Miracle-dz/UniFAR-FTUs huggingface dataset:
Research, part of a Special Feature on The influence of human demography and agriculture on natural systems in the Neotropics A Peri-Urban Neotropical Forest Transition and its Consequences for Environmental Services

We analyzed changes in land cover in the Sierra de San Javier and its surroundings, an area of ca. 70 000 ha near San Miguel de Tucuman, an urban center of ca. 1 million people in subtropical Argentina. The analysis covered two periods: 1949-1972 and 1972-2006 using remote sensing techniques. For the year 2001, we mapped the patterns of distribution of secondary forests dominated by the most abundant exotic tree species ( Ligustrum lucidum). Based on land-cover maps, we estimated sediment yield as an index of watershed condition. Urban area was growing during the whole study period. Between 1949 and 2006, forest area increased approximately 1400 ha, mostly over abandoned agriculture and grasslands; this expansion was accelerated between 1972 and 2006. Increased forest cover resulted in a reduction in erosion and sediment yield that was disproportionately large, as most new forests are located in areas of steep slopes and high rainfall. By 2001, Ligustum-dominated forests had expanded to more than 500 ha, in the southern portion of the sierra only. Overall, the analysis quantifies a process of Neotropical peri- urban forest transition, likely associated with socioeconomic changes related to population urbanization, that promotes improvements of some environmental services, such as watershed and biodiversity conservation. However, natural communities are strongly affected by past land use and neighboring urban areas, which have promoted a growing importance of exotic species with mostly unknown ecological consequences.
CHRNE compound heterozygous mutations in congenital myasthenic syndrome

Rationale: Congenital myasthenic syndrome (CMSs) are a group of rare genetic disorders of the neurological junction, which can result in structural or functional weakness. Here, we characterized a case of CMS in order to clarify the diagnosis and expand the understanding of it. The molecular diagnosis had implications for choice of treatment and genetic counseling. Patient concerns: A 3-year-old male patient with CMS had ptosis and limb weakness for 2 months after birth. Clinical course and electrophysiological, imaging, and genetic findings were assessed. Protein structure/function was predicted. A novel mutation of c.295C>T (exon 4) and another known mutation of c.442T>A (exon 5) were found in CHRNE. Both mutations localized in conserved sequences. The c.442T>A (p.C148S) missense mutation in CHRNE was predicted to be damaging/deleterious. The iterative threading assembly refinement (I-TASSER) server generated vastly different 3-dimensional (3D) atomic models based on protein sequences from wide-type and novel nonsense mutation of c.295C>T (p.R99X) in CHRNE. Diagnoses: The diagnosis of CMS with CHRNE mutations in Han Chinese was confirmed. Interventions: The patient was given prednisone (10 mg, once daily, taken orally) and pyridostigmine (15 mg, three times a day, taken orally). Outcomes: The patient had a moderate response to prednisone and pyridostigmine. Lessons: We expanded the genotype and phenotype of CMS with CHRNE mutations in Han Chinese and provided new insights into the molecular mechanism of CMS and help to the diagnosis and treatment of CMS.
Influence of Air Pollution on Hospital Admissions in Adult Asthma in Northeast China

Background: Asthma is a common chronic respiratory disease and is related to air pollution exposure. However, only a few studies have concentrated on the association between air pollution and adult asthma. Moreover, the results of these studies are controversial. Therefore, the present study aimed to analyze the influence of various pollutants on hospitalization due to asthma in adults. Methods: A total of 1019 unrelated hospitalized adult asthma patients from Northeast China were recruited from 2014 to 2016. Daily average concentrations of air pollutants (particulate matter <2.5 &mgr;m [PM2.5], particulate matter <10 &mgr;m [PM10], sulfur dioxide [SO2], nitrogen dioxide [NO2], and carbon monoxide [CO]) were obtained from the China National Environmental Monitoring Centre website from 2014 to 2016. Cox logistic regression analysis was used to analyze the relationship between air pollutants and hospital admissions in adult asthma. Results: The maximum odds ratio (OR) value for most air pollutants occurred on lag day 1. Lag day 1 was chosen as the exposure period, and 8 days before onset was chosen as the control period. Three pollutants (PM2.5, CO, and SO2) were entered into the regression equation, and the corresponding OR (95% confidence interval) was 0.995 (0.991–0.999), 3.107 (1.607–6.010), and 0.979 (0.968–0.990), respectively. Conclusions: A positive association between hospital admissions and the daily average concentration of CO was observed. CO is likely to be a risk factor for hospital admissions in adults with asthma.
Size-dependent patterns of reproductive investment in the North American invasive plant species Triadica sebifera (L.) Small (Euphorbiaceae)

