gebhart/patrepeval huggingface dataset:
Learning Shape Representations for Clothing Variations in Person Re-Identification (2020)

Person re-identification (re-ID) aims to recognize instances of the same person contained in multiple images taken across different cameras. Existing methods for re-ID tend to rely heavily on the assumption that both query and gallery images of the same person have the same clothing. Unfortunately, this assumption may not hold for datasets captured over long periods of time (e.g., weeks, months or years). To tackle the re-ID problem in the context of clothing changes, we propose a novel representation learning model which is able to generate a body shape feature representation without being affected by clothing color or patterns. We call our model the Color Agnostic Shape Extraction Network (CASE-Net). CASE-Net learns a representation of identity that depends only on body shape via adversarial learning and feature disentanglement. Due to the lack of large-scale re-ID datasets which contain clothing changes for the same person, we propose two synthetic datasets for evaluation. We create a rendered dataset SMPL-reID with different clothes patterns and a synthesized dataset Div-Market with different clothing color to simulate two types of clothing changes. The quantitative and qualitative results across 5 datasets (SMPL-reID, Div-Market, two benchmark re-ID datasets, a cross-modality re-ID dataset) confirm the robustness and superiority of our approach against several state-of-the-art approaches
High-Sensitivity CMOS RF-DC Converter in HF RFID Band (2016)

In this letter, a fully-integrated RF-DC converter operating at the HF RFID working frequency (13.56 MHz) and realized in 350 nm CMOS technology is presented. It is based on a Dickson's rectifier, a Pelliconi's charge pump driven by a 50 kHz ring oscillator, and a voltage monitor. Mathematical model is developed and verified through simulations and measurements. Results show a sensitivity of -19 dBm with related output voltage of 0.5 V. Moreover, taking advantage from the internal voltage monitor, the suitability of the proposed architecture to pilot RFID-based sensor boards has been proved.
Model-Based Detection of Endobronchial Intubation (2006)

In Brief To detect endobronchial intubation (EBI) noninvasively in real time, we developed a novel, automated, lumped model-based approach. The model uses routinely monitored airway pressure and flow as inputs. The specificity of the method in detecting EBI was determined by testing events of stiff chest wall (SCW) in the absence of EBI. EBI was induced in 10 anesthetized, paralyzed, and mechanically ventilated mongrel dogs (19–45 kg) by advancing the endotracheal tube into the right mainstem bronchus. The event of SCW was created by wrapping a pressure cuff around the chest. Airway pressure and flow were continuously recorded at the mouth, and respiratory impedance was estimated from these signals. Model parameters were iteratively identified until the root mean square error between the respiratory and model-predicted impedance was minimum. The change in model parameters during EBI from baseline was analyzed. In nine of 10 cases, it was determined that during EBI, the model’s compliance element (C1) decreased ≥50% and model’s resistance element (R2) changed ≤10-fold from baseline. Testing this rule on 40 cases of SCW, four false positives were obtained. During SCW, R1 and R2 increased, whereas C2 decreased significantly from baseline. This preliminary study is a promising step toward noninvasive, real-time detection of EBI to aid clinicians in decision making. Implications: We describe a novel, automated, noninvasive, model-based approach to detect inadvertent endobronchial intubation within seconds of onset using airway pressure and flow signals.
Proteome-wide quantitative RNA interactome capture (qRIC) identifies phosphorylation sites with regulatory potential in RBM20 (2021)

