Miracle-dz/UniFAR-FTUs huggingface dataset:
The Optimal Machine Learning-Based Missing Data Imputation for the Cox Proportional Hazard Model

An adequate imputation of missing data would significantly preserve the statistical power and avoid erroneous conclusions. In the era of big data, machine learning is a great tool to infer the missing values. The root means square error (RMSE) and the proportion of falsely classified entries (PFC) are two standard statistics to evaluate imputation accuracy. However, the Cox proportional hazards model using various types requires deliberate study, and the validity under different missing mechanisms is unknown. In this research, we propose supervised and unsupervised imputations and examine four machine learning-based imputation strategies. We conducted a simulation study under various scenarios with several parameters, such as sample size, missing rate, and different missing mechanisms. The results revealed the type-I errors according to different imputation techniques in the survival data. The simulation results show that the non-parametric “missForest” based on the unsupervised imputation is the only robust method without inflated type-I errors under all missing mechanisms. In contrast, other methods are not valid to test when the missing pattern is informative. Statistical analysis, which is improperly conducted, with missing data may lead to erroneous conclusions. This research provides a clear guideline for a valid survival analysis using the Cox proportional hazard model with machine learning-based imputations.
Recognition Characteristics of Facial and Bodily Expressions: Evidence From ERPs

In the natural environment, facial and bodily expressions influence each other. Previous research has shown that bodily expressions significantly influence the perception of facial expressions. However, little is known about the cognitive processing of facial and bodily emotional expressions and its temporal characteristics. Therefore, this study presented facial and bodily expressions, both separately and together, to examine the electrophysiological mechanism of emotional recognition using event-related potential (ERP). Participants assessed the emotions of facial and bodily expressions that varied by valence (positive/negative) and consistency (matching/non-matching emotions). The results showed that bodily expressions induced a more positive P1 component and a shortened latency, whereas facial expressions triggered a more negative N170 and prolonged latency. Among N2 and P3, N2 was more sensitive to inconsistent emotional information and P3 was more sensitive to consistent emotional information. The cognitive processing of facial and bodily expressions had distinctive integrating features, with the interaction occurring in the early stage (N170). The results of the study highlight the importance of facial and bodily expressions in the cognitive processing of emotion recognition.
The Toll Route to Structural Brain Plasticity

The human brain can change throughout life as we learn, adapt and age. A balance between structural brain plasticity and homeostasis characterizes the healthy brain, and the breakdown of this balance accompanies brain tumors, psychiatric disorders, and neurodegenerative diseases. However, the link between circuit modifications, brain function, and behavior remains unclear. Importantly, the underlying molecular mechanisms are starting to be uncovered. The fruit-fly Drosophila is a very powerful model organism to discover molecular mechanisms and test them in vivo. There is abundant evidence that the Drosophila brain is plastic, and here we travel from the pioneering discoveries to recent findings and progress on molecular mechanisms. We pause on the recent discovery that, in the Drosophila central nervous system, Toll receptors—which bind neurotrophin ligands—regulate structural plasticity during development and in the adult brain. Through their topographic distribution across distinct brain modules and their ability to switch between alternative signaling outcomes, Tolls can enable the brain to translate experience into structural change. Intriguing similarities between Toll and mammalian Toll-like receptor function could reveal a further involvement in structural plasticity, degeneration, and disease in the human brain.
First Fossil Fokienia (Cupressaceae) in South China and Its Palaeogeographic and Palaeoecological Implications

Fokienia A. Henry & H. H. Thomas is a monotypic genus of the Cupressoideae Rich. ex Sweet (Cupressaceae), native to subtropical evergreen mesophytic forests in South China, northern Laos and Vietnam. The fossil record of Fokienia is very scanty, with only one known occurrence of foliage in the Oligocene of Longjing, Jilin, China. Here we report the fossil foliage of Fokienia discovered in the Miocene Erzitang Formation of the Guiping Basin, South China, which is similar to that of the only extant species Fokienia hodginsii in both macromorphological and epidermal features. This species is the earliest fossil record within the modern distribution area of Fokienia and the only fossil species for which morphology and anatomy have been studied in detail. Fossil evidence suggests that the genus Fokienia was present at middle latitudes of the Northern Hemisphere in the Oligocene and spread to South China during the Miocene. Due to physiological adaptations to warm-wet environments and weak cold tolerance, Fokienia migrated southward, as global climate cooling gradually drove it to extinction in the mid-latitudes. The ecological niche of the extant species, and co-existing plant fossils, suggest that the fossil assemblage represents the remains of an evergreen broad-leaved and conifer mixed forest growing under humid and warm Miocene climate.
Crowding Effects on the Structure and Dynamics of the Intrinsically Disordered Nuclear Chromatin Protein NUPR1

