Miracle-dz/UniFAR-FTUs huggingface dataset:
Head Pose Estimation Based on Multivariate Label Distribution

Accurate ground truth pose is essential to the training of most existing head pose estimation algorithms. However, in many cases, the "ground truth" pose is obtained in rather subjective ways, such as asking the human subjects to stare at different markers on the wall. In such case, it is better to use soft labels rather than explicit hard labels. Therefore, this paper proposes to associate a multivariate label distribution (MLD) to each image. An MLD covers a neighborhood around the original pose. Labeling the images with MLD can not only alleviate the problem of inaccurate pose labels, but also boost the training examples associated to each pose without actually increasing the total amount of training examples. Two algorithms are proposed to learn from the MLD by minimizing the weighted Jeffrey's divergence between the predicted MLD and the ground truth MLD. Experimental results show that the MLD-based methods perform significantly better than the compared state-of-the-art head pose estimation algorithms.
A topological comparison of PWM and hysteresis controls in switching audio amplifiers

The switching audio amplifiers are widely used in various portable and consumer electronics because of their high efficiency, but suffer from low audio performances due to inherent nonlinearity. This problem can be limited with efficient feedback from the output power stage. The research community focuses now to the efficient error correction by feedback control systems. This paper proposes a theoretical and practical comparison between the PWM control and our proposed hysteresis solution. These topologies are widely used in a very wide range of applications. This work shows that the hysteresis solution offers both lower power consumption and higher audio performances for embedded audio application.
Prognostic Significance of the Long Pentraxin PTX3 in Acute Myocardial Infarction

Background—Inflammation has a pathogenetic role in acute myocardial infarction (MI). Pentraxin-3 (PTX3), a long pentraxin produced in response to inflammatory stimuli and highly expressed in the heart, was shown to peak in plasma ≈7 hours after MI. The aim of this study was to assess the prognostic value of PTX3 in MI compared with the best-known and clinically relevant biological markers. Methods and Results—In 724 patients with MI and ST elevation, PTX3, C-reactive protein (CRP), creatine kinase (CK), troponin T (TnT), and N-terminal pro-brain natriuretic peptide (NT-proBNP) were assayed at entry, a median of 3 hours, and the following morning, a median of 22 hours from symptom onset. With respect to outcome events occurring over 3 months after the index event, median PTX3 values were 7.08 ng/mL in event-free patients, 16.12 ng/mL in patients who died, 9.12 ng/mL in patients with nonfatal heart failure, and 6.88 ng/mL in patients with nonfatal residual ischemia (overall P<0.0001). Multivariate analysis including CRP, CK, TnT, and NT-proBNP showed that only age ≥70 years (OR, 2.11; 95% CI, 1.04 to 4.31), Killip class >1 at entry (OR, 2.20; 95% CI, 1.14 to 4.25), and PTX3 (>10.73 ng/mL) (OR, 3.55; 95% CI, 1.43 to 8.83) independently predicted 3-month mortality. Biomarkers predicting the combined end point of death and heart failure in survivors were the highest tertile of PTX3 and of NT-proBNP and a CK ratio >6. Conclusions—In a representative contemporary sample of patients with MI with ST elevation, the acute-phase protein PTX3 but not the liver-derived short pentraxin CRP or other cardiac biomarkers (NT-proBNP, TnT, CK) predicted 3-month mortality after adjustment for major risk factors and other acute-phase prognostic markers.
Centrin plays an essential role in microtubule severing during flagellar excision in Chlamydomonas reinhardtii