Summary RNA-binding proteins (RBPs) are major regulators of gene expression at the post-transcriptional level. While many posttranslational modification sites in RBPs have been identified, little is known about how these modifications regulate RBP function. Here, we developed quantitative RNA-interactome capture (qRIC) to quantify the fraction of cellular RBPs pulled down with polyadenylated mRNAs. Applying qRIC to HEK293T cells quantified pull-down efficiencies of over 300 RBPs. Combining qRIC with phosphoproteomics allowed us to systematically compare pull-down efficiencies of phosphorylated and non-phosphorylated forms of RBPs. Over hundred phosphorylation events increased or decreased pull-down efficiency compared to the unmodified RBPs and thus have regulatory potential. Our data captures known regulatory phosphorylation sites in ELAVL1, SF3B1 and UPF1 and identifies new potentially regulatory sites. Follow-up experiments on the cardiac splicing regulator RBM20 revealed that multiple phosphorylation sites in the C-terminal disordered region affect nucleo-cytoplasmic localization, association with cytosolic RNA granules and alternative splicing. Together, we show that qRIC is a scalable method to identify functional posttranslational modification sites in RBPs. Highlights qRIC globally quantifies the fraction of RNA-binding proteins pulled down with mRNA Combining qRIC with phosphoproteomics identifies sites that affect RNA binding Phosphorylation sites in RBM20 regulate its function in splicing
Possible Use of the Radovan Tissue Expander in Hair Replacement Surgery (1985)

Inelastic scalps in patients with male pattern baldness tax the ingenuity of the dermatologic surgeon in executing a satisfactory donor site closure without tension and subsequent wound dehiscence. The Radovan tissue expander permits the scalp to stretch slowly and facilitates the reconstruction of large scalp defects. Two cases are presented, illustrating this technique and its complications of pressure necrosis and expander extrusion. It is believed that this represents a significant advance in the field of hair replacement surgery.
3D-Xpath (2018)

The advance of DRAM manufacturing technology slows down, whereas the density and performance needs of DRAM continue to increase. This desire has motivated the industry to explore emerging Non-Volatile Memory (e.g., 3D XPoint) and the high-density DRAM (e.g., Managed DRAM Solution). Since such memory technologies increase the density at the cost of longer latency, lower bandwidth, or both, it is essential to use them with fast memory (e.g., conventional DRAM) to which hot pages are transferred at runtime. Nonetheless, we observe that page transfers to fast memory often block memory channels from servicing memory requests from applications for a long period. This in turn significantly increases the high-percentile response time of latency-sensitive applications. In this paper, we propose a high-density managed DRAM architecture, dubbed 3D-XPath for applications demanding both low latency and high capacity for memory. 3D-XPath DRAM stacks conventional DRAM dies with high-density DRAM dies explored in this paper and connects these DRAM dies with 3D-XPath. Especially, 3D-XPath allows unused memory channels to service memory requests from applications when primary channels supposed to handle the memory requests are blocked by page transfers at given moments, considerably increasing the high-percentile response time. This can also improve the throughput of applications frequently copying memory blocks between kernel and user memory spaces. Our evaluation shows that 3D-XPath DRAM decreases high-percentile response time of latency-sensitive applications by ~30% while improving the throughput of an I/O-intensive applications by ~39%, compared with DRAM without 3D-XPath.
Electron transport in silicon inversion slabs of nanometric thickness (2005)

We study the electron transport in ultrathin silicon inversion layers with thickness in a range from 20nm down to 2nm by Monte Carlo simulation. Quantum effects are taken into account by simultaneously solving the Poisson and Schroedinger equations. Once the electron distribution in the silicon layer is known, the effect of a longitudinal electric field applied parallel to the silicon slab is studied. To do so, the Boltzmann transport equation is solved by the Monte Carlo method, and the electron mobility is evaluated. The influence of different scattering mechanisms has been analyzed. We show that two opposite effects appear on the electron mobility as the silicon thickness is reduced. On one hand the subband modulation effect, which contributes to an increase in the electron mobility. On the other hand, the greater confinement of the carriers as the silicon thickness decreases produces, as a consequence of the uncertainty principle, an increase of the phonon scattering rate, and therefore a decrease on the electron mobility. The superposition of these two opposite effects makes that electron mobility does not have a clear trend as the silicon slab thickness decreases.
Factors affecting the efficiency of Rhizobium rhizogenes root transformation of the root parasitic plant Triphysaria versicolor and its host Arabidopsis thaliana (2018)

Analyses of root transformation factors provides a method recovering transgenic roots from both parasitic plants and their hosts at high frequency. In addition to providing an effective in vitro approach for genetic investigations of parasitic plant-host plant interactions, these results are applicable to genetic studies of non-parasitic plants as well.
Exploring cell kinetic models within an integrated simulation environment (1996)

