Miracle-dz/UniFAR-FTUs huggingface dataset:
Computationally efficient framework for diagnosing, understanding and predicting biphasic population growth

Throughout the life sciences, biological populations undergo multiple phases of growth, often referred to as biphasic growth for the commonly-encountered situation involving two phases. Biphasic population growth occurs over a massive range of spatial and temporal scales, ranging from microscopic growth of tumours over several days, to decades-long re-growth of corals in coral reefs that can extend for hundreds of kilometres. Different mathematical models and statistical methods are used to diagnose, understand, and predict biphasic growth. Common approaches can lead to inaccurate predictions of future growth that may result in inappropriate management and intervention strategies being implemented. Here we develop a very general computationally efficient framework, based on profile likelihood analysis, for diagnosing, understanding, and predicting biphasic population growth. The two key components of the framework are: (i) an efficient method to form approximate confidence intervals for the change point of the growth dynamics and model parameters; and, (ii) parameter-wise profile predictions that systematically reveal the influence of individual model parameters on predictions. To illustrate our framework we explore real-world case studies across the life sciences.
Beta human papillomavirus 8E6 promotes alternative end joining

Double strand breaks (DSBs) are one of the most lethal DNA lesions in cells. Previous studies show that the E6 protein of beta-human papillomavirus (HPV8 E6) impairs two major DSB repair pathways homologous recombination (HR) and non-homologous end-joining (NHEJ). However, HPV8 E6 delays but does not eliminate DSB repair capability of cells. How DSBs are repaired in cells with HPV8 E6 remains to be studied. We hypothesis that HPV8 E6 promotes a backup DSB repair pathway, alternative end-joining (Alt-EJ). Using CAS9 based Alt-EJ reporters, we show that HPV8 E6 promotes Alt-EJ. Further, using small molecule inhibitors, CRISPR/CAS9 gene knockout, and HPV8 E6 mutant, we find that HPV8 E6 promotes Alt-EJ by binding p300, an acetyltransferase that facilitates DSB repair by HR and NHEJ. Finally, we analyzed whole genome sequencing data from genomes of human foreskin keratinocytes expressing HPV8 E6 and found they displayed an increased frequency of deletions bearing the microhomology signatures of Alt-EJ. This study fills the knowledge gap how DSB is repaired in cells with HPV8 E6 and the mutagenic consequences of HPV8 E6 mediated p300 destabilization. Broadly, this study supports the hypothesis that beta-HPV promotes cancer formation by increasing genomic instability.
The polygon representation of flat three-dimensional space times

An important set of solutions of 2 + 1 dimensional gravity consists of spacetimes which contain an open neighborhood which admits a slicing 'Bg,N,b x (0,1) in a family of genus 9 Riemann surfaces with N punctures and b asymptotic regions. We define a set of polygons ll', an equivalence relation R, and a bijective map from ll'IR to this set of spacetimes. The construction of a spacetime froIn the corresponding polygon leads to a natural extension beyond singular surfaces. We discuss the existence of a global spacelike foliation, and generalizo to de Silter manifolds, or 2 + l-dimensional gravity with a cosmological constan! RESUMEN. Un conjunto importante de soluciones de las ecuaciones de Einstein en 2+ 1 dimensiones es el de los espacio-tiempos que contienen una vecindad abierta que admite una foliación Lg,N,b x (0,1) en una familia de superficies de gen". 9 con N punturas (partículas) y b fronteras, o regiones asint6ticamente planas. Definimos un conjunto de polígonos Ir, una relación de equivalencia R y una biyección de ll'IR sobre el conjunto de soluciones. La construcción del espacio-tiempo a partir del polígono correspondiente lleva a nna extensión natural de las soluciones más allá de las superficies singulares. Consideramos la existencia de una foliación global regular y generalizamos a soluciones del tipo de Sitter, que corresponden a la gravedad en 2 + 1 dimensiones con constante cosmológica. PAes: 02.40. +m; 03.20. +i; 04.20. -q
Electricity-free nucleic acid extraction method from dried blood spots on filter paper for point-of-care diagnostics

