Miracle-dz/UniFAR-FTUs huggingface dataset:
Templet : Domain-specific Language for Concurrency Control *

The article presents a new domain-specific language (DSL) for concurrency control. Runtime library is a common way to implement concurrency control. However, this method often leads to an increase in application complexity. The design of new concurrent language is natively difficult. We propose a compromise solution which uses DSL with C++ programming language. The article discusses DSL syntax, programming model, and implementation of concurrency control in the Templet language. Keywords—domain-specific language; concurrency control; actor model; language-oriented programming; skeleton programming
Using Deep Neural Network to Identify Cancer Survivors Living with Post-Traumatic Stress Disorder on Social Media

Survivors of cancer are at-risk for the lifelong effects of disease and treatment. A significant number of them face Post-Traumatic Stress Disorder (PTSD) that may adversely affect their mental health. Twitter is a social networking site that allows users to interact with others by posting short messages (tweets). These tweets, which to a certain extent reflect the users psychological state, are convenient for data collection. However, Twitter also contains a mix of noisy and genuine tweets. The process of manually identifying the genuine tweets is expensive and time-consuming. Thus, we stream the data using cancer as a keyword and filter the tweets with cancer-free and PTSD related keywords without having to label each tweet manually. Convolutional Neural Network (CNN) learns the representations of the input to identify cancer survivors with PTSD. The experiments on real-world datasets show that the model outperforms the baselines and correctly classifies the new tweets.
ChoroLibre: Supporting Georeferenced Demographic Information Visualization Through Hierarchical Choropleth Maps

The advent of Smart City and Big Data have generated many data on demographical factors, such as health, public transportation, basic sanitation, education, among others. However, this growing volume of data is little related to their demographic contexts, and when maps represent these data, they generally do not have the interactivity to allow exploration, either by changing the studied territory, increasing or decreasing its scope, relating other data for analysis, visually encoding a data, among other possibilities. Thus, this work aims to present a system that represents demographic data, specifically in geographic maps, and how to make it interactive for the user, presenting the software ChoroLibre as a final product: an opensource tool for visualizing hierarchical and interactive Choropleth geographic maps for the Web. To this end, this paper describes the architecture, implementation, methodology, technologies, and the developed functionalities of the ChoroLibre tool.
Brine rejection and hydrate formation during freeze desalination.

Studying the freezing of saltwater on a molecular level is of fundamental importance for improving freeze desalination methods. Here, we study the freezing process of NaCl solutions using a combination of x-ray diffraction and molecular dynamics simulations for different salt-water concentrations, ranging from seawater conditions to saturation. A linear superposition model can reproduce well the brine rejection due to hexagonal ice Ih formation and allows us to quantify the fraction of recovered ice and brine. Furthermore, upon further cooling we observe the formation of NaCl$\cdot$2H$_2$O hydrates, which coexist with ice Ih in the form of micro-pockets. The molecular dynamics simulations are utilized to model the formation of NaCl crystallites and quantify ion-water cross-correlations and ion inclusion within the ice Ih lattice. From the simulation we estimate that the salinity of the newly produced ice is 0.5% mass percent (m/m) due to ion inclusions, which is within the salinity limits of fresh water. This study demonstrates a sensitive method of detecting salt trapped inside the ice in the form of crystallites and provides a valuable insight to improve freeze desalination efficiency from a molecular perspective.
A Novel Failure Mode and Effects Analysis Method Based on Fuzzy Evidential Reasoning Rules

