Miracle-dz/UniFAR-FTUs huggingface dataset:
Immunologic and Virologic Mechanisms for Partial Protection from Intravenous Challenge by an Integration-Defective SIV Vaccine †

The suppression of viral loads and identification of selection signatures in non-human primates after challenge are indicators for effective human immunodeficiency virus (HIV)/simian immunodeficiency virus (SIV) vaccines. To mimic the protective immunity elicited by attenuated SIV vaccines, we developed an integration-defective SIV (idSIV) vaccine by inactivating integrase, mutating sequence motifs critical for integration, and inserting the cytomegalovirus (CMV) promoter for more efficient expression in the SIVmac239 genome. Chinese rhesus macaques were immunized with idSIV DNA and idSIV particles, and the cellular and humoral immune responses were measured. After the intravenous SIVmac239 challenge, viral loads were monitored and selection signatures in viral genomes from vaccinated monkeys were identified by single genome sequencing. T cell responses, heterologous neutralization against tier-1 viruses, and antibody-dependent cellular cytotoxicity (ADCC) were detected in idSIV-vaccinated macaques post immunization. After challenge, the median peak viral load in the vaccine group was significantly lower than that in the control group. However, this initial viral control did not last as viral set-points were similar between vaccinated and control animals. Selection signatures were identified in Nef, Gag, and Env proteins in vaccinated and control macaques, but these signatures were different, suggesting selection pressure on viruses from vaccine-induced immunity in the vaccinated animals. Our results showed that the idSIV vaccine exerted some pressure on the virus population early during the infection but future modifications are needed in order to induce more potent immune responses.
Mapping Walls of Indoor Environment using RGB-D Sensor

Inferring walls configuration of indoor environment could help robot "understand" the environment better. This allows the robot to execute a task that involves inter-room navigation, such as picking an object in the kitchen. In this paper, we present a method to inferring walls configuration from a moving RGB-D sensor. Our goal is to combine a simple wall configuration model and fast wall detection method in order to get a system that works online, is real-time, and does not need a Manhattan World assumption. We tested our preliminary work, i.e. wall detection and measurement from moving RGB-D sensor, with MIT Stata Center Dataset. The performance of our method is reported in terms of accuracy and speed of execution.
Magnesium aluminate spinel raw materials for high performance refractories for steel ladles

High quality steel production requires extended treatment of the steel in the steel ladle. This has a remarkable impact on the steel ladle refractories, e.g. the need for high performance functional refractories like purging plugs. Operational changes such as increasing tapping temperatures, longer hold times and more aggressive secondary metallurgy are countered by the need for thinner refractory linings and longer refractories life. These combined factors have led to a resurgence in interest in magnesium aluminate spinel raw materials. Magnesium aluminate spinels have been used in steel-making refractories for many years, in a variety of different forms. This paper reviews the production, properties and performance of spinels. Recent developments in the applications of spinels will also be discussed.
Antiphosphatidylserine/prothrombin (aPS/PT) antibodies are associated with Raynaud phenomenon and migraine in primary thrombotic antiphospholipid syndrome

