Miracle-dz/UniFAR-FTUs huggingface dataset:
Maxwell Matters

Charges are everywhere because most atoms are charged. Chemical bonds are formed by electrons with their charge. Charges move and interact according to Maxwell's equations in space and in atoms where the equations of electrodynamics are embedded in Schrödinger’s equation as the potential. Maxwell’s equations are universal, valid inside atoms and between stars from times much shorter than those of atomic motion (0.1 femtoseconds) to years (32 mega-seconds). Maxwell’s equations enforce the conservation of current. Analysis shows that the electric field can take whatever value is needed to ensure conservation of current. The properties of matter rearrange themselves to satisfy Maxwell’s equations and conservation of current. Conservation of current is as universal as Maxwell’s equations themselves. Yet equations of electrodynamics find little place in the literature of material physics, chemistry, or biochemistry. Kinetic models of chemistry and Markov treatments of atomic motion are ordinary differential equations in time and do not satisfy conservation of current unless modified significantly. Systems at equilibrium, without macroscopic flow, have thermal fluctuating currents that are conserved according to the Maxwell equations although the macroscopic averages of the thermal currents are zero. The macroscopic consequences of atomic scale fluctuating thermal currents are not known but are likely to be substantial because of the nonlinear interactions in systems like these, in which ‘everything interacts with everything else’. Version 3: Textbook models are described in Version 3, since most scientists are familiar with them, however unrealistic they are. Wording is changed a little, hopefully improved. A new section derives conservation of current from the continuity equation. Version 4: Current and flux of charge in a resistor are described on p. 13. Textbook models describe displacement currents of materials by a dielectric coefficient that is a true constant. Textbook treatments automatically satisfy conservation of current. In the textbook approximation, the displacement current of matter is proportional to . t ∂ ∂ E However, dielectric coefficients of real materials cannot be described by a constant because the displacement current of real matter is not proportional to t ∂ ∂ E with a single proportionality constant. Even in the simplest ion solutions, dielectric coefficients vary in time by factors ~40× and displacement currents need to be described by convolution integrals with memory kernels. Dielectric properties in real matter are in fact much more complex than that: no one knows how to describe them in a general way. A general formulation of conservation of current is used here that applies whatever the properties of matter. We define ‘current’ as anything that creates curl B . Whatever creates curl B is conserved everywhere, under all conditions, at every time. The vacuum displacement current 0 t ε ∂ ∂ E changes so current is conserved everywhere, under all conditions, at every time. arXiv: 1607.0669, Version 4, September 21, 2016
A new conjugate gradient-like method with sufficient descent condition and its global convergence based on the Armijo line search

In this paper, we propose a new conjugate gradient-like algorithm. The step directions generated by the new algorithm satisfy a sufficient descent condition independent of the line search. The global convergence of the new algorithm, with the Armijo backtracking line search, is proved. Numerical experiments indicate the efficiency and robustness of the new algorithm in solving a collection of unconstrained optimization problems from CUTEst package.
MODIS multi-temporal data retrieval and processing toolbox

The package functionalities are focused for the download and processing of multi-temporal datasets from MODIS sensors. All standard MODIS grid data can be accessed and processed by the package routines. The package is still in alpha development and not all the functionalities are available for now. One of the main capabilities is the retrieval of data from remote sources by defining simple spatial and temporal subsets. The retrieval of the data is performed or through a connection to the main MODIS ftp data pools (LP DAAC and LAADS) or through the MODIS Web service based on SOAP (Simple Object Access Protocol). Further it is possible to define user defined sources and make accessible also data within local area network. As an example, the download of all MODIS (Terra and Aqua) NDVI 16 Days composite at 250 m data covering Austria, is performed by the command getHdf(“product=”MxD13Q1”, extent=”Austria”). To limit the temporal coverage to the year 2005 the user has just to add begin=”2005001” and end=”2005365” within the function arguments. Once data is downloaded the package holds pre-processing functionalities. The main pre-processing capabilities are, mosaicking, resampling, SDS extraction and bit coded SDS decoding. These are mainly performed by using an interface to the MODIS re-projection Tool (MRT,https://lpdaac.usgs.gov/tools/modis\\_reprojection\\_tool) or to the Geospatial Data Abstraction Library (GDAL,http://www.gdal.org/). The download and the pre-processing on user side can be performed by typing a single function and a few simple parameters. The package defaults are set to fit most of the user needs. This makes it possible to use the functionality of the package without having many skills in the programming language R. Output of the pre-processing are standard format raster files usable in any other software that handles remote sensed images. For example the generation of a multi-temporal image stack for the year 2005 over Austria using MRT the function is: runMrt(product=”MxD13Q1”, extent=”austria”, begin=”2005001”, end=”2005365”) this function internally contains the getHdf function that handles the data acquisition. Than using internally MRT the data is re-projected, mosaicked and cropped to a bounding box containing Austria. The main-processing part (currently not available) contains functions focused on the processing of multi-temporal data sets. Further work on the MODIS package will focus on the smoothing and filtering, trend analysis, change-detection and extraction of phenological parameters. The package outputs are aligned with the major geospatial R packages, providing so the possibility to benefit from mostly all geospatial tools sets within R.
Results from a Longitudinal Early Literacy Intervention Study: Expected and Unexpected Outcomes.