Previously, we reported that flagellar excision in Chlamydomonas reinhardtii is mediated by an active process whereby microtubules are severed at select sites within the flagellar-basal body transition zone (Sanders, M. A., and J. L. Salisbury. 1989. J. Cell Biol. 108:1751- 1760). At the time of flagellar excision, stellate fibers of the transition zone contract and displace the microtubule doublets of the axoneme inward. The resulting shear force and torsional load generated during inward displacement leads to microtubule severing immediately distal to the central cylinder of the transition zone. In this study, we have used a detergent-extracted cell model of Chlamydomonas that allows direct experimental access to the molecular machinery responsible for microtubule severing without the impediment of the plasma membrane. We present four independent lines of experimental evidence for the essential involvement of centrin-based stellate fibers of the transition zone in the process of flagellar excision: (a) Detergent-extracted cell models excise their flagella in response to elevated, yet physiological, levels of free calcium. (b) Extraction of cell models with buffers containing the divalent cation chelator EDTA leads to the disassembly of centrin-based fibers and to the disruption of transition zone stellate fiber structure. This treatment results in a complete loss of flagellar excision competence. (c) Three separate anti-centrin monoclonal antibody preparations, which localize to the stellate fibers of the transition zone, specifically inhibit contraction of the stellate fibers and block calcium-induced flagellar excision, while control antibodies have no inhibitory effect. Finally, (d) cells of the centrin mutant vfl-2 (Taillon, B., S. Adler, J. Suhan, and J. Jarvik. 1992. J. Cell Biol. 119:1613-1624) fail to actively excise their flagella following pH shock in living cells or calcium treatment of detergent-extracted cell models. Taken together, these observations demonstrate that centrin-based fiber contraction plays a fundamental role in microtubule severing at the time of flagellar excision in Chlamydomonas.
Pattern Recognition by Self-Organizing Neural Networks

From the Publisher: Pattern Recognition by Self-Organizing Neural Networks presents the most recent advances in an area of research that is becoming vitally important in the fields of cognitive science, neuroscience, artificial intelligence, and neural networks in general. The 20 articles take up developments in competitive learning and computational maps, adaptive resonance theory, and specialized architectures and biological connections.
Genome-wide identification and transcriptional expression analysis of mitogen-activated protein kinase and mitogen-activated protein kinase kinase genes in Capsicum annuum

The tripartite mitogen-activated protein kinase (MAPK) signaling cascades have been implicated in plant growth, development, and environment adaptation, but a comprehensive understanding of MAPK signaling at genome-wide level is limited in Capsicum annuum. Herein, genome-wide identification and transcriptional expression analysis of MAPK and MAPK kinase (MAPKK) were performed in pepper. A total of 19 pepper MAPK (CaMAPKs) genes and five MAPKK (CaMAPKKs) genes were identified. Phylogenetic analysis indicated that CaMAPKs and CaMAPKKs could be classified into four groups and each group contains similar exon-intron structures. However, significant divergences were also found. Notably, five members of the pepper MAPKK family were much less conserved than those found in Arabidopsis, and 9 Arabidopsis MAPKs did not have orthologs in pepper. Additionally, 7 MAPKs in Arabidopsis had either two or three orthologs in the pepper genome, and six pepper MAPKs and one MAPKK differing in sequence were found in three pepper varieties. Quantitative real-time RT-PCR analysis showed that the majority of MAPK and MAPKK genes were ubiquitously expressed and transcriptionally modified in pepper leaves after treatments with heat, salt, and Ralstonia solanacearum inoculation as well as exogenously applied salicylic acid, methyl jasmonate, ethephon, and abscisic acid. The MAPKK-MAPK interactome was tested by yeast two-hybrid assay, the results showed that one MAPKK might interact with multiple MAPKs, one MAPK might also interact with more than one MAPKKs, constituting MAPK signaling networks which may collaborate in transmitting upstream signals into appropriate downstream cellular responses and processes. These results will facilitate future functional characterization of MAPK cascades in pepper.
Adrenal Gland: Chemically Induced Structural and Functional Changes in the Cortex