Objectives Antibodies to phosphatidylserine/prothrombin complex (aPS/PT) detectable in sera of some patients with antiphospholipid syndrome (APS) have been shown to correlate with thrombosis. However, associations of aPS/PT antibodies with APS related disorders remain unclear. Aim To evaluate whether there are any associations between aPS/PT antibodies and Raynaud phenomenon, migraine and/or valvular lesions in primary thrombotic APS (PAPS). Methods We enrolled 67 consecutive patients (56 women) with thrombotic PAPS (VTE in 80.6%), aged 46.2 ± 13.5 years. The exclusion criteria were: acute coronary syndromes or stroke within preceding 6 months, cancer, severe comorbidities and pregnancy. The IgG and IgM aPS/PT antibodies were determined by ELISA with the cut-off of 30 units. We recorded Raynaud phenomenon, migraine and valvular lesions. Results Positive IgM or/and IgG aPS/PT antibodies were observed in 29 patients (43.3%), with a higher prevalence of IgM antibodies (n = 27, 40.3%) compared with IgG isotype (n = 12, 17.9%, p = 0.014). aPS/PT antibodies were observed most commonly in patients with triple aPL (n = 12, 85.7%) compared with those with double (n = 5, 35.7%) or single aPL antibodies (n = 12, 30.8%, p = 0.03), with no association with demographics, the ANA titre, the type of thrombotic events or medications. Raynaud phenomenon, migraine and valvular lesions were observed in 15% (n = 10), 30% (n = 20) and 18% (n = 12) of the patients, respectively. Raynaud phenomenon and migraine, but not valvular lesions, were markedly more frequent in PAPS patients presenting with positive aPS/PT antibodies (n = 10, 34.5% vs. n = 0, 0%; p = 0.0001). Conclusions In PAPS patients aPS/PT antibodies are related to the occurrence of both Raynaud phenomenon and migraine.
Estimation of Ammonia Emission from Manure Belt Poultry Layer Houses Using an Alternative Mass-Balance Method

Ammonia (NH3) emission from animal feeding operations (AFOs) has caused concerns on public health and environmental degradation, such as ecosystem acidification, eutrophication, and formation of PM2.5 fine particles. Current ammonia emission measurement methodologies are accurate and reliable, but time consuming, expensive, and impractical for most facilities. In the present study, an alternative and cost effective mass balance methodology was developed to predict the ammonia emission from animal facilities. The mass balance equations have been developed to eliminate needs for tracking manure flow rate to obtain accurate NH3 estimation. The methodology was applied to three manure-belt layer poultry houses with approximately 150,000 birds in each house in Ohio and validated using continuous ammonia emission measurement data. Feed, manure and egg samples were collected from the three houses in three seasons (cold, mild, and hot) to evaluate the seasonal variation of ammonia emission from the poultry facilities. Results show that this alternative mass balance method can estimate NH3 emission from manure-belt poultry layer house effectively. NH3 emission rate from manure belt poultry layer houses with manure removal every 3.5 to 5 days was 0.07-0.37 g NH3 bird-1day-1. These results agrees well with the NH3 emission values published in the previous literatures (0.027-0.616 g NH3 bird-1day-1), but were lower than the NH3 emission rate (0.1-0.86 g NH3 bird-1day-1) measured using continuous monitoring system. In the comparison analysis of NH3 measurement and estimation emissions, Normalized Mean Error (NME), Normalized Mean Square Error (NMSE) and Fractional Bias (FB) are calculated to be 52.05%, 85.32% and -70.36% respectively. This study suggests that manure removal time interval and air temperature can be important factors impacting NH3 emission. This mass balance method can only estimate total nitrogen loss in a whole production process, which is an upper bound of NH3-N loss. It is needed to quantify other nitrogen compound gas emissions, such as N2O, NOx, N2 for accurate NH3 emission estimation.
Increased in vitro fatty acid supply and cellular transport capacities in cold-acclimated ducklings ( Cairina moschata).

In cold-acclimated (CA) birds, lipids play a crucial role in regulatory thermogenesis by acting both as substrates for and activators of thermogenic processes. The capacity to supply lipids to thermogenic tissues, which could limit cold thermogenesis, was assessed in CA ducklings (5 wk old, 4°C) and compared with thermoneutral controls (TN, 25°C). In CA ducklings, basal lipolytic activity of adipose tissue fragments was higher (202 ± 9 vs. 130 ± 14 nmol glycerol released ⋅ 100 mg tissue-1 ⋅ h-1, +55%) than in TN controls, while glucagon had a much higher stimulatory effect (+140 to +500% depending on dose). This was consistent with increased plasma levels of nonesterified fatty acids (FA, +57%) and glycerol (+31%) in vivo. In vitro endothelial lipase activity per organ was higher in CA than in TN ducklings in red gastrocnemius muscle (6.3 ± 0.6 vs. 3.5 ± 0.3 μeq nonesterified FA released per hour, +80%) and liver (+55%). The intracellular FA-binding capacity of (12-18 kDa) proteins was higher in gastrocnemius muscle (+43%) and liver (+74%) from CA ducklings. In gastrocnemius, it was linked to a higher content (21 ± 2 vs. 15 ± 2 μg/mg protein, +37%) of an intracellular 15.4-kDa FA-binding protein. These in vitro results indicate that coordinated increases in FA supply from adipose tissue, cellular uptake of lipoprotein-derived FA, and intracellular FA transport capacity occur in CA ducklings endowed with higher thermogenic capacity and cold endurance.
Apathy and impulsivity in frontotemporal lobar degeneration syndromes

