Miracle-dz/UniFAR-FTUs huggingface dataset:
Ranking Functions over Labelings

We study rankings over labelings as a generalization of traditional labeling-based semantics in abstract argumentation. Our approach is an alternative to recent developments on rankings over arguments. The formal basis is a qualitative abstraction of probability theory called ranking theory. We propose a fundamental property, called SCC stratiﬁcation , that a ranking-theoretic semantics can be expected to satisfy, present a general scheme to deﬁne a ranking-theoretic semantics, and determine conditions under which this scheme satisﬁes SCC stratiﬁcation.
Abnormal changes in the quantity and function of osteoblasts cultured in vitro in patients with myelodysplastic syndrome

Changes in bone marrow niches can lead to the occurrence of myelodysplastic syndrome (MDS). As an important part of the bone marrow niche, osteoblasts serve a key role in the progression of MDS. The present study investigated the quantity and function of osteoblasts and, through in vitro assays, detected changes in signaling pathways and the association with progression in MDS patients. The ratios of osteoprogenitors (CD34+OCN+) and OCN+CD34−Lin− osteoblasts in MDS patients were significantly less than those of normal controls. The results of this study demonstrated that the quantity and activity of osteoblasts in MDS patients were lower than those in normal controls. Furthermore the activity of osteoblasts in patients correlated with the severity of MDS. The quantity of osteoblasts cultured in vitro from high-risk and very high-risk MDS patients (WHO Classification-Based Prognostic Scoring System score 3–6) was decreased. The levels of T-cell immunoglobulin and mucin domain-containing 3 (TIM3) and Jagged 1 were also increased in the osteoblasts in vitro. These results indicated that osteoblasts are abnormally altered in MDS patients, and that there are associations between abnormal changes of osteoblasts and the severity of MDS.
Countdown games, and simulation on (succinct) one-counter nets

We answer an open complexity question by Hofman, Lasota, Mayr, Totzke (LMCS 2016) for simulation preorder on the class of succinct one-counter nets (i.e., one-counter automata with no zero tests where counter increments and decrements are integers written in binary); the problem was known to be PSPACE-hard and in EXPSPACE. We show that all relations between bisimulation equivalence and simulation preorder are EXPSPACE-hard for these nets; simulation preorder is thus EXPSPACE-complete. The result is proven by a reduction from reachability games whose EXPSPACE-completeness in the case of succinct one-counter nets was shown by Hunter (RP 2015), by using other results. We also provide a direct self-contained EXPSPACE-completeness proof for a special case of such reachability games, namely for a modification of countdown games that were shown EXPTIME-complete by Jurdzinski, Sproston, Laroussinie (LMCS 2008); in our modification the initial counter value is not given but is freely chosen by the first player. We also present an alternative proof for the upper bound by Hofman et al. In particular, we give a new simplified proof of the belt theorem that yields a simple graphic presentation of simulation preorder on (non-succinct) one-counter nets and leads to a polynomial-space algorithm (which is trivially extended to an exponential-space algorithm for succinct one-counter nets).
A CNN-Based Approach for Automatic License Plate Recognition in the Wild

In this paper, we address automatic license plate recognition (ALPR) in the wild. Such an ALPR system takes an arbitrary image as input and outputs the recognized license plate numbers. In the detection stage, we adopt a cascade structure comprising of a fast region proposal network and a R-CNN network. The R-CNN network not only eliminates false alarms but also regresses corner positions for each detected plate. This allows us to estimate an affine transformation matrix to rectify the extracted plates. In the recognition stage, we propose an innovative structure composed of parallel spatial transform networks and shared-weight recognizers. The system is trained and evaluated on a Chinese license plate dataset with over 18K images. Results show that our detector performs better than faster R-CNN (VGG) which is 1.5x slower in testing and 57x larger in model size. The recognizer is also significantly better than existing solutions, reducing 57.5% of the errors of a state-of-the-art character sequence encoding scheme.
Integrative proteomics and bioinformatic prediction enable a high-confidence apicoplast proteome in malaria parasites