Failure mode and effects analysis (FMEA) is an effective reliability analysis technique and has been used for safety and dependability analysis in a wide range of fields. In the traditional FMEA, a method called risk priority number (RPN) has been widely used to determine the risk levels of failure modes. However, the method is deficient in dealing with imprecise data. To overcome that shortcoming, we propose a novel method based on fuzzy evidential reasoning rules to study the risk evaluation of failure modes in an uncertainty evaluation environment. The main contributions of this work are twofold: First, by analyzing the classical risk priority number method, we extract the reasoning knowledge from RPN method to construct fuzzy evidential reasoning rules for risk evaluation based on virtue of Dempster-Shafer evidence theory and fuzzy set theory; Second, the initial risk assessment is modeled with fuzzy form based on basic probability assignment (BPA) and fuzzy number, which can perfectly reflect the uncertainties in practice. The approach establishes a new reasoning model for fuzzy risk evaluation in FMEA. Finally, an example for risk evaluation of failure modes during general anesthesia process is given to illustrate the effectiveness of the proposed method.
Establishing quality control in UK wildflower seed production

practice operates (Flora Locale, 2001). In contrast, little work seems to have been done to establish the fundamental requirement for germination testing to determine the planting value of wildflower seeds, and there are neither regulatory levels nor industry standards. Seed is generally traded without germination or purity test results being available. For some species, the conditions for germination testing are quite straightforward, and a few of the species have germination conditions described in the ISTA Rules, e.g. Leucanthemum vulgare (ISTA, 2006). However, these have been developed mainly for cultivated material, and wild populations do not always behave in the same way. A major factor inhibiting the development of germination testing amongst producers, traders and users of wildflower seeds is the presence and range of types of dormancy found in native populations (Baskin and Baskin, 2001), which has inhibited the adoption of routine testing. Dormancy affects wildflower seeds in field and nursery conditions as well as laboratory testing, and in cases of seed failure, the lack of established testing methods often leads to the acceptance that, as the seed quality and behaviour is unknown, the cause just range from meadow species (including native grasses) to heath and wetland plants and woodland species, and cover a wide range of families and plant types. Despite the increase in commercial production, in the UK, the trade remains largely unregulated. Agricultural seed legislation, in the form of the Fodder Seeds Regulations (HMSO, 1993), coincidentally covers some native species which are also traded as ‘wild’ material (e.g. Lotus corniculatus L.), but the requirement for registered cultivars (tested for distinctness, uniformity and stability) means that natural populations cannot possibly conform to the varietal standards. Neither have the standards for purity and germination in these regulations been applied to wildflower seeds. A recent attempt has been made in England to amend the regulations to include wild material, but this applies to the origin of the seed and not to other quality factors. There has been considerable debate over the last twenty years about the importance of origin (or provenance) of the material of native species, especially as much of the seed has been imported to the UK from other European countries. Even here there is no regulation, but a voluntary code of Establishing quality control in UK wildflower seed production
Brownian Thermometry Beyond Equilibrium

Since Albert Einstein's seminal 1905-paper on Brownian motion, the temperature of fluids and gases of known viscosity can be deduced from observations of the fluctuations of small suspended probe particles. We summarize recent generalizations of this standard technique of Brownian thermometry to situations involving spatially heterogeneous temperature fields and other non-equilibrium conditions in the solvent medium. The notion of effective temperatures is reviewed and its scope critically assessed. Our emphasis is on practically relevant real-world applications, for which effective temperatures have been explicitly computed and experimentally confirmed. We also elucidate the relation to the more general concept of (effective) temperature spectra and their measurement by Brownian thermospectrometry. Finally, we highlight the conceptual importance of non-equilibrium thermometry for active and biological matter, such as microswimmer suspensions or biological cells, which often play the role of non-thermal ('active') heat baths for embedded Brownian degrees of freedom.
Discovery of the Galactic High-mass Gamma-Ray Binary 4FGL J1405.1−6119

We report the identification from multiwavelength observations of the Fermi Large Area Telescope (LAT) source 4FGL J1405.1−6119 (=3FGL J1405.4−6119) as a high-mass gamma-ray binary. Observations with the LAT show that gamma-ray emission from the system is modulated at a period of 13.7135 ± 0.0019 days, with the presence of two maxima per orbit with different spectral properties. X-ray observations using the Neil Gehrels Swift Observatory X-ray Telescope show that X-ray emission is also modulated at this period, but with a single maximum that is closer to the secondary lower-energy gamma-ray maximum. A radio source, coincident with the X-ray source is also found from Australia Telescope Compact Array observations, and the radio emission is modulated on the gamma-ray period with similar phasing to the X-ray emission. A large degree of interstellar obscuration severely hampers optical observations, but a near-infrared counterpart is found. Near-infrared spectroscopy indicates an O6 III spectral classification. This is the third gamma-ray binary to be discovered with the Fermi-LAT from periodic modulation of the gamma-ray emission, the other two sources also have early O star, rather than Be star, counterparts. We consider at what distances we can detect such modulated gamma-ray emission with the LAT, and examine constraints on the gamma-ray binary population of the Milky Way.
Dust production in the debris disk around HR 4796 A

