of selecting the ‘next’ view of a scene to obtain that will provide the ‘best’ improvement in an observation is known as the Next Best View (NBV) planning problem. This thesis presents work on NBV planning with a novel unstructured scene representation. In contrast to existing literature on the problem, which typically uses structured representations, an unstructured representation does not impose an external structure on scene observations. There is no reduction in the fidelity of information represented or simplifying assumptions made about the scene structure. This unstructured representation is used to create the Surface Edge Explorer (SEE), a novel NBV planning approach. Observed points are classified based on the local measurement density. Views are chosen to improve the surface coverage of an observation until a minimum point density has been attained. Experiments comparing SEE with structured approaches demonstrate that it is able to obtain an equivalent observation quality using fewer views and a lower computation time. Novel point-based techniques for considering occlusions and scene visibility are investigated. This work overcomes the raycasting constraints of existing methods used by structured approaches. The best performing strategies for addressing each of these challenges are integrated with SEE to create SEE++. An experimental comparison of SEE++ with SEE and structured approaches demonstrates that it achieves significant improvements in observation performance by requiring fewer views and shorter travel distances while maintaining a reasonable computation time. Observations of real world scenes using SEE and SEE++ illustrate the successful transference of their capabilities from a simulation environment to the real world. Qualitative results show that both approaches are able to obtain highly complete observations of several scenes with varying size and structural complexity using multiple sensor modalities. Quantitative results demonstrate that SEE++ observes the scenes with greater efficiency than SEE by utilising an increased computational time.
From Basic Biology to Patient Mutational Spectra of GATA2 Haploinsufficiencies: What Are the Mechanisms, Hurdles, and Prospects of Genome Editing for Treatment

Inherited bone marrow failure syndromes (IBMFS) are monogenetic disorders that result in a reduction of mature blood cell formation and predisposition to leukemia. In children with myeloid leukemia the gene most often mutated is Gata binding protein 2 (GATA2) and 80% of patients with GATA2 mutations develop myeloid malignancy before the age of forty. Although GATA2 is established as one of the key regulators of embryonic and adult hematopoiesis, the mechanisms behind the leukemia predisposition in GATA2 haploinsufficiencies is ambiguous. The only curative treatment option currently available is allogeneic hematopoietic stem cell transplantation (allo-SCT). However, allo-SCT can only be applied at a relatively late stage of the disease as its applicability is compromised by treatment related morbidity and mortality (TRM). Alternatively, autologous hematopoietic stem cell transplantation (auto-SCT), which is associated with significantly less TRM, might become a treatment option if repaired hematopoietic stem cells would be available. Here we discuss the recent literature on leukemia predisposition syndromes caused by GATA2 mutations, current knowledge on the function of GATA2 in the hematopoietic system and advantages and pitfalls of potential treatment options provided by genome editing.