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Using induced pluripotent stem cells derived neurons to model brain diseases

The ability to use induced pluripotent stem cells (iPSC) to model brain diseases is a powerful tool for unraveling mechanistic alterations in these disorders. Rodent models of brain diseases have spurred understanding of pathology but the concern arises that they may not recapitulate the full spectrum of neuron disruptions associated with human neuropathology. iPSC derived neurons, or other neural cell types, provide the ability to access pathology in cells derived directly from a patient's blood sample or skin biopsy where availability of brain tissue is limiting. Thus, utilization of iPSC to study brain diseases provides an unlimited resource for disease modelling but may also be used for drug screening for effective therapies and may potentially be used to regenerate aged or damaged cells in the future. Many brain diseases across the spectrum of neurodevelopment, neurodegenerative and neuropsychiatric are being approached by iPSC models. The goal of an iPSC based disease model is to identify a cellular phenotype that discriminates the disease-bearing cells from the control cells. In this mini-review, the importance of iPSC cell models validated for pluripotency, germline competency and function assessments is discussed. Selected examples for the variety of brain diseases that are being approached by iPSC technology to discover or establish the molecular basis of the neuropathology are discussed.
In Vivo Imaging of Brain Ischemia Using an Oxygen-Dependent Degradative Fusion Protein Probe

Within the ischemic penumbra, blood flow is sufficiently reduced that it results in hypoxia severe enough to arrest physiological function. Nevertheless, it has been shown that cells present within this region can be rescued and resuscitated by restoring perfusion and through other protective therapies. Thus, the early detection of the ischemic penumbra can be exploited to improve outcomes after focal ischemia. Hypoxia-inducible factor (HIF)-1 is a transcription factor induced by a reduction in molecular oxygen levels. Although the role of HIF-1 in the ischemic penumbra remains unknown, there is a strong correlation between areas with HIF-1 activity and the ischemic penumbra. We recently developed a near-infrared fluorescently labeled-fusion protein, POH-N, with an oxygen-dependent degradation property identical to the alpha subunit of HIF-1. Here, we conduct in vivo imaging of HIF-active regions using POH-N in ischemic brains after transient focal cerebral ischemia induced using the intraluminal middle cerebral artery occlusion technique in mice. The results demonstrate that POH-N enables the in vivo monitoring and ex vivo detection of HIF-1-active regions after ischemic brain injury and suggest its potential in imaging and drug delivery to HIF-1-active areas in ischemic brains.
Changes in Gene Expression and Estrogen Receptor Cistrome in Mouse Liver Upon Acute E 2 Treatment

28 Transcriptional regulation by the Estrogen Receptor α (ER) has been investigated mainly in breast 29 cancer cell lines but estrogens such as 17β-Estradiol (E2) exert numerous extra-reproductive effects, 30 particularly in the liver where E2 exhibits both protective metabolic and deleterious thrombotic 31 actions. To analyze the direct and early transcriptional effects of estrogens in the liver, we determined 32 the E2-sensitive transcriptome and ER cistrome in mice following acute administration of E2 or 33 placebo. These analyses revealed the early induction of genes involved in lipid metabolism, which fits 34 with the crucial role of ER in the prevention of liver steatosis. Characterization of the chromatin state 35 of ER binding sites (BSs) in mice expressing or not ER demonstrated that ER is not required per se 36 for the establishment and/or maintenance of chromatin modifications at the majority of its BSs. This 37 is presumably a consequence of a strong overlap between ER and Hepatocyte nuclear factor 4 α 38 (Hnf4α) BSs. In contrast, 40% of the BSs of the pioneer factor Foxa2 were dependent upon ER 39 expression, and ER expression also affected the distribution of nucleosomes harboring dimethylated 40 H3K4 around Foxa2 BSs. We finally show that, in addition to a network of liver-specific transcription 41 factors including Cebpα/β and Hnf4α, ER might be required for proper Foxa2 function in this tissue. 42
Compliant Motion Control for Multisegment Continuum Robots With Actuation Force Sensing