Findings are presented from a two-year longitudinal study involving the Quick60 Foundation programme for beginning readers. This programme is a 32 week whole-class literacy curriculum that systematically and explicitly teaches key early literacy skills. End of Year 2 literacy performances of students receiving this programme during their first year of schooling were compared with students who received “regular” literacy instruction. Participants were in low decile Auckland schools, with large numbers of Maˉori and Pasifika students. At the end of Year 2, Quick60 students outperformed comparison students on reading book level, word knowledge, and reading accuracy; results for reading comprehension were not statistically significant but in the expected direction for Quick60 students. Surprisingly, students from home backgrounds rated by teachers as “normal” did not perform considerably better than students from “difficult” backgrounds. The results are discussed in terms of the benefits of explicit, code-orientated literacy instruction from the outset of schooling.
Resource-efficient Control in Cyber-Physical Systems Resource efficient stochastic predictive control under packet dropouts

This study presents a resource efficient framework for a class of stochastic control systems that utilises state dependent control strategies in order to reduce the online computational load. When the states are in a given neighbourhood of the desired operating point, the controller is switched off, and data from the feedback channel is not transmitted. Outside this neighbourhood, the authors pay close attention to the performance of the controller by adopting a stochastic predictive algorithm when the states are in a predefined comfort zone, and activate a recovery algorithm beyond the comfort zone that secures at least good qualitative properties. The authors demonstrate that the proposed controller leads to mean square boundedness of the closed loop states in the presence of stochastic noise, bounded control authority, and control channel erasures, while entailing a dramatic reduction in network traffic and computational resources.
Big Data Predictive and Prescriptive Analytics

The Analytics tools are capable of suggesting the most favourable future planning by analyzing “Why” and “How” blended with What, Who, Where, and When. Descriptive, Predictive, and Prescriptive analytics are the analytics currently in use. Clear understanding of these three analytics will enable an organization to chalk out the most suitable action plan taking various probable outcomes into account. Currently, corporate are flooded with structured, semi-structured, unstructured, and hybrid data. Hence, the existing Business Intelligence (BI) practices are not sufficient to harness potentials of this sea of data. This change in requirements has made the cloud-based “Analytics as a Service (AaaS)” the ultimate choice. In this chapter, the recent trends in Predictive, Prescriptive, Big Data analytics, and some AaaS solutions are discussed.
Complex transmission patterns and age-related dynamics of a selfish mtDNA deletion.

Despite wide-ranging implications of selfish mitochondrial DNA (mtDNA) elements for human disease and topics in evolutionary biology (e.g., speciation), the forces controlling their formation, age-related accumulation, and offspring transmission remain largely unknown. Selfish mtDNA poses a significant challenge to genome integrity, mitochondrial function and organismal fitness. For instance, numerous human diseases are associated with mtDNA mutations; however, few genetic systems can simultaneously represent pathogenic mitochondrial genome evolution and inheritance. The nematode Caenorhabditis briggsae is one such system. Natural C. briggsae isolates harbor varying levels of a large-scale deletion affecting the mitochondrial nduo-5 gene, termed nad5Δ. A subset of these isolates contain putative compensatory mutations that may reduce the risk of deletion formation. We studied the dynamics of nad5Δ heteroplasmy levels during animal development and transmission from mothers to offspring in genetically diverse C. briggsae natural isolates. Results support previous work demonstrating that nad5Δ is a selfish element and that heteroplasmy levels of this deletion can be quite plastic, exhibiting high degrees of inter-family variability and divergence between generations. The latter is consistent with a mitochondrial bottleneck effect, and contrasts with previous findings from a laboratory-derived model uaDf5 mtDNA deletion in C. elegans. However, we also found evidence for among-isolate differences in the ability to limit nad5Δ accumulation, the pattern of which suggested that forces other than the compensatory mutations are important in protecting individuals and populations from rampant mtDNA deletion expansion over short time scales.
Using PyMOL as a platform for computational drug design