Lansdall et al. reveal the structural brain changes leading to different types of apathy and impulsivity, across the spectrum of disorders caused by frontotemporal lobar degeneration, including frontotemporal dementia, progressive supranuclear palsy and corticobasal syndrome. The positive correlation between apathy and impulsivity indicates the need for a unified therapeutic strategy.
Sox2 Is Essential for Oligodendroglial Proliferation and Differentiation during Postnatal Brain Myelination and CNS Remyelination

In the CNS, myelination and remyelination depend on the successful progression and maturation of oligodendroglial lineage cells, including proliferation and differentiation of oligodendroglial progenitor cells (OPCs). Previous studies have reported that Sox2 transiently regulates oligodendrocyte (OL) differentiation in the embryonic and perinatal spinal cord and appears dispensable for myelination in the postnatal spinal cord. However, the role of Sox2 in OL development in the brain has yet to be defined. We now report that Sox2 is an essential positive regulator of developmental myelination in the postnatal murine brain of both sexes. Stage-specific paradigms of genetic disruption demonstrated that Sox2 regulated brain myelination by coordinating upstream OPC population supply and downstream OL differentiation. Transcriptomic analyses further supported a crucial role of Sox2 in brain developmental myelination. Consistently, oligodendroglial Sox2-deficient mice developed severe tremors and ataxia, typical phenotypes indicative of hypomyelination, and displayed severe impairment of motor function and prominent deficits of brain OL differentiation and myelination persisting into the later CNS developmental stages. We also found that Sox2 was required for efficient OPC proliferation and expansion and OL regeneration during remyelination in the adult brain and spinal cord. Together, our genetic evidence reveals an essential role of Sox2 in brain myelination and CNS remyelination, and suggests that manipulation of Sox2 and/or Sox2-mediated downstream pathways may be therapeutic in promoting CNS myelin repair. SIGNIFICANCE STATEMENT Promoting myelin formation and repair has translational significance in treating myelin-related neurological disorders, such as periventricular leukomalacia and multiple sclerosis in which brain developmental myelin formation and myelin repair are severely affected, respectively. In this report, analyses of a series of genetic conditional knock-out systems targeting different oligodendrocyte stages reveal a previously unappreciated role of Sox2 in coordinating upstream proliferation and downstream differentiation of oligodendroglial lineage cells in the mouse brain during developmental myelination and CNS remyelination. Our study points to the potential of manipulating Sox2 and its downstream pathways to promote oligodendrocyte regeneration and CNS myelin repair.
Crowd-based Multi-Predicate Screening of Papers in Literature Reviews

Systematic literature reviews (SLRs) are one of the most common and useful form of scientific research and publication. Tens of thousands of SLRs are published each year, and this rate is growing across all fields of science. Performing an accurate, complete and unbiased SLR is however a difficult and expensive endeavor. This is true in general for all phases of a literature review, and in particular for the paper screening phase, where authors filter a set of potentially in-scope papers based on a number of exclusion criteria. To address the problem, in recent years the research community has began to explore the use of the crowd to allow for a faster, accurate, cheaper and unbiased screening of papers. Initial results show that crowdsourcing can be effective, even for relatively complex reviews. In this paper we derive and analyze a set of strategies for crowd-based screening, and show that an adaptive strategy, that continuously re-assesses the statistical properties of the problem to minimize the number of votes needed to take decisions for each paper, significantly outperforms a number of non-adaptive approaches in terms of cost and accuracy. We validate both applicability and results of the approach through a set of crowdsourcing experiments, and discuss properties of the problem and algorithms that we believe to be generally of interest for classification problems where items are classified via a series of successive tests (as it often happens in medicine).
Measuring the semantic gap based on a communication channel model