Background Nucleic acid extraction is a crucial step for molecular biology applications, being a determinant for any diagnostic test procedure. Dried blood spots (DBS) have been used for decades for serology, drug monitoring, environmental investigations, and molecular studies. Nevertheless, nucleic acid extraction from DBS remains one of the main challenges to translate them to the point-of-care (POC). Method We have developed a fast nucleic acid extraction (NAE) method from DBS which is electricity-free and relies on cellulose filter papers (DBSFP). The performance of NAE was assessed with loop-mediated isothermal amplification (LAMP), targeting the human reference gene beta-actin. The developed method was evaluated against FTA cards and magnetic bead-based purification, using time-to-positive (min) for comparative analysis. We optimised and validated the developed method for elution (eluted disk) and disk directly in the reaction (in-situ disk), RNA and DNA detection, and whole blood stored in anticoagulants (K2EDTA and lithium heparin). Furthermore, the compatibility of DBSFP with colourimetric detection was studied to show the transferability to the POC. Results The proposed DBSFP is based on grade 3 filter paper pre-treated with 8% (v/v) igepal surfactant, 1 min washing step with PBS 1X and elution in TE 1X buffer after 5 min incubation at room temperature, enabling NAE under 7 min. Obtained results were comparable to gold standard methods across tested matrices, targets and experimental conditions, demonstrating the versatility of the methodology. Lastly, eluted disk colourimetric detection was achieved with a sample-to-result turnaround time under 35 min. Conclusions The developed method is a fast, electricity-free, and low-cost solution for NAE from DBSFP enabling molecular testing in virtually any POC setting.
Workload-Aware Query Recommendation Using Deep Learning

Users interact with databases by writing sequences of SQL queries that are are often stored in query workloads. Current SQL query recommendation approaches make little use of query workloads. Our work presents a novel workload-aware approach to query recommendation. We use deep learning prediction models trained on query pairs extracted from large-scale query workloads to build our approach. Our algorithms suggest contextual (query fragments) and structural (query templates) information to aid users in formulating their next query. We evaluate our algorithms on two real-world datasets: the Sloan Digital Sky Survey (SDSS) and SQLShare. We perform a thorough analysis of the workloads and then empirically show that our workload-aware, deep-learning approach vastly outperforms known collaborative filtering approaches.
Parametric estimation of sparse channels - theory and applications

The use of parametric methods for the estimation of communication channels requires a diverse suite of components : models, algorithms (for estimation and detection) and analytical tools (error bounds, time-frequency uncertainty limits,. . . ). The coherent study of each one of them is the goal of this thesis. In the first part, we propose a parametric model, the sparse common support model, and study under which conditions it can be used to describe communication channels. We then extend classical subspace estimation methods to work on this model, and propose a fast estimation algorithm having a superlinear complexity and a linear memory footprint with respect to the number of measurements. For comparison, a direct implementation has a cubic complexity and a quadratic memory footprint. Parametric estimation can only be relevant if it is wisely used, i.e. if the right model is first selected. This task is called detection, and we outline two procedures to complete it. The first one uses the statistical properties of the noise and is therefore powerful but sensitive to model mismatches. A second detection method is based on the low dimensionality of the model, and uses a convexification of the rank of a matrix, called the effective rank, to determine the intrinsic dimension of the model. The first part is concluded with comparative tests on measured channel impulse responses (with added noise), which shows the proposed model and algorithms improve channel estimation at low signal to noise ratio (SNR). In the second part, we study the localization on periodic domains, which is necessary to analyze the performance of periodic parameters estimation. First, we will construct periodic waveforms which have a minimal time-frequency product. These periodic waveforms — obtained from Mathieu functions — play a role similar to Gaussian functions with respect to the Heisenberg uncertainty principle. A fundamental difference is that in the periodic case, the Heisenberg limit is only achieved by (infinitely) narrow periodic waveforms, and thus, the maximally compact waveforms we construct provide the achievable lowerbound for any given width. Then, we show that lowerbounds on the variance of estimators such as the CramérRao bound (CRB), and its siblings (the CRB family), can be expressed in a form equivalent to the Heisenberg uncertainty principle. From this similarity, we build periodic lowerbounds (the periodic CRB, the periodic Hammersley-Chapman-Robbins bound,. . . ) with minimal efforts. Finally, we obtain an explicit analytical formula for the Barankin bound on a single periodic parameter and observe that this bound is not necessarily tight despite the fact that it is the strongest that can be obtained in the CRB family.
Efficient Maintenance of Agree-Sets Against Dynamic Datasets