During exploration through tortuous unstructured passages by continuum robots, methods are required to minimize the force interaction between the environment and the robot along its length. This paper presents and evaluates an algorithm for compliant motion control of continuum robots subjected to multiple unknown contacts with the environment. A mapping of external wrenches to a generalized force in the configuration space of a multisegment continuum robot is presented and related to measured joint-level actuation forces. These measurements are applied as inputs to a low-level compliant motion controller. Friction and modeling uncertainties, presenting an unknown nonlinear deviation from the nominal system model, are corrected via a feed-forward estimate provided by a support vector machine. The controller is evaluated on Ø9 and Ø5 mm multisegment continuum robots. We quantify the minimal interaction forces needed to generate compliant motion and demonstrate the ability of the controller to minimize interaction forces during insertion through tortuous passages.
Exposure to predators does not lead to the evolution of larger brains in experimental populations of threespine stickleback

Natural selection is often invoked to explain differences in brain size among vertebrates. However, the particular agents of selection that shape brain size variation remain obscure. Recent studies suggest that predators may select for larger brains because increased cognitive and sensory abilities allow prey to better elude predators. Yet, there is little direct evidence that exposure to predators causes the evolution of larger brains in prey species. We experimentally tested this prediction by exposing families of 1000–2000 F2 hybrid benthic‐limnetic threespine stickleback to predators under naturalistic conditions, along with matched controls. After two generations of selection, we found that fish from the predator addition treatment had significantly smaller brains (specifically smaller telencephalons and optic lobes) than fish from the control treatment. After an additional generation of selection, we reared experimental fish in a common environment and found that this difference in brain size was maintained in the offspring of fish from the predator addition treatment. Our results provide direct experimental evidence that (a) predators can indeed drive the evolution of brain size–‐but not in the fashion commonly expected and (b) that the tools of experimental evolution can be used to the study the evolution of the vertebrate brain.
THE IMPACTS OF SELF-BRAND CONGRUENCE ON BRAND LOYALTY: A STUDY ON CELLULAR PHONE USERS

In this study, hypothesized that congruence or incongruence of consumer image and brand image leads positive or negative attitudes towards brand and these attitudes affect consumer decision process as mediators, formation of brand loyalty process is approached from an image congruence perspective. A preformed questionnaire form was used as data collection tool and pure data was analyzed with Structural Equation Modeling in order to demonstrate how observed variables fit the theoretical model. Analysis results show that consumer image and brand image congruence affect love/passion and commitment, and love/passion and commitment affect brand loyalty positively. Other attitudes and satisfaction are found statistically insignificant relation with brand loyalty
The Space-Borne SBAS-DInSAR Technique as a Supporting Tool for Sustainable Urban Policies: The Case of Istanbul Megacity, Turkey

In today’s urbanizing world, home of 28 megacities, there is a growing need for tools to assess urban policies and support the design and implementation of effective development strategies. Unsustainable practices of urbanization bring major implications for land and environment, and cause a dramatic increase of urban vulnerability to natural hazards. In Istanbul megacity, disaster risk reduction represents a challenging issue for urban managers. In this paper, we show the relevance of the space-borne Differential SAR Interferometry (DInSAR) technique as a tool for supporting risk management, and thus contributing to achieve the urban sustainability. To this aim, we use a dataset of high resolution SAR images collected by the TerraSAR-X satellite that have been processed through the advanced (multi-temporal) Small BAseline Subset (SBAS)—DInSAR technique, thus producing spatially-dense deformation velocity maps and associated time-series. Results allow to depict an up-to-date picture of surface deformations occurring in Istanbul, and thus to identify urban areas subject to potential risk. The joint analysis of remotely sensed measurements and ancillary data (geological and urban development information) provides an opportunity for city planners and land professionals to discuss on the mutual relationship between urban development policies and natural/man-made hazards.
A containerized analytics framework for data and compute-intensive pipeline applications

The joint effort of scientific collaborations and the expanding data market creates demand for high-performance and data-intensive analytics infrastructures that can exploit the potential of heterogeneous multi-core architectures with dynamic and scalable execution environments. Contemporary approaches focus on developing efficient parallel application models, but lack the flexibility of efficiently integrating and utilizing native or accelerator-based code. In this work, we illustrate a novel approach on mending this shortcoming and offering seamless application integration into a highly versatile execution infrastructure. The centerpiece is a framework of containerized execution units and management thereof for satisfying the diverse requirements of data analytics pipelines and its stages. Containers not only ease distribution and deployment of applications, but, more importantly enable an efficient synthesis of different stage implementation variants aimed towards exploiting heterogeneous computing resources. Consequently, this approach allows the infrastructure to utilize mainstream data and compute-intensive techniques and paradigms to achieve the goal of efficient pipeline execution. We present our approach in form of a requirement analysis, a multi-tier architecture description, and deployment scenarios based on our current prototype implementation.
Culture and Online Learning: Global Perspectives and Research, edited by Insung Jung and Charlotte Nirmalani Gunawardena