Malaria parasites (Plasmodium spp.) and related apicomplexan pathogens contain a non-photosynthetic plastid called the apicoplast. Derived from an unusual secondary eukaryote-eukaryote endosymbiosis, the apicoplast is a fascinating organelle whose function and biogenesis rely on a complex amalgamation of bacterial and algal pathways. Because these pathways are distinct from the human host, the apicoplast is an excellent source of novel antimalarial targets. Despite its biomedical importance and evolutionary significance, the absence of a reliable apicoplast proteome has limited most studies to the handful of pathways identified by homology to bacteria or primary chloroplasts, precluding our ability to study the most novel apicoplast pathways. Here we combine proximity biotinylation-based proteomics (BioID) and a new machine learning algorithm to generate a high-confidence apicoplast proteome consisting of 346 proteins. Critically, the high accuracy of this proteome significantly outperforms previous prediction-based methods and extends beyond other BioID studies of unique parasite compartments. Half of identified proteins have unknown function, and 77% are predicted to be important for normal blood-stage growth. We validate the apicoplast localization of a subset of novel proteins and show that an ATP-binding cassette protein ABCF1 is essential for blood-stage survival and plays a previously unknown role in apicoplast biogenesis. These findings indicate critical organellar functions for newly discovered apicoplast proteins. The apicoplast proteome will be an important resource for elucidating unique pathways derived from secondary endosymbiosis and prioritizing antimalarial drug targets.
Total Capture: 3D Human Pose Estimation Fusing Video and Inertial Sensors

We present an algorithm for fusing multi-viewpoint video (MVV) with inertial measurement unit (IMU) sensor data to accurately estimate 3D human pose. A 3-D convolutional neural network is used to learn a pose embedding from volumetric probabilistic visual hull data (PVH) derived from the MVV frames. We incorporate this model within a dual stream network integrating pose embeddings derived from MVV and a forward kinematic solve of the IMU data. A temporal model (LSTM) is incorporated within both streams prior to their fusion. Hybrid pose inference using these two complementary data sources is shown to resolve ambiguities within each sensor modality, yielding improved accuracy over prior methods. A further contribution of this work is a new hybrid MVV dataset (TotalCapture) comprising video, IMU and a skeletal joint ground truth derived from a commercial motion capture system. The dataset is available online at http://cvssp.org/data/totalcapture/.
Quantification of Blood Velocity with 4D Digital Subtraction Angiography Using the Shifted Least-Squares Method

BACKGROUND AND PURPOSE: 4D-DSA provides time-resolved 3D-DSA volumes with high temporal and spatial resolutions. The purpose of this study is to investigate a shifted least squares method to estimate the blood velocity from the 4D DSA images. Quantitative validation was performed using a flow phantom with an ultrasonic flow probe as ground truth. Quantification of blood velocity in human internal carotid arteries was compared with measurements generated from 3D phase-contrast MR imaging. MATERIALS AND METHODS: The centerlines of selected vascular segments and the time concentration curves of each voxel along the centerlines were determined from the 4D-DSA dataset. The temporal shift required to achieve a minimum difference between any point and other points along the centerline of a segment was calculated. The temporal shift as a function of centerline point position was fit to a straight line to generate the velocity. The proposed shifted least-squares method was first validated using a flow phantom study. Blood velocities were also estimated in the 14 ICAs of human subjects who had both 4D-DSA and phase-contrast MR imaging studies. Linear regression and correlation analysis were performed on both the phantom study and clinical study, respectively. RESULTS: Mean velocities of the flow phantom calculated from 4D-DSA matched very well with ultrasonic flow probe measurements with 11% relative root mean square error. Mean blood velocities of ICAs calculated from 4D-DSA correlated well with phase-contrast MR imaging measurements with Pearson correlation coefficient r = 0.835. CONCLUSIONS: The availability of 4D-DSA provides the opportunity to use the shifted least-squares method to estimate velocity in vessels within a 3D volume.
Radiological and Clinical Outcomes of Balloon Kyphoplasty versus Radiofrequency Kyphoplasty in the Treatment of Vertebral Compression Fractures