Constraint discovery is a fundamental task in data profiling, which involves identifying the dependencies that are satisfied by a dataset. As published datasets are increasingly dynamic, a number of researchers have begun to investigate the problem of dependencies’ discovery in dynamic datasets. Proposals this far in this area can be viewed as schema-based in the sense that they model and explore the solution space using a lattice built on the basis of the attributes (columns) of the dataset. It is recognized that proposals that belong to this class, like their static counterpart, tend to perform well for datasets with a large number of tuples but a small number of attributes. The second class of proposals that have been examined for static datasets (but not in dynamic settings) is data-driven and is known to perform well for datasets with a large number of attributes and a small number of tuples. The main bottleneck of this class of solutions is the generation of agree-sets, which involves pairwise comparison of the tuples in the dataset. We present in this paper DynASt , a system for the efficient maintenance of agree-sets in dynamic datasets. We investigate the performance of DynASt and its scalability in terms of the number of tuples and the number of attributes of the target dataset. We also show that it outperforms existing (static and dynamic) state-of-the-art solutions for datasets with a large number of attributes.
Eﬀects of Treatment on the Treated: Identiﬁcation and Generalization

Many applications of causal analysis call for assessing, retrospectively, the eﬀect of with-holding an action that has in fact been im-plemented. This counterfactual quantity, sometimes called “eﬀect of treatment on the treated,” (ETT) have been used to to evaluate educational programs, critic public poli-cies, and justify individual decision making. In this paper we explore the conditions under which ETT can be estimated from (i.e., identiﬁed in) experimental and/or observational studies. We show that, when the action in-vokes a singleton variable, the conditions for ETT identiﬁcation have simple characteriza-tions in terms of causal diagrams. We further give a graphical characterization of the conditions under which the eﬀects of multiple treatments on the treated can be identiﬁed, as well as ways in which the ETT estimand can be constructed from both interventional and observational distributions.
Joint Source and Schema Evolution: Insights from a Study of 195 FOSS Projects

In this paper, we address the problem of the co-evolution of Free Open Source Software projects with the relational schemata that they encompass. We exploit a data set of 195 publicly available schema histories of FOSS projects hosted in Github, for which we locally cloned their respective project and measured their evolution progress. Our first research question asks which percentage of the projects demonstrates a “hand-in-hand” schema and source code co-evolution? To address this question, we defined synchronicity by allowing a bounded amount of lag between the cumulative evolution of the schema and the entire project. A core finding is that there are all kinds of behaviors with respect to project and schema co-evolution, resulting in only a small number of projects where the evolution of schema and project progress in sync. Moreover, we discovered that after exceeding a 5-year threshold of project life, schemata gravitate to lower rates of evolution, which practically means that, with time, the schemata stop evolving as actively as they originally did. To answer a second question, on whether evolution comes early in the life of a schema, we measured how often does the cumulative progress of schema evolution exceed the respective progress of source change, as well as the respective progress of time. The results indicate that a large majority of schemata demonstrates early advance of schema change with respect to code evolution, and, an even larger majority is also demonstrating an advance of schema evolution with respect to time, too. Third, we asked at which time point in their lives do schemata attain a substantial
A Method for Custom Movement Generation in Wireless Mobile Network Simulation