Context. Debris disks are the natural by-products of the planet formation process. Scattered or polarized light observations are mostly sensitive to small dust grains that are released from the grinding down of bigger planetesimals. Aims. High angular resolution observations at optical wavelengths can provide key constraints on the radial and azimuthal distribution of the small dust grains. These constraints can help us better understand where most of the dust grains are released upon collisions. Methods. We present SPHERE/ZIMPOL observations of the debris disk around HR 4796 A, and we modeled the radial profiles along several azimuthal angles of the disk with a code that accounts for the effect of stellar radiation pressure. This enabled us to derive an appropriate description for the radial and azimuthal distribution of the small dust grains. Results. Even though we only modeled the radial profiles along, or close to, the semi-major axis of the disk, our best-fit model is not only in good agreement with our observations but also with previously published datasets (from near-infrared to sub-mm wavelengths). We find that the reference radius is located at 76.4 ± 0.4 au, and the disk has an eccentricity of 0.076−0.010+0.016 with the pericenter located on the front side of the disk (north of the star). We find that small dust grains must be preferentially released near the pericenter to explain the observed brightness asymmetry. Conclusions. Even though parent bodies spend more time near the apocenter, the brightness asymmetry implies that collisions happen more frequently near the pericenter of the disk. Our model can successfully reproduce the shape of the outer edge of the disk without requiring an outer planet shaping the debris disk. With a simple treatment for the effect of the radiation pressure, we conclude that the parent planetesimals are located in a narrow ring of about 3.6 au in width.
ProgressiveDB - Progressive Data Analytics as a Middleware

ProgressiveDB transforms any standard SQL database into a progressive database capable of continuous, approximate query processing. It introduces a few small extensions to the SQL query language that allow clients to express progressive analytical queries. These extensions are processed in the ProgressiveDB middleware that sits between a database application and the underlying database providing interactive query processing as well as query steering capabilities to the user. In our demo, we show how this system allows a database application with a graphical user interface to interact with different backends, while providing the user with immediate feedback during exploratory data exploration of an on-time flight database. ProgressiveDB also supports efficient query steering by providing a new technique, called progressive views, which allows the intermediate results of one progressive query to be shared and reused by multiple concurrent progressive queries with refined scope. PVLDB Reference Format: Lukas Berg, Tobias Ziegler, Carsten Binnig and Uwe Röhm. ProgressiveDB – Progressive Data Analytics as a Middleware. PVLDB, 12(12): 1814-1817, 2019. DOI: https://doi.org/10.14778/3352063.3352073
Quantification of T-Cell and B-Cell Replication History in Aging, Immunodeficiency, and Newborn Screening

Quantification of T-cell receptor excision circles (TRECs) has impacted on human T-cell research, but interpretations on T-cell replication have been limited due to the lack of a genomic coding joint. We here overcome this limitation with multiplex TRG rearrangement quantification (detecting ~0.98 alleles per TCRαβ+ T cell) and the HSB-2 cell line with a retrovirally introduced TREC construct. We uncovered <5 cell divisions in naive and >10 cell divisions in effector memory T-cell subsets. Furthermore, we show that TREC dilution with age in healthy adults results mainly from increased T cell replication history. This proliferation was significantly increased in patients with predominantly antibody deficiency. Finally, Guthrie cards of neonates with Down syndrome have fewer T and B cells than controls, with similar T-cell and slightly higher B-cell replication. Thus, combined analysis of TRG coding joints and TREC signal joints can be utilized to quantify in vivo T-cell replication, and has direct applications for research into aging, immunodeficiency, and newborn screening.
DPSAaS: Multi-Dimensional Data Sharing and Analytics as Services under Local Differential Privacy