The intracellular environment is crowded with macromolecules, including sugars, proteins and nucleic acids. In the cytoplasm, crowding effects are capable of excluding up to 40% of the volume available to any macromolecule when compared to dilute conditions. NUPR1 is an intrinsically disordered protein (IDP) involved in cell-cycle regulation, stress-cell response, apoptosis processes, DNA binding and repair, chromatin remodeling and transcription. Simulations of molecular crowding predict that IDPs can adopt compact states, as well as more extended conformations under crowding conditions. In this work, we analyzed the conformation and dynamics of NUPR1 in the presence of two synthetic polymers, Ficoll-70 and Dextran-40, which mimic crowding effects in the cells, at two different concentrations (50 and 150 mg/ml). The study was carried out by using a multi-spectroscopic approach, including: site-directed spin labelling electron paramagnetic resonance spectroscopy (SDSL-EPR), nuclear magnetic resonance spectroscopy (NMR), circular dichroism (CD), small angle X-ray scattering (SAXS) and dynamic light scattering (DLS). SDSL-EPR spectra of two spin-labelled mutants indicate that there was binding with the crowders and that the local dynamics of the C and N termini of NUPR1 were partially affected by the crowders. However, the overall disordered nature of NUPR1 did not change substantially in the presence of the crowders, as shown by circular dichroism CD and NMR, and further confirmed by EPR. The changes in the dynamics of the paramagnetic probes appear to be related to preferred local conformations and thus crowding agents partially affect some specific regions, further pinpointing that NUPR1 flexibility has a key physiological role in its activity.
Vertical transports of energy and trace gases at anchor stations and their spatial and temporal extrapolation under complex natural conditions

Improved knowledge on the atmosphere as part of the climate system, on regional weather as well as on effects of land use change and management requires better understanding of land-surface atmosphere interactions at different scales. The research project VERTIKO aimed at measuring and modelling vertical transports (momentum, energy, trace gases) in the atmospheric boundary layer as a spatial mean above inhomogeneous terrain. It questioned the appropriate spatial and temporal resolution to describe landsurface atmosphere interactions adequately. This was investigated for a specific target area in eastern Germany comprising 30,000 km2 from the Erzgebirge (Ore Mountains) to the Oder-Spree lake district (Figure 1). Continuous measurements and measurement campaigns were conducted at anchor stations of different land use types in the target area supplemented by data sets from external sites (test sites). Spatial integration is achieved by remote sensing (AVHRR, Landsat TM, Meteosat 6/7/8) in connection with a model hierarchy of SVAT/BGC models, a boundary-layer model and the mesoscale model (Lokalmodell) of the German Meteorological Service, DWD. Data on meteorological variables, measured 68 Theme Group 1.2: VERTIKO RESULTS
Beyond classroom walls: The role of a co-curricular English club in supporting second language learning

Second language learners of English in South Africa and beyond face challenges in acquiring the target language. In this paper, we report on a study during which we worked with an English Language Club set up as a co-curricular activity at a South African high school. We focus on one activity of the club that took place beyond the classroom walls to help learners improve their spelling. While the activities of the club were underpinned by critical pedagogy, we interpreted the findings of the study using Krashen's Affective Filter hypothesis. Using a critical paradigm, a qualitative approach, and an action research design, in this aspect of the study, as foregrounded in this paper, we aimed to answer the question of how learners' attitudes towards spelling may be changed by an activity outside the classroom. Our observations, fieldnotes, and reflections revealed that learners are able to transcend their fear of the language and increase their participation levels when they are in a relaxed learning environment that values their interests; this increased, in turn, their self-confidence. We argue for the use of alternative teaching methods to complement conventional teaching and learning.
Infection Yersinia pestis against Pulmonary IL-17 Contributes to Cell-Mediated Defense

Pneumonic plague is one of the world’s most deadly infectious diseases. The causative bacterium, Yersinia pestis , has the potential to be exploited as a biological weapon, and no vaccine is available. Vaccinating B cell-deﬁcient mice with D27-pLpxL, a live attenuated Y. pestis strain, induces cell-mediated protection against lethal pulmonary Y. pestis challenge. In this article, we demonstrate that prime/boost vaccination with D27-pLpxL confers better protection than prime-only vaccination. The improved survival does not result from enhanced bacterial clearance but is associated with increased levels of IL-17 mRNA and protein in the lungs of challenged mice. The boost also increases pulmonary numbers of IL-17–producing CD4 T cells. Interestingly, most of these cells simultaneously produce canonical type 1 and type 17 cytokines; most produce IL-17 and TNF- a , and many produce IL-17, TNF- a , and IFN- g . Neutralizing IL-17 counteracts the improved survival associated with prime/boost vaccination without signiﬁcantly impacting bacterial burden. Thus, IL-17 appears to mediate the enhanced protection conferred by booster immunization. Although neutralizing IL-17 signiﬁcantly reduces neutrophil recruitment to the lungs of mice challenged with Y. pestis , this impact is equally evident in mice that receive one or two immunizations with D27-pLpxL, suggesting it cannot sufﬁce to account for the improved survival that results from booster immunization. We conclude that IL-17 plays a yet to be identiﬁed role in host defense that enhances protection against pulmonary Y. pestis challenge, and we suggest that pneumonic plague vaccines should aim to induce mixed type 1 and type 17 cellular responses. The Journal of Immunology , 2011, 186: 1675–1684.
Analysis of electromagnetic NDE modelling using Stratton-Chu formulations based fast algorithm