—Random motion is often used in evaluating performance of Mobile Ad hoc Networks (MANETs). Mobility pattern of nodes significantly affects performance of MANETs. In the simulation of large mobile networks, automated movement generators are used, such as the setdest utility in ns2. In this paper, we investigate the modifications to the standard setdest generator that specifies the motions along straight-line paths. We propose and implement a new method for movement generation for the ns2 simulator that specifies the node movements along curved paths generated using simple fractals. The new generator was successfully tested with the ns2 simulator. The results show that, in the random way point motion, only the node speed significantly affects MANET performance, and not the shape of the individual path segments taken by a node.
Web-Based Supplementary Materials for “New Methods for Treatment Eﬀect Calibration, with Applications to Non-Inferiority Trials”

for Treatment Effect Calibration, with Applications to Non-Inferiority Trials” Zhiwei Zhang, Lei Nie, Guoxing Soon and Zonghui Hu Division of Biostatistics, Office of Surveillance and Biometrics, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA Division of Biometrics V, Office of Biostatistics, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA Division of Biometrics IV, Office of Biostatistics, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA Biostatistics Research Branch, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, Maryland, USA
Cosmic Ray Cradles in the Galaxy Cosmic Ray Cradles in the Galaxy

The search for the origin of high-energy cosmic rays has made significant progress in the past decade. By including multi-messenger methods, the general picture of the presence of a galactic component at low energies and an extragalactic one at the highest energies has been strengthened. Yet, unambiguous proof of the exact origins of cosmic rays is still missing. This chapter will review localized regions in the galaxy, which, due to their high nonthermal emission, are likely cosmic ray cradles. What we can learn from combining theoretical modeling with multi-messenger observations of regions like the Cygnus X complex, the Eta Carinae, and the Galactic Center region will be discussed. How the investigation of such localized regions in the Milky Way will help to resolve the more than 100-year-old question: what is the origin of cosmic rays? will be reviewed.
Influence of the domestic COVID-19 pandemic on the pediatric emergency department

Objectives After the coronavirus disease 2019 (COVID-19) pandemic emerged, there has been a substantial decline in emergency department (ED) visits. However, the impact of the pandemic on pediatric ED (PED) visits has not been well discussed. This study aimed to compare the epidemiology and clinical characteristics of PED visits before and after the time of the COVID-19 outbreak. Methods Data of pediatric patients admitted to the PED between February 2019 and January 2021 were retrospectively collected. All patients were divided into two groups: 1 year before the COVID-19 pandemic (group 1) and 1 year after the COVID-19 outbreak (group 2). Basic demographics, clinical characteristics, triage levels, categories of diagnosis at PED, disposition, and hospitalization rates (wards and intensive care units) were further analyzed and compared between the two groups. Results During the study period, 48,146 pediatric patients were enrolled (30,823 in group 1, and 17,323 in group 2). PED visits represented a 43.8% annual decline. The most common diseases in the PED in group 1 were infectious diseases, whereas digestive system diseases were the most common diseases in group 2 (both P < 0.001). In group 2, shorter PED observational time, longer hospital stay, and higher admission rates were noted compared to those in group 1 (all P < 0.001). Conclusion During the COVID-19 pandemic, the proportion of respiratory system diseases and infectious diseases sharply decreased in the PED, whereas the proportion of digestive system diseases relatively increased. The COVID-19 pandemic has impacted the nature of PED visits and we should pay more attention on digestive system diseases and the rates of out-of-hospital cardiac arrest and overall mortality.
Genome-wide identification and functional analysis of cupin_1 domain-containing members involved in the responses to Sclerotinia sclerotiorum and abiotic stress in Brassica napus