Differential privacy has emerged as the de facto standard for privacy deﬁnitions, and been used by, e.g. , Apple, Google, Uber, and Microsoft, to collect sensitive information about users and to build privacy-preserving analytics engines. However, most of such advanced privacy-protection techniques are not accessible to mid-size companies and app developers in the cloud. We demonstrate a lightweight middleware DPSAaS , which provides d ifferentially p rivate data-s haring-and-a nalytics functionality a s cloud s ervices. We focus on multi-dimensional analytical (MDA) queries under local differential privacy (LDP) in this demo. MDA queries against a fact table have predicates on (categorical or ordinal) dimensions and aggregate one or more measures. In the absence of a trusted agent, sensitive dimensions and measures are encoded in a privacy-preserving way locally using our LDP data sharing service, before being sent to the data collector. The data collector estimates the answers to MDA queries from the encoded data, using our data analytics service. We will highlight the design decisions of DPSAaS and twists made to LDA algorithms to ﬁt the design, in order to smoothly connect DPSAaS to the data processing platform and analytics engines, and to facilitate efﬁcient large-scale processing. PVLDB
Comprehensive Analysis of Alzheimer’s Disease Biologically Candidate Causal Genes Revealed by Function Association Study With GWAS

Although genome-wide association studies (GWAS) have successfully identified many risk loci associated with Alzheimer’s disease (AD), the dispute about missing heritability and weak interpretability must be resolved to reveal the causal genes in the risk loci and explain the mechanism of AD. The aim of this study was to overcome the problems that involve moving from the risk loci to causal genes and to understand the genotype-to-phenotype relationship of AD. We integrated the prediction results from different methods (e.g., DAPPLE, DEPICT, Prix Fixe, etc.) based on GWAS data combining protein-protein interaction networks, gene functions, co-function networks or expression quantitative trait loci data. A total of 43 plausible causal genes of AD were identified, including eight high-confidence AD causal genes (BIN1, CR1, CLU, HMHA1, MS4A4A, MS4A6A, PICALM and PVR). Then the landscape of these 43 causal genes was generated. Gene Ontology analysis showed that these identified causal genes were enriched in lipid/lipoprotein-related complexes and processes, supporting that lipid/lipoprotein homeostasis has a critical role in AD. The distinct spatial-temporal expression patterns of these causal genes illustrated that they played diverse roles in different cell types and developmental stages. The top eight causal genes were dysregulated in AD cases compared with their expression in normal controls, indicating that these genes are important in the pathophysiology of AD. Results from our study could provide meaningful clues for understanding AD pathogenesis. Together, further functional validation of the causal genes of AD will help identify potential targets for AD therapy.
Conversion of rainforest to oil palm and rubber plantations alters energy channels in soil food webs

Abstract In the last decades, lowland tropical rainforest has been converted in large into plantation systems. Despite the evident changes above ground, the effect of rainforest conversion on the channeling of energy in soil food webs was not studied. Here, we investigated community‐level neutral lipid fatty acid profiles in dominant soil fauna to track energy channels in rainforest, rubber, and oil palm plantations in Sumatra, Indonesia. Abundant macrofauna including Araneae, Chilopoda, and Diplopoda contained high amounts of plant and fungal biomarker fatty acids (FAs). Lumbricina had the lowest amount of plant, but the highest amount of animal‐synthesized C20 polyunsaturated FAs as compared to other soil taxa. Mesofauna detritivores (Collembola and Oribatida) contained high amounts of algal biomarker FAs. The differences in FA profiles between taxa were evident if data were analyzed across land‐use systems, suggesting that soil fauna of different size (macro‐ and mesofauna) are associated with different energy channels. Despite that, rainforest conversion changed the biomarker FA composition of soil fauna at the community level. Conversion of rainforest into oil palm plantations enhanced the plant energy channel in soil food webs and reduced the bacterial energy channel; conversion into rubber plantations reduced the AMF‐based energy channel. The changes in energy distribution within soil food webs may have significant implications for the functioning of tropical ecosystems and their response to environmental changes. At present, these responses are hard to predict considering the poor knowledge on structure and functioning of tropical soil food webs.
IHCS: An Integrated Hybrid Cleaning System