Study Design Retrospective cohort analysis Purpose Comparison of balloon kyphoplasty (BKP) and radiofrequency kyphoplasty (RFK) with respect to height restoration of the fractured vertebral bodies and the pain relief experienced after the surgical procedure. Overview of Literature BKP and RFK both offer safe, time-saving, and potent treatment options for vertebral compression fractures, but neither of these methods demonstrated any key advantage over the other yet. Methods We performed a retrospective analysis of a cohort of 156 patients (mean age, 73±11 years) with 252 fractured vertebral bodies treated with kyphoplasty. Pain intensity was measured using a Visual Analogue Scale. Preoperative and postoperative computed tomography images were analyzed and gauged using modified bisegmental Cobb angle, vertebral angle, as well as anterior (Ha), middle (Hm), and posterior (Hp) vertebral body heights. Results The mean postoperative pain relief was 5.1±1.8, which was maintained over the entire follow-up period. There were no significant differences in the pain relief between BKP and RFK. Postoperative changes in the vertebral angle (−1.3°±3.3°, p<0.001) and Ha, Hm, and Hp vertebral body heights (Ha, 1.5±2.9 mm; Hm, 2.1±2.9 mm; Hp, 0.9±2.1 mm; p<0.001) were significant. However, the initial height restoration could not be maintained by the 6-week and 1-year follow-up. Neither BKP nor RFK could achieve a clinically relevant advantage over each other. There was no correlation between pain relief and height restoration after kyphoplasty. Conclusions Both BKP and RFK had comparable beneficial clinical and radiological effects in the treatment of vertebral compression fractures. However, neither the actual extent of height restoration nor its loss seems to affect the marked pain relief.
The Competitive Dynamics of New DVD Releases

We study the market for new (movie) DVDs in the United States. Our demand model captures seasonality, freshness (i.e., time between theatrical and DVD release), and state dependence. We also develop a structural model of dynamic competition in which studios balance waiting for high-demand weeks, against reduced freshness, and against competitive crowding. We find that studios emphasize DVD revenues from larger movies (by theatrical revenue) over DVD revenues from smaller movies. Studios also emphasize revenue from consumers who prefer larger and fresher movies. These behaviors are consistent with managerial conservatism: studio executives forgo DVD revenues from smaller movies to ensure the DVD success of larger movies. This paper was accepted by J. Miguel Villas-Boas, marketing.
Multi-view Brain Network Prediction from a Source View Using Sample Selection via CCA-Based Multi-kernel Connectomic Manifold Learning

Several challenges emerged from the dataclysm of neuroimaging datasets spanning both healthy and disordered brain spectrum. In particular, samples with missing data views (e.g., functional imaging modality) constitute a hurdle to conventional big data learning tech-niques which ideally would be trained using a maximum number of samples across all views. Existing works on predicting target data views from a source data view mainly used brain images such as predicting PET im-age from MRI image. However, to the best of our knowledge, predicting a set of target brain networks from a source network remains unexplored. To ﬁll this gap, a multi-kernel manifold learning (MKML) framework is proposed to learn how to predict multi-view brain networks from a source network to impute missing views in a connectomic dataset. Prior to performing multiple kernel learning of multi-view data, it is typically assumed that the source and target data come from the same distribution. However, multi-view connectomic data can be drawn from diﬀerent distributions. In order to build robust predictors for predicting target multi-view networks from a source network view, it is necessary to take into account the shift between the source and target domains. Hence, we ﬁrst estimate a mapping function that transforms the source and the target domains into a shared space where their correlation is maximized using canonical correlation analysis (CCA). Next, we nest the projected training and testing source samples into a connectomic manifold using multiple kernel learning, where we identify the most similar training samples to the testing source network. Given a testing subject, we introduce a cross-domain trust score to assess the reliability of each selected training sample for the target prediction task. Our model outperformed both conventional MKML technique and the proposed CCA-based MKML technique without enhancement by trust scores.
Trypsin inhibition by Ligupurpuroside B as studied using spectroscopic, CD, and molecular docking techniques