The eddy current non-destructive evaluation (NDE) modelling using Stratton-Chu formulation-based fast algorithm is analysed. Stratton-Chu formulations, which have no low frequency breakdown issue, are selected for modelling electromagnetic NDE problems with low frequency and high conductivity approximations. As the main contribution of this article, the robustness and efficiency of the approximations, which result in big savings in both memory and CPU time, are validated and analysed using examples from practical EC testing. The boundary element method (BEM) is used to discretize the integral equations into a linear system of equations: the first order Rao-Wilton-Glisson (RWG) vector basis functions with the flat triangle meshes of the object and pulse basis functions are selected to expand the equivalent surface currents and the normal component of magnetic fields, respectively. Then the multilevel adaptive cross approximation (MLACA) algorithm is applied to accelerate the iterative solution process. The performance and efficiency of adaptively applying a multi-stage (level) algorithm based on the criteria concluded for the operators are shown.
Learning to Rank Model Performance and Review with Pairwise Transformations

Learning to rank is an application of machine learning that is finding increasing use in information retrieval systems. Various applications such as document retrieval, webpage ranking, sentiment analysis, and online advertising use one or the other kind of learning algorithm to return a list of instances ranked in order of the quality of fit. Learning to rank also finds application in sports analytic; especially in activities like football scouting, where club representatives attend football games worldwide to collect intelligence on potential recruits. In this project, learning to rank method is applied to automate the process of football scouting by analyzing the player database to generate a list of desired number of footballers that could be recruited based on given criteria. This becomes an important application as player recruiting is a competitive business and having a list of options ranked on given criteria can help in making faster and better decisions. Learning to rank technique is used with pairwise-approach that makes it possible to use state-of-the-art supervised algorithms for generating predictions. Borda count technique is applied to convert the pairwise predictions into a ranked list.
Trk receptor signalling and sensory neuron fate are perturbed in human neuropathy caused by Gars mutations Running title: Sensory neuron identity is impaired in CMT2D mice

1 Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, London WC1N 3BG, UK 2 Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, UK. 3 Departments of Chemical Physiology and Cell and Molecular Biology, The Scripps Research Institute, La Jolla, California 92037, USA. 4 The Jackson Laboratory, Bar Harbor, ME 04609, USA. 5 The Graduate School of Biomedical Science and Engineering, The University of Maine, Orono, ME 04469, USA. # These authors contributed equally.
Discovering genomic islands using DNA sequence embedding

Genomic islands(GIs) are clusters of genes that are acquired during the Horizontal Gene Transfer process(HGT) by bacterial genomes. These islands play a crucial role in the evolution of bacteria by helping them adapt to changing environments. The detection of GIs is therefore an important problem in medical and environmental research. There have been many previous studies on computationally identifying GIs, but most of the studies rely on either closely related genomes or annotated nucleotide sequences with predictions based on a ﬁxed set of known features. Previous research on unannotated sequences has not been able to reach a good accuracy due to the lack of information taken into account while prediction and lack of GI boundary detection method. In this thesis, I present a machine learning-based framework called TreasureIsland, that uses an unsupervised representation of DNA sequences to predict GI. I propose to improve the boundary detection problem of GI by using a boundary ﬁne-tuning method to attain better precision. I evaluate the eﬃciency of my framework by using a reference dataset obtained by the comparative genomics method and from the literature. The evaluations show that this framework was able to achieve a high recall and accuracy when compared to other GI predictors.
Time-averaged Spray Analysis in the Near-field Using Broadband and Narrowband X-ray Measurements

The characterization of a spray in the near-field region is challenging because of its high optical density in this region. X-ray based techniques, with weak scatter and strong penetration properties, can provide better characterization than optical assessment techniques in this region. In this work, the effects of various operating parameters on the evaluation of the optical depth (defined as the accumulated liquid thickness in the beam path times the X ray attenuation coefficient) and spray profile of an atomizing spray in the near-field region are evaluated based on time-averaged X-ray analysis techniques. Controlling parameters in the spray structure include swirl ratio, liquid phase Reynolds number, and gas phase Reynolds number. Data from the broadband X-ray radiographs obtained using a tube source at Iowa State University and from focused beam measurements at the Advanced Photon Source at Argonne National Laboratory are compared. The X-ray tube source at ISU was operated at two different energy levels, which reveals that the X-ray tube source energy influenced the magnitude of the optical depth but did not change the shape of the distribution. For the no swirl condition, gas flow rate and liquid flow rate had opposite effects on the spray profile, where the spray widens as the gas flow rate increases and narrows as the liquid flow rate increases. As the swirl ratio increases from 0 to 1, the spray widens and then narrows, which indicates that the effect of swirl being more dramatic and then weaker. The critical swirl ratio at which the spray reaches its widest spread differs at different flow conditions.
#A62 INTEGERS 20 (2020) SYSTEMATIC COUNTING OF RESTRICTED PARTITIONS