The collected Earth Observation (EO) data volumes are increasing immensely. In the meantime, the need for retrieval of focused information for decision making is increasing. Due to the particular nature of EO sensors, recording signals very differently than humans perceptual system, the challenges raised by the semantic and sensory gaps are immensely amplified in designing retrieval methods for EO images. This article introduces a method based on communication channel model to quantify and measure the semantic gap, used to assess various feature descriptors for semantic annotation purposes. The approach uses Latent Dirichlet Allocation (LDA), considering images as the source and the semantic topics as the receiver. The parameters of LDA are estimated for computing the Mutual Information to assess latent semantics of feature space. We further introduce a method to measure the distance between humans' and computer's semantics. The results are validated using an SVM-based classifier for an annotated dataset.
The Role of Haptics in User Input for Simple 3D Interaction Tasks - An Analysis of Interaction Performance and User Experience

Traditionally, input devices allowed for at least a certain degree of haptic experience by involving direct physical contact between user and device. Recently, touchless interaction gained popularity through readily available, cheap devices like the Leap motion controller or Microsoft Kinect. Usually, these devices support more than two degrees of freedom and are thus especially suitable for interaction tasks in a three-dimensional space. However, besides the high potential that lies within touchless input techniques, they also involve new challenges (e.g., lack of borders and natural haptic guidance). In this paper, we aim at the identification of potentials and limitations inherent to three different input techniques that involve a varying amount of haptics (i.e., touchful, touchless and semi-touchless input). We present a study conducted with 25 users that focuses on simple input tasks in a 3D interaction space and analyzes objective interaction performance metrics (e.g., regularity or time) and subjective User Experience aspects (e.g., dependability or efficiency). It reveals parallels as well as contrasts between the users’ actual interaction performance and perceived UX (e.g., several metrics suggested haptic input to outperform touchless input while differences regarding UX were not significant). The results are intended to inform other researchers when designing interactive environments.
Closed Analytic Elements with Flexible Geometry

A simple and fast treatment of hydrogeologic features with irregularly shaped boundaries in two‐dimensional analytic element groundwater flow models is presented. The star domain shapes of the features are restricted to closed shapes represented as smooth and continuous single‐valued functions of distance from a focus point, rˆθ . The element can be used to treat a variety of boundary and continuity conditions, including those of irregularly shaped lakes or heterogeneities in hydraulic conductivity. The new element is demonstrated via some simple illustrative test cases and shown to be efficient, accurate, and much simpler to implement than existing solutions for irregular shapes.
Direct Observation of Aggregative Nanoparticle Growth: Kinetic Modeling of the Size Distribution and Growth Rate

Direct observations of solution-phase nanoparticle growth using in situ liquid transmission electron microscopy (TEM) have demonstrated the importance of “non-classical” growth mechanisms, such as aggregation and coalescence, on the growth and final morphology of nanocrystals at the atomic and single nanoparticle scales. To date, groups have quantitatively interpreted the mean growth rate of nanoparticles in terms of the Lifshitz–Slyozov–Wagner (LSW) model for Ostwald ripening, but less attention has been paid to modeling the corresponding particle size distribution. Here we use in situ fluid stage scanning TEM to demonstrate that silver nanoparticles grow by a length-scale dependent mechanism, where individual nanoparticles grow by monomer attachment but ensemble-scale growth is dominated by aggregation. Although our observed mean nanoparticle growth rate is consistent with the LSW model, we show that the corresponding particle size distribution is broader and more symmetric than predicted by LSW. Follow.
Multi-processor FFT