PyMOL, a cross‐platform molecular graphics tool, has been widely used for three‐dimensional (3D) visualization of proteins, nucleic acids, small molecules, electron densities, surfaces, and trajectories. It is also capable of editing molecules, ray tracing, and making movies. This Python‐based software, alongside many Python plugin tools, has been developed to enhance its utilities and facilitate the drug design in PyMOL. To gain an insightful view of useful drug design tools and their functions in PyMOL, we present an extensive discussion on various molecular modeling modules in PyMOL, covering those for visualization and analysis enhancement, protein–ligand modeling, molecular simulations, and drug screening. This review provides an excellent introduction to present 3D structures visualization and computational drug design in PyMOL. WIREs Comput Mol Sci 2017, 7:e1298. doi: 10.1002/wcms.1298
Patient-reported lung symptoms and quality of life before and after radiation therapy for non-small cell lung cancer: correlation with radiation pneumonitis and functional imaging

Radiation-induced toxicity, particularly radiation pneumonitis (RP), negatively affects patients’ quality of life (QOL) and survival after definitive thoracic radiation therapy (RT) [1,2]. Baseline QOL demonstrated to be independent prognostic factor for survival in randomized radiation dose escalation trial RTOG 0617 [3]. In the recent prospective study, single photon emissioncomputed tomography (SPECT) was found to be a valuable functional imaging modality to predict radiation-induced lung injury after curative RT for non-small cell lung cancer (NSCLC) [4–6]. The primary endpoint of the study was development of clinically significant grade 2 and higher RP, as assessed by Common Terminology Criteria for Adverse Events (CTCAE) [7]. Patient-reported outcomes are an important secondary endpoint of this study. The objective of the study was to investigate QOL and patient-reported respiratory symptoms before and after definitive radiotherapy for NSCLC. Correlation of patient-reported outcomes with radiation pneumonitis was investigated, together with prognostic value of dose-volume parameters on the lung symptoms and QOL outcomes. The primary hypothesis predicted worsening of general QOL and lung-related symptoms in patients who developed radiation pneumonitis. It has been demonstrated that the risk of radiation pneumonitis depends on the radiation dose to a threshold of lung volume and mean lung dose [1,2,4]. Functional dose-volume parameters, and mean dose to the functional lung, as defined by SPECT scan, showed to provide an improved predictive value for radiation-induced lung damage, compared to the conventional CTbased parameters [4]. In this study, relationship between functional dose-volume parameters and patient-reported QOL and lung symptoms measures after curative RT were analyzed.
Detecting insertion, substitution, and deletion errors in radiology reports using neural sequence-to-sequence models.

Background Errors in grammar, spelling, and usage in radiology reports are common. To automatically detect inappropriate insertions, deletions, and substitutions of words in radiology reports, we proposed using a neural sequence-to-sequence (seq2seq) model. Methods Head CT and chest radiograph reports from Mount Sinai Hospital (MSH) (n=61,722 and 818,978, respectively), Mount Sinai Queens (MSQ) (n=30,145 and 194,309, respectively) and MIMIC-III (n=32,259 and 54,685) were converted into sentences. Insertions, substitutions, and deletions of words were randomly introduced. Seq2seq models were trained using corrupted sentences as input to predict original uncorrupted sentences. Three models were trained using head CTs from MSH, chest radiographs from MSH, and head CTs from all three collections. Model performance was assessed across different sites and modalities. A sample of original, uncorrupted sentences were manually reviewed for any error in syntax, usage, or spelling to estimate real-world proofreading performance of the algorithm. Results Seq2seq detected 90.3% and 88.2% of corrupted sentences with 97.7% and 98.8% specificity in same-site, same-modality test sets for head CTs and chest radiographs, respectively. Manual review of original, uncorrupted same-site same-modality head CT sentences demonstrated seq2seq positive predictive value (PPV) 0.393 (157/400; 95% CI, 0.346-0.441) and negative predictive value (NPV) 0.986 (789/800; 95% CI, 0.976-0.992) for detecting sentences containing real-world errors, with estimated sensitivity of 0.389 (95% CI, 0.267-0.542) and specificity 0.986 (95% CI, 0.985-0.987) over n=86,211 uncorrupted training examples. Conclusions Seq2seq models can be highly effective at detecting erroneous insertions, deletions, and substitutions of words in radiology reports. To achieve high performance, these models require site- and modality-specific training examples. Incorporating additional targeted training data could further improve performance in detecting real-world errors in reports.
Structural determinants conferring unusual long life in human serum to rattlesnake‐derived antimicrobial peptide Ctn[15‐34]

Ctn[15‐34], a downsized version of the snake venom cathelicidin‐like peptide crotalicidin (Ctn), shows an unusually high lifespan (t1/2, approximately 12 h) in human serum, which significantly adds to its promise as an antimicrobial and antitumor agent. Herein we investigate the role of Ctn[15‐34] structure on serum survival. Using a set of analogs, we show that C‐terminal amidation, as well as the specific layout of the Ctn[15‐34] sequence—a helical N‐terminal domain followed by a hydrophobic domain—is crucial for slow degradation, and any change in their arrangement results in significantly lower t1/2. Aside from the privileged primary structure, features such as self‐aggregation can be ruled out as causes for the long serum life. Instead, studies in other protease‐rich fluids suggest a key role for certain human serum components. Finally, we demonstrate that Ctn[15‐34] is able to induce bacterial death even after 12‐hour pre‐incubation in serum, in agreement with the proteolytic data. Altogether, the results shed light on the uncommon stability of Ctn[15‐34] in human serum and confirm its potential as an anti‐infective lead.
Methodology for developing and evaluating food-based dietary guidelines and a Healthy Eating Index for Ethiopia: a study protocol