The understanding of the mechanisms controlling the normal (i.e. healthy) and abnormal (i.e. diseased) cell kinetic behaviour of epithelial tissues is a prerequisite for therapy. Complex control structures hierarchically organize the tissue&amp;apos;s steady state as well as tissue response to external influences. Insight into the controls which mediate this exquisitely fine and (mostly) stable tuning is sought in cell kinetic experiments. While the hypotheses, derived from experimental observations are often very vague, consisting of informal and qualitative descriptions, a mathematical modeler, trying to formalize the experimental results, needs precise and explicit information in terms of parameters, relations etc. In order to fill this gap between informal and formal knowledge, we describe a modelling approach in which qualitative models of the tissue structure and dynamics can be built. Based on this approach a specification of a modelling and simulation environment for rapid prototyping and execution of models of cell kinetic hypotheses will be presented, supporting different states of the biological experiment, e.g. pre-experimental planning, like exploration of relevant experimental parameters, post-experimental model exploration to find new hypotheses etc. The use of the modelling and simulation environment allows a qualitative judgement of hypotheses about the cell kinetic behavior and control mechanisms.
Semantics for probabilistic programming: higher-order functions, continuous distributions, and soft constraints (2016)

We study the semantic foundation of expressive probabilistic programming languages, that support higher-order functions, continuous distributions, and soft constraints (such as Anglican, Church, and Venture). We define a metalanguage (an idealised version of Anglican) for probabilistic computation with the above features, develop both operational and denotational semantics, and prove soundness, adequacy, and termination. They involve measure theory, stochastic labelled transition systems, and functor categories, but admit intuitive computational readings, one of which views sampled random variables as dynamically allocated read-only variables. We apply our semantics to validate nontrivial equations underlying the correctness of certain compiler optimisations and inference algorithms such as sequential Monte Carlo simulation. The language enables defining probability distributions on higher-order functions, and we study their properties.
In-situ Backpropagation in Photonic Neural Networks (2018)

Recently, integrated optics has gained interest as a hardware platform for implementing machine learning algorithms. Here, we introduce a method that enables highly efficient, in situ training of a photonic artificial neural network. We use the adjoint variable method to derive the photonic analogue of the backpropagation algorithm, which is the standard method for computing gradients for conventional neural networks. We further show how these gradients can be obtained exactly through intensity measurements inside the device. Beyond the training of photonic machine learning implementations, our method may also be of broad interest to experimental sensitivity analysis of photonic systems and the optimization of reconfigurable optics platforms.
Microbial life in the deep terrestrial subsurface (1988)

The distribution and function of microorganisms is a vital issue in microbial ecology. The US Department of Energy`s Program, ``Microbiology of the Deep Subsurface,`` concentrates on establishing fundamental scientific information about organisms at depth, and the use of these organisms for remediation of contaminants in deep vadose zone and groundwater environments. This investigation effectively extends the Biosphere hundreds of meters into the Geosphere and has implications to a variety of subsurface activities.
Characterization of a highly sensitive ultra-thin piezoresistive silicon cantilever probe and its application in gas flow velocity sensing (2002)

We present a highly sensitive ultra-thin micromachined silicon cantilever beam with an integrated strain gauge on its root for optimizing piezoresistive readout. The mechanical characteristics and electrical readout of the cantilever beam, such as spring constant, resonant frequencies and piezoresistive sensitivity, are theoretically given from the derived formulae or from finite element modeling. The results of characterization show reasonably good agreement between the experimental results and the theoretical values. As one of the applications, for the first time the fabricated silicon cantilever beams have been applied to measure airflow velocity distribution in a steel pipe with an inner diameter of 7.0 mm. The experimental piezoresistive sensitivity (Δ&lt;i&gt;R&lt;/i&gt;/&lt;i&gt;R&lt;/i&gt;)/&lt;i&gt;y&lt;/i&gt;(0) is in the range of 0.23–2.89 × 10−6 nm&lt;sup&gt;−1&lt;/sup&gt; in the beam bending tests, and the experimental flow sensitivity (Δ&lt;i&gt;R&lt;/i&gt;/&lt;i&gt;R&lt;/i&gt;)/&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;gas&lt;/sub&gt;&lt;sup&gt;2&lt;/sup&gt; is in the range of 0.652–4.489 × 10&lt;sup&gt;−5&lt;/sup&gt; (m s&lt;sup&gt;−1&lt;/sup&gt;)&lt;sup&gt;−2&lt;/sup&gt; in the airflow velocity tests. The experimental detectable minimum airflow velocity is 7.0 cm s&lt;sup&gt;−1&lt;/sup&gt;, which is comparable to that of a hot wire anemometer.
Power Noise Measurements of Cryptographic VLSI Circuits Regarding Side-Channel Information Leakage (2014)