The topic of culture in distance education (DE) continues to become more important in recent years. First and foremost, DE has grown and become more accepted with the advent of online education in particular. In the United States there are estimated to be 5.8 million DE students in higher education alone (Allen and Seaman 2016). That number is much higher when DE offerings in secondary education, training, and continuing professional education, among others, are included. The sheer number of people now taking DE would suggest there is more cultural diversity of students and teachers within courses. Second, DE, and online education in particular, affords more access to students from and in different parts of the world. This has been the case for conventional DE and online offerings for some time. Student diversity is highlighted more recently with MOOCs, which in some courses have students from over 195 countries (Jablokow, Matson, and Velegol 2014). The growth of DE is not unique to the United States; nor is the increasing diversity of students in courses. Given these changes to DE, Jung and Gunawardena have edited a very useful book titled Culture and Online Learning. Discussing culture in education is no small undertaking. “Culture is one of the two or three most complicated words in the English language,” said Raymond Williams (2014), the late adult educator and cultural theorist, in his book
Autonomous Data Management and Federation to Support High-throughput Query Evaluations over Voluminous Datasets

In recent years, both the breadth and depth of information being generated and stored has continued to grow rapidly, causing an information explosion. Observational devices and remote sensing equipment are no exception to this rule, giving researchers new avenues for detecting and predicting phenomena at a global scale. To cope with these storage loads, hybrid clouds offer an elastic solution that also satisfies processing and budgetary needs. This paper describes our algorithms and system design for dealing with voluminous datasets in a hybrid cloud setting. Our distributed storage framework autonomously tunes in-memory data structures and query parameters to ensure efficient retrievals and minimize resource consumption. To circumvent processing hotspots, we predict changes in incoming traffic and federate our query resolution structures to the public cloud for processing. We also demonstrate the efficacy of our framework on a real-world, petabyte dataset consisting of over 20 billion files.
The Effects of Situational and Dispositional Factors on the Change in Financial Risk Tolerance

Utilizing the lens of Heider’s (1958) attribution theory and Grable and Joo’s (2004) conceptual framework, this chapter studies the effect of situational and dispositional attributions on changes in financial risk tolerance. Situational factors are assessed through changes in household situation and changes in macroeconomic factors. For dispositional factors, changes upon sensation seeking attitudes are explored. The data employed in this research come from the 1993, 1994, and 2006 National Longitudinal Survey of Youth (N = 5,449). Results from structural equation modeling indicate that changes in internal attributions have a significant and positive effect (coefficient = 0.12, p <0.01) on the change in risk tolerance, as is true for changes in external attributions where a significant effect is seen (coefficient = 0.30, p <0.01). Thus, the findings from this study support the conceptual framework premised on Heider’s attribution theory and Grable and Joo’s (2004) conceptual model.
Correlation effects and many-body interactions in water clusters

Background: The quantum-chemical description of the interactions in water clusters is an essential basis for deriving accurate and physically sound models of the interaction potential for water to be used in molecular simulations. In particular, the role of many-body interactions beyond the two-body interactions, which are often not explicitly taken into account by empirical force fields, can be accurately described by quantum chemistry methods on an adequate level, e.g., random-phase approximation electron correlation methods. The relative magnitudes of the different interaction energy contributions obtained by accurate ab initio calculations can therefore provide useful insights that can be exploited to develop enhanced force field methods. Results: In line with earlier theoretical studies of the interactions in water clusters, it has been found that the main contribution to the many-body interactions in clusters with a size of up to N = 13 molecules are higher-order polarisation interaction terms. Compared to this, many-body dispersion interactions are practically negligible for all studied sytems. The two-body dispersion interaction, however, plays a significant role in the formation of the structures of the water clusters and their stability, since it leads to a distinct compression of the cluster sizes compared to the structures optimized on an uncorrelated level. Overall, the many-body interactions amount to about 13% of the total interaction energy, irrespective of the cluster size. The electron correlation contribution to these, however, amounts to only about 30% to the total many-body interactions for the largest clusters studied and is repulsive for all structures considered in this work. Conclusion: While this shows that three- and higher-body interactions can not be neglected in the description of water complexes, the electron correlation contributions to these are much smaller in comparison to the two-body electron correlation effects. Efficient quantum chemistry approaches for describing intermolecular interactions between water molecules may therefore describe higher-body interactions on an uncorrelated Hartree–Fock level without a serious loss in accuracy.