We use ‘partial difference operator schemes’ and dynamical programming to design algorithms that systematically count sets of integer partitions avoiding any set of patterns (of a certain, natural, kind). We describe two approaches, a ‘negative’ (adapting the Goulden–Jackson algorithm for enumerating words), and a ‘positive’ approach that turns out to be much more efficient. Nevertheless, the negative approach has theoretical interest.
Centennial Olive trees in Lebanon: a substantial patrimony

This study aimed to assess the centennial olive trees growing across Lebanon, with the perspective of conservation of the ancient germplasm. The survey indicated the existence of numerous centennial olive trees distributed in different agro-climatic areas, from 80 to 1350 meters altitude across the country. Centennial olives were found in large size orchards and scattered as well as in young orchards, road hedges and gardens for ornamental purposes. Yet, no reliable information is available regarding the age of the centennials, but they can considered as 500 to 1000 years old. Among these, only six centennials located in Bcheale village in the north of the country at 1000 meters altitude are considered as “millenials” or “monumentals” by the Ministry of Tourism, while the remaining ones widespread across the countries are still ignored. As a preliminary morphological characterization of the trees conducted on 292 centennials spread in 48 orchards, a large variability was recorded for foot, trunk and central cavity sizes. Principal component analysis showed that foot and trunk circumferences as well as central cavity diameter were the most discriminating descriptors. Most of the 48 orchards were clustered together in one pool sharing similar traits. The most outstanding orchards were located in 10 locations distributed across Lebanon. At the tree level, six single trees located in North and Mount Lebanon were well differentiated by their large sized foot, trunk and central cavity diameter. These centennials should be further characterized using morphological and agronomical descriptors in order to understand their performance through time and to valorize them in selection programs.
miR-3187-3p enhances migration and invasion by targeting PER2 in head and neck squamous cell carcinomas

Invasion and metastasis are major contributors to treatment failure in patients with head and neck squamous cell carcinomas (HNSCCs) and microRNAs (miRNAs) are reported to play important roles in tumor progression. Our study therefore try to find the crucial miRNAs and reveal their molecular and functional mechanisms involved in migration and invasion of HNSCCs. Through The Cancer Genome Atlas (TCGA) data analysis, we screened out miR-3187-3p and its biological function and specific mechanism were further analyzed. The wound-healing and transwell invasion assay demonstrated that miR-3187-3p promoted the capacity of migration and invasion of HNSCCs in vitro. Luciferase reporter assays showed that PER2 was a direct target of miR-3187-3p, which could reverse the effect of miR-3187-3p in HNSCCs. Furthermore, we found that miR-3187-3p / PER2 axis activated the Wnt / β-catenin signaling pathway in HNSCCs. Altogether, our study indicated that miR-3187-3p enhanced migration and invasion by targeting PER2 in HNSCCs.
Structural connectivity of subthalamic nucleus stimulation for improving freezing of gait

Gait impairments such as freezing of gait (FOG) are among the most common and disabling symptoms of Parkinson's disease (PD). While the efficacy of deep brain stimulation (DBS) of the subthalamic nucleus (STN) in patients with early or advanced PD has been proven in large randomised controlled trials, its effect on gait impairments is still insufficiently understood. Moreover, there is uncertainty about pathways that need to be modulated to improve gait impairments. In this bi-centric study, we investigated how STN-DBS alters FOG in 47 subjects with PD. We assessed freezing prevalence and severity using the Freezing of Gait Questionnaire and Item 14 of the Unified Parkinson's Disease Rating Scale-II. Using a model of publicly available basal-ganglia pathways we determined a connectivity profile for postoperative changes in FOG. Compared to preoperative baseline, freezing of gait significantly improved six months postoperatively, marked by reduced frequency and duration of freezing episodes. We found that optimal stimulation sites for improving freezing of gait structurally connected to primary and supplementary motor areas, the dorsolateral prefrontal cortex and to the globus pallidus. Stimulation of the lenticular fasciculus was associated with worsening of freezing of gait. Our findings highlight the need for optimal identification and characterisation for network structures that can be implemented in stereotactic planning and can additionally pose a target for postoperative stimulation strategies.