The adrenal cortex is the target of a surprisingly large number of exogenous chemicals. Until recently, the toxic action of these chemicals was discovered serendipitously. Following our observations that acrylonitrile, cysteamine or pyrazole induces hemorrhagic adrenocortical necrosis in the rat, we recently recognized a structure-activity correlation which predicts the adrenocorticolytic property of alkyl chemicals, i.e., 2–3 carbons with double or triple bonds and with nucleophilic terminal radicals (e.g., -CN, -SH, -NH2). On the basis of our results obtained with electron microscopic, histochemical and biochemical studies as well as those of others, we propose the following sequence of events in the pathogenesis of chemically induced adrenocortical necrosis: 1) Depletion of glutathione and increased dopamine concentration in the adrenals; 2) Endothelial damage and rupture of capillary walls in the adrenal cortex due to either direct attack by the chemicals (metabolites) and/or released monoamines; 3) Retrograde embolization of medullary tissue fragments into the cortical capillaries; 4) Enhanced destruction of cortical vascular walls with subsequent platelet aggregation, fibrin deposition which is of ten associated with a systemic drop in platelet counts, and changes in blood coagulation; 5) Escape of plasma and cellular elements of blood into extravascular spaces and damage of adrenocortical parenchymal cells; and 6) Hemorrhage and necrosis in the adrenal cortex. This pathogenetic sequence was investigated in detail with acrylonitrile, and studied in various aspects with thioguanine, cysteamine and pyrazole.
Measuring the Quality of Pronunciation Dictionaries

In this paper we investigate measures for the evaluation of pronunciation dictionaries that can be used independently of the type of lexicon, the language, a specific recognizer and how the dictionary was generated. We will describe statistical measures, measures based on information theory and performance measures and give examples how these measures can be practically applied in supervision of data-driven dictionary training, selection of pronunciation variants and evaluation of the consistency of different dictionaries. Although the introduced measures are independent of the type of dictionary, we only report results obtained with a datadriven dictionary generation and do not address measures specific to rule-based approaches.
Round-the-year based network reinforcement solution generator

In this paper a round-the-year based network reinforcement solution generator for the transmission expansion planning problem is proposed. The solution generator makes use of a round-the-year network security analysis which combines zonal market simulations with load flow calculations. This allows a robust evaluation of the reinforcement candidates as all the hours in the year are considered. The solver iterates sequentially over possible reinforcements until no more congestion occurs in the grid, under both normal and N-1 branch outage situations. New criteria for assessing the grid congestion level are defined and used in the evaluation of candidates. The decrease in the proposed "grid severity index" is used to measure the effectiveness of each reinforcement candidate. At the end of the process, an ordered list of reinforcements is given together with the criteria values at each reinforcement step. The New England IEEE test system is used for validating the method.
A Note on the Impact of Law Enforcement Design on Legal Compliance and Avoidance

This exploratory note presents experimental evidence on how the design of law enforcement impacts legal compliance and detection avoidance. The experiment varies the enforcer's identity and the use of fine revenue. The data show that the level of detection avoidance is indeed influenced by the design of law enforcement. There also are observable differences in legal compliance across treatments, but they are not statistically significant.
An Evolutionary Study of Linux Memory Management for Fun and Profit

We present a comprehensive and quantitative study on the development of the Linux memory manager. The study examines 4587 committed patches over the last five years (2009-2015) since Linux version 2.6. 32. Insights derived from this study concern the development process of the virtual memory system, including its patch distribution and patterns, and techniques for memory optimizations and semantics. Specifically, we find that the changes to memory manager are highly centralized around the key functionalities, such as memory allocator, page fault handler and memory resource controller. The well-developed memory manager still suffers from increasing number of bugs unexpectedly. And the memory optimizations mainly focus on data structures, memory policies and fast path. To the best of our knowledge, this is the first such study on the virtual memory system.
Non-Invasive Ventilation (NIV) and Homeostatic Model Assessment (HOMA) Index in Stable Chronic Obstructive Pulmonary Disease (COPD) Patients with Chronic Hypercapnic Respiratory Failure: A Pilot Study