Power supply noise waveforms within cryptographic VLSI circuits in a 65nm CMOS technology are captured by using an on-chip voltage waveform monitor (OCM). The waveforms exhibit the correlation of dynamic voltage drops to internal logical activities during Advance Encryption Standard (AES) processing, and causes side-channel information leakage regarding to secret key bytes. Correlation Power Analysis (CPA) is the method of an attack extracting such information leakage from the waveforms. The frequency components of power supply noise contributing the leakage are shown to be localized in an extremely low frequency region. The level of information leakage is strongly associated with the size of increment of dynamic voltage drops against the Hamming distance in the AES processing. The time window of significant importance where the leakage most likely happens is clearly designated within a single clock cycle in the final stage of AES processing. The on-chip power supply noise measurements unveil the facts about side-channel information leakage behind the traditional CPA with on-board sensing of power supply current through a resistor of 1 ohm.
Biased 2-3 trees (1980)

We describe a new data structure for maintaining collections of weighted items. The access time for an item of weight w in a collection of total weight W is proportional to log(W/w) in the worst case (which is optimal in a certain sense), and several other useful operations can be made to work just, as fast. The data structure is simpler than previous proposals, but the running time must be amortized over a sequence of operations to achieve the time bounds.
Stress Hormone-Related Psychopathology: Pathophysiological and Treatment Implications (2001)

Stress is commonly associated with a variety of psychiatric conditions, including major depression, and with chronic medical conditions, including diabetes and insulin resistance. Whether stress causes these conditions is uncertain, but plausible mechanisms exist by which such effects might occur. To the extent stress-induced hormonal alterations (e.g., chronically elevated cortisol levels and lowered dehydroepiandrosterone [DHEA] levels) contribute to psychiatric and medical disease states, manipulations that normalize these hormonal aberrations should prove therapeutic. In this review, we discuss mechanisms by which hormonal imbalance (discussed in the frameworks of "allostatic load" and "anabolic balance") might contribute to illness. We then review certain clinical manifestations of such hormonal imbalances and discuss pharmacological and behavioural treatment strategies aimed at normalizing hormonal output and lessening psychiatric and physical pathology.
Bacteriological and chemical changes occurring in Bunker-stored silage covered with biodegradable coating (2006)

Results emphasize the possibility of the use of a biodegradable coating as an alternative to plastic film for sealing horizontal bunker silos.
The Impact of Draping Effects on the Stiffness and Failure Behavior of Unidirectional Non-Crimp Fabric Fiber Reinforced Composites (2020)

Unidirectional non-crimp fabrics (UD-NCF) are often used to exploit the lightweight potential of continuous fiber reinforced plastics (CoFRP). During the draping process, the UD-NCF fabric can undergo large deformations that alter the local fiber orientation, the local fiber volume content (FVC) and create local fiber waviness. Especially the FVC is affected and has a large impact on the mechanical properties. This impact, resulting from different deformation modes during draping, is in general not considered in composite design processes. To analyze the impact of different draping effects on the mechanical properties and the failure behavior of UD-NCF composites, experimental results of reference laminates are compared to the results of laminates with specifically induced draping effects, such as non-constant FVC and fiber waviness. Furthermore, an analytical model to predict the failure strengths of UD laminates with in-plane waviness is introduced. The resulting stiffness and strength values for different FVC or amplitude to wavelength configurations are presented and discussed. In addition, failure envelopes based on the PUCKmathsizesmall failure criterion for each draping effect are derived, which show a clear specific impact on the mechanical properties. The findings suggest that each draping effect leads to a "new fabric" type. Additionally, analytical models are introduced and the experimental results are compared to the predictions. Results indicate that the models provide reliable predictions for each draping effect. Recommendations regarding necessary tests to consider each draping effect are presented. As a further prospect the resulting stiffness and strength values for each draping effect can be used for a more accurate prediction of the structural performance of CoFRP parts.
European Respiratory Society Annual Congress 2013 (2013)

