gebhart/patrepeval huggingface dataset:
Assessment of a Spatiotemporal Deep Learning Approach for Soil Moisture Prediction and Filling the Gaps in Between Soil Moisture Observations (2021)

Soil moisture (SM) plays a significant role in determining the probability of flooding in a given area. Currently, SM is most commonly modeled using physically-based numerical hydrologic models. Modeling the natural processes that take place in the soil is difficult and requires assumptions. Besides, hydrologic model runtime is highly impacted by the extent and resolution of the study domain. In this study, we propose a data-driven modeling approach using Deep Learning (DL) models. There are different types of DL algorithms that serve different purposes. For example, the Convolutional Neural Network (CNN) algorithm is well suited for capturing and learning spatial patterns, while the Long Short-Term Memory (LSTM) algorithm is designed to utilize time-series information and to learn from past observations. A DL algorithm that combines the capabilities of CNN and LSTM called ConvLSTM was recently developed. In this study, we investigate the applicability of the ConvLSTM algorithm in predicting SM in a study area located in south Louisiana in the United States. This study reveals that ConvLSTM significantly outperformed CNN in predicting SM. We tested the performance of ConvLSTM based models by using a combination of different sets of predictors and different LSTM sequence lengths. The study results show that ConvLSTM models can predict SM with a mean areal Root Mean Squared Error (RMSE) of 2.5% and mean areal correlation coefficients of 0.9 for our study area. ConvLSTM models can also provide predictions between discrete SM observations, making them potentially useful for applications such as filling observational gaps between satellite overpasses.
Gliadin fragments promote migration of dendritic cells (2010)

In genetically predisposed individuals, ingestion of wheat gliadin provokes a T-cell-mediated enteropathy, celiac disease. Gliadin fragments were previously reported to induce phenotypic maturation and Th1 cytokine production by human dendritic cells (DCs) and to boost their capacity to stimulate allogeneic T cells. Here, we monitor the effects of gliadin on migratory capacities of DCs. Using transwell assays, we show that gliadin peptic digest stimulates migration of human DCs and their chemotactic responsiveness to the lymph node-homing chemokines CCL19 and CCL21. The gliadin-induced migration is accompanied by extensive alterations of the cytoskeletal organization, with dissolution of adhesion structures, podosomes, as well as up-regulation of the CC chemokine receptor (CCR) 7 on cell surface and induction of cyclooxygenase (COX)-2 enzyme that mediates prostaglandin E2 (PGE₂) production. Blocking experiments confirmed that gliadin-induced migration is independent of the TLR4 signalling. Moreover, we showed that the α-gliadin-derived 31-43 peptide is an active migration-inducing component of the digest. The migration promoted by gliadin fragments or the 31-43 peptide required activation of p38 mitogen-activated protein kinase (MAPK). As revealed using p38 MAPK inhibitor SB203580, this was responsible for DC cytoskeletal transition, CCR7 up-regulation and PGE₂ production in particular. Taken together, this study provides a new insight into pathogenic features of gliadin fragments by demonstrating their ability to promote DC migration, which is a prerequisite for efficient priming of naive T cells, contributing to celiac disease pathology.
Parallel distributed Bayesian detection with privacy constraints (2014)

In this paper, the privacy problem of a parallel distributed detection system vulnerable to an eavesdropper is proposed and studied in the Bayesian formulation. The privacy risk is evaluated by the detection cost of the eavesdropper which is assumed to be informed and greedy. It is shown that the optimal detection strategy of the sensor whose decision is eavesdropped on is a likelihood-ratio test. This fundamental insight allows for the optimization to reuse known algorithms extended to incorporate the privacy constraint. The trade-off between the detection performance and privacy risk is illustrated in a numerical example. The incorporation of physical layer privacy in the system design will lead to trustworthy sensor networks in future.
Midfoot Degenerative Arthritis and Partial Fusion After Pediatric Lisfranc Fracture-Dislocation (2018)

We present a case of a 10-year-old girl who sustained a Lisfranc fracture-dislocation after an all-terrain vehicle accident. She underwent open reduction and internal fixation with smooth Kirschner wires. At 5-year follow-up, she had developed functional pain and radiographic evidence of degenerative arthritis and partial fusion of her midfoot. There are several possible explanations for this outcome, including loss of reduction, traumatic or iatrogenic physeal injury, and severity of initial injury. Long-term outcomes in children with Lisfranc injuries are not well described. Our case may begin to shed light on the natural history of these injuries in the pediatric population, with the consideration of potential treatment implications and pitfalls.
Analyzing the influence of contact-induced quenching processes on F&#246;rster resonance energy transfer (2007)

Experiments based on F&ouml;rster resonance energy transfer (FRET) are widely used to obtain information on conformational dynamics of biomolecular systems. To reliably measure FRET, accurate knowledge of photophysical properties of the used fluorophores is indispensable. In high FRET constructs donor (D) and acceptor (A) fluorophores can approach each other close enough that electronic interactions might occur. When separated by distances on the order of van der Waals radii, photophysical properties can be changed reversibly, opening new non-radiative relaxation pathways, or irreversibly, chemically altering the fluorophores. Even transient contacts can thus compromise accurate FRET measurements. To study FRET and competing D-A contact-induced processes we labeled the amino acid cystein (Cys) with two fluorophores. A donor (D; TMR or Cy3B) was attached to the thiol group and an acceptor (A; Atto647N) to the amino group of Cys. Absorption spectroscopy, steady-state fluorescence spectroscopy, and time-correlated single-photon counting (TCSPC) were used to characterize the different A-Cys-D complexes at the ensemble level. In addition, we performed single-molecule FRET experiments using alternating-laser excitation to study the heterogeneity of the FRET-systems. We identified competing quenching processes severely changing D and A quantum yields upon fluorophore contact. The results are applicable for quantitative analysis of FRET in dynamic molecular systems that allow transient contact between D and A fluorophores.
High-speed ultra-accurate direct C2W bonding (2020)