Introduction Food-based dietary guidelines (FBDGs) are used to promote and maintain healthy eating in a population, by providing country-specific guidance. However, many African countries like Ethiopia do not have FBDGs. This paper describes the methodology for the development of Ethiopian FBDGs and for creating and evaluating a Healthy Eating Index and a scoring tool that can be used to monitor the adherence of the population to FBDGs. Methods and analysis A multidisciplinary technical working group will be tasked to develop FBDGs for the general population above 2 years of age based on identification of priority diet-related public health problems and risk factors, and a systematic review of dietary patterns in relation to the identified priority health outcomes, following a multistep process. FBDGs will be translated into daily food choices for specific subpopulations by applying linear programming using data from the National Food Consumption Survey (NFCS) of 2011. FBDGs will be evaluated for cultural appropriateness, acceptability, consumer understanding and practicality. A dietary gap assessment will be conducted by comparing the national food supply with the country’s food demand. In addition an Ethiopian Healthy Eating Index (EHEI) will be developed based on the FBDGs using the NFCS data. The EHEI will be evaluated by comparing the EHEI Score based on 24 hours diet recall with that of the EHEI Score based on a Food Frequency Questionnaire, by analysing the association of the EHEI Score with population characteristics and micronutrient intake with or without additional adjustment for energy intake. Finally, a brief Food Quality Screening tool scoring for the important EHEI components will be developed to enable evaluation for counselling. Ethics and dissemination Ethical approval is received from the Scientific and Ethical Review Office of the Ethiopian Public Health Institute. The findings will be disseminated through peer-reviewed publications.A dissemination workshop will be organised with key implementing sectors of the food system for a healthier diet (http://a4nh.cgiar.org/our-research/research-flagships/) and with key public and private partners. The findings from this study will be translated into FBDGs and shared through conferences, reports and the mass media (TV and radio). Trial registration number NCT03394963; Pre-results.
The alphabet projection of spectra.

In metabolomics, glycomics, and mass spectrometry of structured small molecules, the combinatoric nature of the problem renders a database impossibly large and thus de novo analysis is necessary. De novo analysis requires an alphabet of mass difference values used to link peaks in fragmentation spectra when they are different by a mass in the alphabet divided by a charge. Often, this alphabet is not known, prohibiting de novo analysis. A method is proposed that, given fragmentation mass spectra, identifies an alphabet of m/z differences that can build large connected graphs from many intense peaks in each spectrum from a collection. We then introduce a novel approach to efficiently find recurring substructures in the de novo graph results.
Dynamic Sensing-Rate Control Scheme Using a Selective Data-Compression for Energy-Harvesting Wireless Sensor Networks

: In wireless sensor networks, increasing the sensing rate of each node to improve the data accuracy usually incurs a decrease of network lifetime. In this study, an energy-adaptive data compression scheme is proposed to efficiently control the sensing rate in an energy-harvesting wireless sensor network (WSN). In the proposed scheme, by utilizing the surplus energy effectively for the data compression, each node can increase the sensing rate without any rise of blackout time. Simulation result verifies that the proposed scheme gathers more amount of sensory data per unit time with lower number of blackout nodes than the other compression schemes for WSN.
HIV infection among women in the United States: 2000–2017

ABSTRACT Although HIV diagnoses among women have declined in recent years in the United States (U.S.), women accounted for 19% of new HIV diagnoses in 2016. In addition, women comprise 24% of the 973,846 persons living with HIV infection in the U.S. However, HIV prevention interventions targeting women are limited. We performed a review on HIV infection in women to increase awareness, improve overall care, and inform intervention development. A systematic literature review was conducted using literature published in PubMed, PsychINFO (EBSCO), and Scopus from July 2000 and June 2017. We included studies that: (1) were conducted in the U.S., (2) enrolled at least 50 HIV-positive women, and (3) utilized a case–control, cohort, or surveillance study design. Of 7497 articles, 48 articles met inclusion criteria. HIV diagnoses among women declined 32% between 2001 and 2016. In 2016, 61% of diagnoses in women were among African American women, and 56% were in the South. Women reported barriers to HIV care largely due to psychosocial challenges and social/structural determinants of health (SDH) barriers. Though new diagnoses among women have declined, racial and regional disparities remain. HIV prevention and research efforts with women are vital to inform interventions and reduce disparities.