Cupin_1 domain-containing proteins (CDPs) are ubiquitously present in higher plants, which are known to play essential roles in various biological processes. In this study, we carried out genome-wide characterization and systematic investigation of the CDP genes in Brassica napus. A total of 96 BnCDPs, including 71 germin-like proteins (GLPs; proteins with a single cupin_1 domain) and 25 CDP bicupins (proteins with two cupin_1 domains), were identified and clustered into six distinct subfamilies (I–VI) based on the phylogenic analysis, gene structure and motif distribution. Further analysis indicated that whole-genome duplication (WGD) and segmental duplication are main contributors to the species-specific expansion of the BnCDP gene family, and all the duplicated genes subsequently underwent strong purification selection. The promoter region of BnCDPs showed enrichment of cis-regulatory elements associated with development, hormone and stress, as well as transcription factor binding sites, which validates the prediction that BnCDPs are widely involved in plant growth and biotic and abiotic stress responses. The BnCDPs in different subfamilies exhibited obvious differences in expression among 30 developmental tissues/stages of B. napus, implying that BnCDPs may be involved in tissue- and stage-specific developmental processes. Similar trends in expression of most BnCDPs were observed under Sclerotinia sclerotiorum inoculation and four abiotic stresses (dehydration, cold, ABA and salinity), particularly the BnGLPs in subfamily I and III with single cupin_1 domain, revealing that BnCDPs are of great importance in the environmental adaption of B. napus. We then performed a genome-wide association study (GWAS) of 274 B. napus core germplasms on S. sclerotiorum resistance and identified four significantly associated loci harboring five BnGLPs. The expression levels of two candidate genes, BnGLP1.A08 and BnGLP1.C08, were significantly correlated with S. sclerotiorum resistance. Their functional responses to multiple stages of S. sclerotiorum inoculation and four abiotic stresses were further examined through qPCR. Overall, this study provides rich resources for research on the function and evolutionary playground of CDP genes.
Altered functional connectivity of cerebellar dentate nucleus in peak-dose dyskinesia in Parkinson’s disease

The cerebellum is associated with the emergence of levodopa-induced dyskinesia (LID) in Parkinson’s disease (PD), yet the neural mechanism remains obscure. Our aim was to ascertain the role of functional connectivity (FC) patterns of the cerebellar dentate nucleus (DN) in the pathogenesis of peak-dose dyskinesia in PD. Twenty-three peak-dose dyskinetic PD patients, 27 non-dyskinetic PD patients, and 36 healthy controls (HCs) were enrolled and underwent T1-weighted and resting-state functional magnetic resonance imaging (rs-fMRI) scans after dopaminergic medication intake. We selected left and right DN as the regions of interest and then employed voxel-wise FC analysis and voxel-based morphometry analysis (VBM). The correlations between the altered FC pattern and clinical scores were also examined. Finally, receiver operating characteristic (ROC) curve analysis was performed to assess the potential of DN FC measures as a feature of peak-dose dyskinesia in PD. Dyskinetic PD patients showed excessively increased FC between the left DN and right putamen compared with the non-dyskinetic. When compared with controls, dyskinetic PD patients mainly exhibited increased FC between left DN and bilateral putamen, left paracentral lobule, right postcentral gyrus, and supplementary motor area. Additionally, non-dyskinetic PD patients displayed increased FC between left DN and left precentral gyrus and right paracentral lobule compared with controls. Meanwhile, increased FC between DN (left/right) and ipsilateral cerebellum lobule VIII was observed in both PD subgroups. However, no corresponding alteration in gray matter volume (GMV) was found. Further, a positive correlation between the z-FC values of left DN-right putamen and the Unified Dyskinesia Rating Scale (UDysRS) was confirmed in dyskinetic PD patients. Notably, ROC curve analyses revealed that the z-FC values of left DN-right putamen could be a potential neuroimaging feature identifying dyskinetic PD patients. Our findings demonstrated that the excessively strengthened connectivity of DN-putamen might contribute to the pathophysiological mechanisms of peak-dose dyskinesia in PD.