Abstract It is well known that Ligupurpuroside B is a water-soluble polyphenolic compound and used to brew bitter tea with antioxidant activities. It acted as a stimulant to the central nervous system and a diuretic (increase the excretion of urine), was used to treat painful throat and high blood pressure, and also exerted weight-loss function. In this regard, a detailed investigation on the mechanism of interaction between Ligupurpuroside B and trypsin could be of great interest to know the pharmacokinetic behavior of Ligupurpuroside B and for the design of new analogues with effective pharmacological properties. Ligupurpuroside B successfully quenched the intrinsic fluorescence of trypsin via static quenching mechanism. The binding constants (Ka) at three temperatures (288, 298, and 308 K) were 1.7841 × 104, 1.6251 × 104 and 1.5483 × 104 L mol−1, respectively. Binding constants revealed the stronger binding interaction between Ligupurpuroside B and trypsin. The number of binding sites approximated to one, indicating a single class of binding for Ligupurpuroside B in trypsin. The enzyme activity result suggested that Ligupurpuroside B can inhibit trypsin activity. Thermodynamic results revealed that both hydrogen bonds and hydrophobic interactions play main roles in stabilization of Ligupurpuroside B-trypsin complex. Circular dichroism (CD) results showed that the conformation of trypsin changed after bound to ligupurpuroside B. Molecular docking indicated that Ligupurpuroside B can enter the hydrophobic cavity of trypsin and was located near Trp215 and Tyr228 of trypsin. Communicated by Ramaswamy H. Sarma
Autonomic Symptoms in Gulf War Veterans Evaluated at the War Related Illness and Injury Study Center.

INTRODUCTION We characterized the presence of autonomic symptoms in a sample of Veterans with Gulf War Illness (GWI) using the Composite Autonomic Symptom Scale (COMPASS-31). In addition, we examined the report of autonomic symptoms across comorbid mental health conditions in this sample. MATERIALS AND METHODS Case-series follow-up of Gulf War veterans evaluated by the War Related Illness and Injury Study Center (WRIISC) between 2011 and 2016 (n = 153). Phone-based interview consisted of questionnaires designed to investigate autonomic symptoms, physical symptoms, mental health conditions, and GWI. Sixty-One Veterans agreed to participate in this follow-up arm of the study. We restricted our analysis to only those Veterans meeting CDC and/or Kansas criteria for GWI, leaving us with a sample of 56 Veterans. RESULTS Veterans in our sample were, male (n = 55, 98%), 49 (±6.8) years old and used 8 (±6.6) medications. The mean COMPASS-31 score for our sample was 45.6 (±18.3). There were no differences in reports of autonomic symptoms between participants who screened positive or negative for depression or post-traumatic stress disorder, but COMPASS-31 scores were higher among those who screened positive for anxiety (49.6 (±16.0)) compared with those who screened negative (29.3 (±18.9)) (p < 0.001). CONCLUSIONS The elevated COMPASS-31 scores suggest that there may be autonomic dysfunction present in our sample of Veterans with GWI, consistent with other published reports. Additionally, we believe that the high scores on the anxiety measure may reflect assessment of physiological symptoms that are not specific to anxiety, and may reflect GWI symptoms. Objective physiological tests of the autonomic nervous system are warranted to better characterize autonomic function and the clinical relevance of COMPASS-31 in this population.
Mediation of Debates with Dynamic Argumentative Behaviors

Mediation is a process for resolving conﬂicts among several entities. In argumentation debates, conﬂicting agents that may be organized as teams exchange arguments to persuade each other. In this paper, we consider an automated mediator, which assigns the speaking slots to agents so as to optimize some objectives and ensure the fairness of the debate. We propose a general setting where the argumentation strategies of the agents are probabilistically known and may evolve over time. We show that the problem can be solved as a semi-Markov decision problem with hidden modes.
Use of Bioelectrical Impedance Analysis for the Measurement of Appendicular Skeletal Muscle Mass/Whole Fat Mass and Its Relevance in Assessing Osteoporosis among Patients with Low Back Pain: A Comparative Analysis Using Dual X-ray Absorptiometry