Number: 6020 Publication Number: YI03 Abstract Group: 3.3. Mechanisms of Lung Injury and Repair
ChemInform Abstract: X‐RAY STRUCTURAL CHARACTERIZATION AND CATALYTIC PROPERTIES OF HYDRIDOBIS(4,5‐BIS((DIPHENYLPHOSPHINO)METHYL)‐2,2‐DIMETHYL‐1,3‐DIOXOLANE)RHODIUM(I) (1981)

Abstract Die Titelverbindung (I) mit dem (+)‐4S,5S‐konfigurierten Liganden wird röntgenographisch untersucht.
A high-sensitivity micromachined biosensor (1997)

The Force Amplified Biological Sensor (FABS) is a desktop or portable instrument currently under development at the Naval Research Laboratory. FABS will use a rapid, automated immunoassay to detect analytes such as proteins, viruses, and bacteria. The assay uses forces produced by micron-sized magnetic particles to pull on antibody-antigen bonds. Microfabricated piezoresistive cantilevers measure the resulting piconewton-level forces with sufficient sensitivity to detect single antibody-antigen bonds. These forces also serve to characterize the bonds, allowing FABS to distinguish specific antibody-antigen bonds from nonspecific interactions.
Dynamic evaluation of autofocusing for automated microscopic analysis of blood smear and pap smear (2007)

Autofocusing is a fundamental procedure towards automated microscopic evaluation of blood smear and pap smear samples for clinical diagnosis. This paper presents comparison results of 16 selected focus algorithms based on 8000 static bright-field images and 1600 dynamic autofocusing trials using 10 blood smear and pap smear samples. Besides static behaviour, dynamic autofocusing performance is introduced for ranking the 16 focus algorithms. The Fibonacci search algorithm is employed for controlling the z-motor of the microscope to reach the focus position that is determined by focus objective functions. Experimental results demonstrate that the variance algorithm provides the best overall performance. Together with our previously reported findings, it is demonstrated that the variance algorithm or the normalized variance algorithm is the optimal focus algorithm for non-fluorescence microscopy applications including pap smear and blood smear imaging.
CD1d ligation on human monocytes directly signals rapid NF-κB activation and production of bioactive IL-12 (2005)

Natural killer T cells (NKT cells) expressing a semi-invariant CD1d-reactive T cell receptor (invariant NKT, iNKT) can be rapidly activated by monocytes or immature dendritic cells (iDCs) bearing a CD1d-presented glycolipid antigen and can in turn stimulate these myeloid cells to mature and produce IL-12. Previous studies have shown that iNKT-produced IFNgamma and CD40 ligand contribute to this dendritic cell maturation. This study demonstrates that CD1d ligation alone, in the absence of iNKT, could rapidly (within 24 h) stimulate production of bioactive IL-12p70 by CD1d+ human peripheral blood monocytes as well as iDCs. IFNgamma alone had no effect, but it markedly enhanced CD1d-stimulated IL-12 production. Monocyte differentiation, as assessed by CD40 and CD1a up-regulation, was also accelerated by CD1d stimulation, consistent with this representing a physiological response. CD1d ligation on the human monocytic cell line THP-1 similarly specifically stimulated IL-12 production. Biochemical studies showed that IL-12 release correlated with rapid phosphorylation of IkappaB, a critical step in NF-kappaB activation. Selective NF-kappaB inhibition blocked this CD1d-stimulated IL-12 production. Finally, CD1d ligation could also enhance IL-12 production in the presence of suboptimal LPS or CD40 stimulation. These findings demonstrate an innate immune signaling function for CD1d and provide a mechanism for the rapid activation of monocytes and iDCs by CD1d-reactive T cells.