Computing the Fast Fourier Transform on a distributed memory architecture by a direct pipelined radix-2 algorithm, a bi-section or multi-section algorithm, all yield the same communications requirement, if communication for all FFT stages can be performed concurrently, the input data is in normal order, and the data allocation consecutive. With a cyclic data allocation, or bit-reversed input data and a consecutive allocation, multi-sectioning o ers a reduced communications requirement by approximately a factor of two. For a consecutive data allocation, normal input order, a decimation-in-time FFT requires that P N + d 2 twiddle factors be stored for P elements distributed evenly over N processors, and the axis subject to transformation distributed over 2 d processors. No communication of twiddle factors is required. The same storage requirements hold for a decimation-in-frequency FFT, bit-reversed input order, and consecutive data allocation. The opposite combination of FFT type and data ordering requires a factor of log 2 N more storage for N processors. The peak performance for a Connection Machine system CM-200 implementation is 12.9 G ops/s in 32-bit precision, and 10.7 G ops/s in 64-bit precision for unordered transforms local to each processor. The corresponding execution rates for ordered transforms are 11.1 G ops/s and 8.5 G ops/s, respectively. For distributed oneand two-dimensional transforms the peak performance for unordered transforms exceeds 5 G ops/s in 32-bit precision, and 3 G ops/s in 64-bit precision. Three-dimensional transforms executes at a slightly lower rate. Distributed ordered transforms executes at a rate of about 1 2 to 2 3 of the unordered transforms.
Predicting Temperament using Keirsey's Model for Portuguese Twitter Data

Temperament is a set of innate tendencies of the mind related with the processes of perceiving, analyzing and decision making. The purpose of this paper is to predict the user's temperament based on Portuguese tweets and following Keirsey's model, which classifies the temperament into artisan, guardian, idealist and rational. The proposed methodology uses a Portuguese version of LIWC, which is a dictionary of words, to analyze the context of words, and supervised learning using the KNN, SVM and Random Forest algorithms for training the classifiers. The resultant average accuracy obtained was 88.37% for the artisan temperament, 86.92% for the guardian, 55.61% for the idealist, and 69.09% for the rational. By using binary classifiers the average accuracy was 90.93% for the artisan temperament, 88.98% for the guardian, 51.98% for the idealist and 71.42% for the Rational.
NODDI-DTI: Estimating Neurite Orientation and Dispersion Parameters from a Diffusion Tensor in Healthy White Matter

The NODDI-DTI signal model is a modification of the NODDI signal model that formally allows interpretation of standard single-shell DTI data in terms of biophysical parameters in healthy human white matter (WM). The NODDI-DTI signal model contains no CSF compartment, restricting application to voxels without CSF partial-volume contamination. This modification allowed derivation of analytical relations between parameters representing axon density and dispersion, and DTI invariants (MD and FA) from the NODDI-DTI signal model. These relations formally allow extraction of biophysical parameters from DTI data. NODDI-DTI parameters were estimated by applying the proposed analytical relations to DTI parameters estimated from the first shell of data, and compared to parameters estimated by fitting the NODDI-DTI model to both shells of data (reference dataset) in the WM of 14 in vivo diffusion datasets recorded with two different protocols, and in simulated data. The first two datasets were also fit to the NODDI-DTI model using only the first shell (as for DTI) of data. NODDI-DTI parameters estimated from DTI, and NODDI-DTI parameters estimated by fitting the model to the first shell of data gave similar errors compared to two-shell NODDI-DTI estimates. The simulations showed the NODDI-DTI method to be more noise-robust than the two-shell fitting procedure. The NODDI-DTI method gave unphysical parameter estimates in a small percentage of voxels, reflecting voxelwise DTI estimation error or NODDI-DTI model invalidity. In the course of evaluating the NODDI-DTI model, it was found that diffusional kurtosis strongly biased DTI-based MD values, and so, making assumptions based on healthy WM, a novel heuristic correction requiring only DTI data was derived and used to mitigate this bias. Since validations were only performed on healthy WM, application to grey matter or pathological WM would require further validation. Our results demonstrate NODDI-DTI to be a promising model and technique to interpret restricted datasets acquired for DTI analysis in healthy white matter with greater biophysical specificity, though its limitations must be borne in mind.