Abstract The effects of Non-invasive Ventilation (NIV) on Insulin Resistance (IR) in stable Chronic Obstructive Pulmonary Disease (COPD) patients have not been fully explored. The aim of this study was to assess the effects of NIV on IR and adiponectin levels during one year application of NIV in stable COPD patients with Chronic Hypercapnic Respiratory Failure. Twenty-five (25) stable COPD patients with Chronic Hypercapnic Respiratory Failure and with no self-reported comorbidities completed the study. NIV was administered in the spontaneous/timed mode via a full face mask using a bi-level positive airway pressure system. Spirometry, blood pressure, arterial blood gases, dyspnea, daytime sleepiness, serum fasting glucose and insulin levels were assessed. IR was assessed with the calculation of the Homeostatic Model Assessment (HOMA) index. Adiponectin was measured with radioimmunoassay. Study participants were re-evaluated on the first, third, sixth, ninth and twelfth month after the initial evaluation. There was a significant improvement in FEV1 values from the first month (34.1 ± 11.6% vs 37 ± 12.3%, p = 0.05). There was a significant decrease in IR by the ninth month of NIV use (3.4 ± 2.3 vs 2.2 ± 1.4, p < 0.0001), while adiponectin levels significantly improved from the first month of NIV use. Stepwise regression analysis revealed that baseline HOMA index was associated with paCO2 (⇓ = 0.07 ± 0.02, p = 0.001), while baseline adiponectin levels were associated with FVC (⇓ = 0.05 ± 0.02, p = 0.035) and the concentration of serum bicarbonate (HCO3-) (-⇓ = 0.18 ± 0.06, p = 0.002). Insulin sensitivity and glucose metabolism as well as adiponectin levels improved along with the improvements in respiratory failure.
Algorithmic Stability and Generalization Performance

We present a novel way of obtaining PAC-style bounds on the generalization error of learning algorithms, explicitly using their stability properties. A stable learner is one for which the learned solution does not change much with small changes in the training set. The bounds we obtain do not depend on any measure of the complexity of the hypothesis space (e.g. VC dimension) but rather depend on how the learning algorithm searches this space, and can thus be applied even when the VC dimension is infinite. We demonstrate that regularization networks possess the required stability property and apply our method to obtain new bounds on their generalization performance.
Heterogeneous Stock Mice are Susceptible to Encephalomyelitis and Antibody‐initiated Arthritis but not to Collagen‐ and G6PI‐induced Arthritis

The strategy of using heterogeneous stock (HS) mice has proven to be successful in fine mapping of quantitative trait loci in complex diseases. However, whether these mice can be used for arthritis, encephalomyelitis and autoimmune phenotypes has not been addressed. Here, we screened the Northport HS mice for arthritis phenotypes using three different models: collagen‐induced arthritis (CIA), using rat, bovine or chicken collagen type II (CII); recombinant human glucose‐6‐phosphate isomerase (G6PI)‐induced arthritis; and collagen antibody–induced arthritis (CAIA). Irrespective of the origin of collagen, we found HS mice to be fairly resistant to CIA and G6PI‐induced arthritis, despite the development of antibodies against the respective antigens. On the other hand, HS mice were found to be susceptible for CAIA. Similarly, these mice developed encephalomyelitis (EAE) induced either with mouse or rat spinal cord homogenate (SCH), or with recombinant rat myelin oligodendrocyte glycoprotein, with elevated antibody levels against CNS proteins. Accordingly, we conclude that the use of HS mice for fine mapping and positional cloning of gene(s) involved in CAIA and EAE is possible, but not for collagen‐ and G6PI‐induced arthritis.
Clinical neurocardiology defining the value of neuroscience‐based cardiovascular therapeutics

The autonomic nervous system regulates all aspects of normal cardiac function, and is recognized to play a critical role in the pathophysiology of many cardiovascular diseases. As such, the value of neuroscience‐based cardiovascular therapeutics is increasingly evident. This White Paper reviews the current state of understanding of human cardiac neuroanatomy, neurophysiology, pathophysiology in specific disease conditions, autonomic testing, risk stratification, and neuromodulatory strategies to mitigate the progression of cardiovascular diseases.
Potentiation of Fc∈ Receptor I–Activated Ca2+ Current (ICRAC) by Cholera Toxin