Data cleaning is a prerequisite to subsequent data analysis, and is know to often be time-consuming and labor-intensive. We present IHCS, a hybrid data cleaning system that integrates error detection and repair to contend effectively with multiple error types. In a preprocessing step that precedes the data cleaning, IHCS formats an input dataset to be cleaned, and transforms applicable data quality rules into a unified format. Then, an MLN index structure is formed according to the unified rules, enabling IHCS to handle multiple error types simultaneously. During the cleaning, IHCS first tackles abnormalities through an abnormal group process, and then, it generates multiple data versions based on the MLN index. Finally, IHCS eliminates conflicting values across the multiple versions, and derives the final unified clean data. A visual interface enables cleaning process monitoring and cleaning result analysis. PVLDB Reference Format: Congcong Ge, Yunjun Gao, Xiaoye Miao, Lu Chen, Christian S. Jensen, Ziyuan Zhu. IHCS: An Integrated Hybrid Cleaning System. PVLDB, 12(12): 1874-1877, 2019. DOI: https://doi.org/10.14778/3352063.3352088
Neutron-capture elements in dwarf galaxies

Context. We present a large homogeneous set of stellar parameters and abundances across a broad range of metallicities, involving 13 classical dwarf spheroidal (dSph) and ultra-faint dSph (UFD) galaxies. In total, this study includes 380 stars in Fornax, Sagittarius, Sculptor, Sextans, Carina, Ursa Minor, Draco, Reticulum II, Bootes I, Ursa Major II, Leo I, Segue I, and Triangulum II. This sample represents the largest, homogeneous, high-resolution study of dSph galaxies to date. Aims. With our homogeneously derived catalog, we are able to search for similar and deviating trends across different galaxies. We investigate the mass dependence of the individual systems on the production of α-elements, but also try to shed light on the long-standing puzzle of the dominant production site of r-process elements. Methods. We used data from the Keck observatory archive and the ESO reduced archive to reanalyze stars from these 13 classical dSph and UFD galaxies. We automatized the step of obtaining stellar parameters, but ran a full spectrum synthesis (1D, local thermal equilibrium) to derive all abundances except for iron to which we applied nonlocal thermodynamic equilibrium corrections where possible. Results. The homogenized set of abundances yielded the unique possibility of deriving a relation between the onset of type Ia supernovae and the stellar mass of the galaxy. Furthermore, we derived a formula to estimate the evolution of α-elements. This reveals a universal relation of these systems across a large range in mass. Finally, we show that between stellar masses of 2.1 × 107 M⊙ and 2.9 × 105 M⊙, there is no dependence of the production of heavy r-process elements on the stellar mass of the galaxy. Conclusions. Placing all abundances consistently on the same scale is crucial to answering questions about the chemical history of galaxies. By homogeneously analyzing Ba and Eu in the 13 systems, we have traced the onset of the s-process and found it to increase with metallicity as a function of the galaxy’s stellar mass. Moreover, the r-process material correlates with the α-elements indicating some coproduction of these, which in turn would point toward rare core-collapse supernovae rather than binary neutron star mergers as a host for the r-process at low [Fe/H] in the investigated dSph systems.
A new record of enumeration of regular graphs by parallel processing

We broke a record, set 8 years ago, in the enumeration of non-isomorphic regular graphs by expanding the sequence of A006820 in OEIS, to achieve the number for 4-regular graphs of order 23 as 429,668,180,677,439, while discovering serval optimal regular graphs with minimum diameters. The number of 4-regular graphs and the optimal graphs, extremely time-consuming to calculate, result from a method we adapt from GENREG, a classical regular graph generator, to fit for supercomputers' strengths of using thousands of processor cores.