Study Design Cross-sectional observational study. Purpose To compare measurements of appendicular skeletal muscle mass (ASMM) and whole fat mass (WFM) obtained using dualenergy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA) among patients with low back pain (LBP). Moreover, the study investigated the correlation between BIA-based ASMM and DXA-based bone mineral density (BMD). Overview of the Literature If reliable, BIA may be a useful alternative to DXA as a screening tool for sarcopenia and osteoporosis among patients with LBP. Methods Measurements were performed in 130 patients, including BMD of the lumbar spine and femoral neck. The correlation between DXA and BIA as well as between BIA-ASMM and BMD were evaluated. Results BIA and DXA were highly correlated in both male and female patients (r =0.73–0.90, p <0.0001). However, BIA consistently overestimated ASMM by 1.5–2.5 kg on an average (p <0.0001) and underestimated WFM (−4.0 to −2.7 kg) on an average (p <0.0001). BIA-based ASMM correlated with BMD of the lumbar spine in both male and female patients (r =0.28–0.37, p ≤0.02) and that of the femoral neck (r =0.34–0.51, p ≤0.005). Regarding the calculated skeletal muscle index (SMI: ASMM/height [m2]) used as a criterion for sarcopenia, BIA-based SMI correlated with BMD of the lumbar spine in male patients (r =0.44, p =0.0004) and that of the femoral neck in female patients (r =0.33, p =0.009). Conclusions BIA may be a favorable alternative to DXA as a screening tool for sarcopenia and osteoporosis among patients with LBP. Considering the overestimation of BIA-based ASMM and SMI, we recommend using the cutoff values for sarcopenia of 7.9 kg/m2 for males and 6.1 kg/m2 for females.
Poole–Frenkel emission on functionalized, multilayered-packed reduced graphene oxide nanoplatelets

The unique electronic, mechanical and optical properties of graphene make it a remarkable 2D material, widely explored in a plethora of applications. However, graphene zero-bandgap and the production of defect-free pristine graphene in large areas still limit some applications. To circumvent these issues, graphene-derived 2D materials have arisen as attractive candidates for low-dimensional systems, which requires a better comprehension of their properties. Here, we report a detailed investigation of the conduction mechanisms of two functionalized reduced graphene oxides (rGOs) nanoplatelets, named GPAH and GPSS. The functionalized rGO nanoplatelets were bottom-up assembled via the layer-by-layer technique, enabling molecular-level thickness control of nanostructures with well-defined composition and structure. For the reported multilayered GPAH/GPSS films the charge carriers followed Mott’s law, presenting a typical conduction behavior of 2D systems described by the Poole–Frenkel model. The multilayered GPAH/GPSS nanostructure presented a conductivity of 10–4 S cm−1, optical bandgap of ∼3.3 eV and a relative dielectric permittivity (εr) of 6.4. Temperature-dependent I–V measurements indicated a strong variation of εr below the critical temperature (TC = 237 K), associated with a high dipole reorientation in the formed GPAH/GPSS nanostructure. All these characteristics make the GPAH/GPSS nanocomposite attractive for graphene-oriented applications, such as electronic devices.
A “technology-smart” battery policy strategy for Europe

Batteries' inherent characteristics should inform policies The world market for battery and hybrid electric vehicles (EVs), including passenger cars, buses, and freight trucks, is growing rapidly. Currently, almost all lithium-ion (Li-ion) battery cells for EVs are produced by East Asian (Chinese, Japanese, and Korean) manufacturers. Meanwhile, the European automotive industry, among the largest in the world, generates 4% of European gross domestic product, and 12 million jobs (1); however, Europe houses less than 1% of the global Li-ion battery cell manufacturing capacity, and this production capability largely addresses niche markets. Manufacturing of batteries for EVs is thus at the center of industry policy discussions at the European Commission (EC), with calls for “European sovereignty” in Li-ion battery manufacturing (2). Here, we offer insights from battery research and innovation studies to suggest that catching up with East Asian companies is worthwhile, but can only be achieved step by step, by bringing competences to Europe through strategic global collaborations, supported by creation of an attractive European market for EVs.