Antigen-evoked influx of extracellular Ca2+ into mast cells may occur via store-operated Ca2+ channels called calcium release–activated calcium (CRAC) channels. In mast cells of the rat basophilic leukemia cell line (RBL-2H3), cholera toxin (CT) potentiates antigen-driven uptake of 45Ca2+ through cAMP-independent means. Here, we have used perforated patch clamp recording at physiological temperature to test whether cholera toxin or its substrate, Gs, directly modulates the activity of CRAC channels. Cholera toxin dramatically amplified (two- to fourfold) the Ca2+ release–activated Ca2+ current (ICRAC) elicited by suboptimal concentrations of antigen, without itself inducing ICRAC, and this enhancement was not mimicked by cAMP elevation. In contrast, cholera toxin did not affect the induction of ICRAC by thapsigargin, an inhibitor of organelle Ca2+ pumps, or by intracellular dialysis with low Ca2+ pipette solutions. Thus, the activity of CRAC channels is not directly controlled by cholera toxin or Gsα. Nor was the potentiation of ICRAC due to enhancement of phosphoinositide hydrolysis or calcium release. Because Gs and the A subunit of cholera toxin bind to ADP ribosylation factor (ARF) and could modulate its activity, we tested the sensitivity of antigen-evoked ICRAC to brefeldin A, an inhibitor of ARF-dependent functions, including vesicle transport. Brefeldin A blocked the enhancement of antigen-evoked ICRAC without inhibiting ADP ribosylation of Gsα, but it did not affect ICRAC induced by suboptimal antigen or by thapsigargin. These data provide new evidence that CRAC channels are a major route for Fc∈ receptor I–triggered Ca2+ influx, and they suggest that ARF may modulate the induction of ICRAC by antigen.
Automating Network Application Dependency Discovery: Experiences, Limitations, and New Solutions

Large enterprise networks consist of thousands of services and applications. The performance and reliability of any particular application may depend on multiple services, spanning many hosts and network components. While the knowledge of such dependencies is invaluable for ensuring the stability and efficiency of these applications, thus far the only proven way to discover these complex dependencies is by exploiting human expert knowledge, which does not scale with the number of applications in large enterprises. Recently, researchers have proposed automated discovery of dependencies from network traffic [8, 18]. In this paper, we present a comprehensive study of the performance and limitations of this class of dependency discovery techniques (including our own prior work), by comparing with the ground truth of five dominant Microsoft applications. We introduce a new system, Orion, that discovers dependencies using packet headers and timing information in network traffic based on a novel insight of delay spike based analysis. Orion improves the state of the art significantly, but some shortcomings still remain. To take the next step forward, Orion incorporates external tests to reduce errors to a manageable level. Our results show Orion provides a solid foundation for combining automated discovery with simple testing to obtain accurate and validated dependencies.
Structure Identification of a Prenylflavonol Glycoside from Epimedium koreanum by Electrospray Ionization Tandem Mass Spectrometry

A novel prenylflavonol glycoside, named acetylicariin, has been isolated from the aerial parts of Epimedium koreanum Nakai. The structure has been identified by electrospray ionization multi-stage tandem mass spectrometry (ESI-MS^n) and other chemical evidence, which has been elucidated as 8-prenylkaempferol-42-methoxyl-3-0-a-L-rhamnopyranosyl-7-O-β-D-(23- O -acetyl)glucopyranoside.
Automatic Scoring of Children’s Read-Aloud Text Passages and Word Lists

Assessment of reading proficiency is typically done by asking subjects to read a text passage silently and then answer questions related to the text. An alternate approach, measuring reading-aloud proficiency, has been shown to correlate well with the aforementioned common method and is used as a paradigm in this paper. We describe a system that is able to automatically score two types of children's read speech samples (text passages and word lists), using automatic speech recognition and the target criterion "correctly read words per minute". Its performance is dependent on the data type (passages vs. word lists) as well as on the relative difficulty of passages or words for individual readers. Pearson correlations with human assigned scores are around 0.86 for passages and around 0.80 for word lists.