Chip-to-wafer hybrid bonding is needed as contact pitch and pad size decrease to the single micrometer range (5 micrometer or lower). Here, classical bonding technologies like themo-compression bonding and flip-chip with mass reflow are no longer sufficient, and hybrid bonding emerges as an attractive alternative. While the technology is well known in wafer-to-wafer processing, for chip-to-wafer at industrial speed and accuracy, new placement technologies and deeper understanding of accuracy behavior during the bonding process both are essential. This paper describes new optical recognition methods for small pads for accurate in-situ alignment before the bonding stroke as well as a new bond-head design and behavior for accurate placement at 200 nm at each point of the die, including large dies, and at speeds of 2000 units per hour.
Geometric distribution of chordae tendineae: an important anatomic feature in mitral valve function. (2000)

Based on triangular structures involving the basal and marginal chordae, a compensatory mechanism was described which explains how the severity of mitral regurgitation can vary following PM displacement. Basal chordae provide a constant connection between the annulus and papillary muscles, while marginal chordae maintain marginal leaflet flexibility, governing proper valve closure. This study relates chordal distribution to normal valve function, and provides a better understanding of breakdown in valve function under pathophysiological conditions.
Investigation of transverse oscillation method (2006)

Conventional ultrasound scanners can display only the axial component of the blood velocity vector, which is a significant limitation when vessels nearly parallel to the skin surface are scanned. The transverse oscillation (TO) method overcomes this limitation by introducing a TO and an axial oscillation in the pulse echo field. The theory behind the creation of the double oscillation pulse echo field is explained as well as the theory behind the estimation of the vector velocity. A parameter study of the method is performed, using the ultrasound simulation program Field II. A virtual linear-array transducer with center frequency 7 MHz and 128 active elements is created, and a virtual blood vessel of radius 6.4 mm is simulated. The performance of the TO method is found around an initial point in the parameter space. The parameters varied are: flow angle, transmit focus depth, receive apodization, pulse length, transverse wave length, number of emissions, signal-to-noise ratio (SNR), and type of echo-canceling filter used. Using an experimental scanner, the performance of the TO method is evaluated. An experimental flowrig is used to create laminar parabolic flow in a blood mimicking fluid, and the fluid is scanned under different flow-to-beam angles. The relative standard deviation on the transverse velocity estimate is found to be less than 10% for all angles between 50 degrees and 90 degrees. Furthermore, the TO method is evaluated in the flowrig using pulsatile flow, which resembles the flow in the femoral artery. The estimated volume flow as a function of time is compared to the volume flow derived from a conventional axial method at a flow-to-beam angle of 60 degrees. It is found that the method is highly sensitive to the angle between the flow and the beam direction. Also, the choice of echo canceling filter affects the performance significantly.
Supplementary Figure 3 from Differentiation Syndrome with Ivosidenib and Enasidenib Treatment in Patients with Relapsed or Refractory IDH-Mutated AML: A U.S. Food and Drug Administration Systematic Analysis (2023)

&lt;p&gt;Supplementary Figure 3. Blood count trajectory for patients with or without DS.&lt;/p&gt;
Abnormalities of CSF flow patterns in the cerebral aqueduct in treatment‐resistant late‐life depression: A potential biomarker of microvascular angiopathy (2006)

There is growing evidence that microvascular angiopathy (MVA) plays an important role in the development of dementia and affective disorders in older people. At currently available image resolutions it is not possible to image directly the vascular changes associated with MVA, but the effects on blood and cerebrospinal fluid (CSF) flow may be detectable. The aim of this study was to investigate a potential biomarker for MVA based on MRI of abnormalities in CSF flow. Since there is considerable indirect evidence that treatment resistance in late-onset depressive disorder is related to MVA, we assessed the method in a group of 22 normal volunteers and 29 patients with responsive (N=21) or treatment-resistant (N=8) late-onset depressive disorder. Single-slice quantified phase-contrast (PC) images of cerebral blood and CSF flow were collected at 15 points over a cardiac cycle, and the resulting flow curves were parameterized. Significant differences in the CSF flow (width of systolic flow peak and diastolic flow volume, both P<0.01) through the cerebral aqueduct were observed for the group of treatment-resistant patients when compared to age matched controls. No significant difference was observed for a group of 21 patients with treatment-responsive depression. The findings support the hypothesis that MR measurement of CSF flow abnormalities provides a biomarker of MVA, and thus could have application in a wide range of age-related diseases.
The Emerging Optical Data Center (2011)

We review the architecture of modern datacenter networks, as well as their scaling challenges; then present high-level requirements for deploying optical technologies in datacenters, particularly focusing on optical circuit switching and WDM transceivers.
Influence of structural disorder on the optical properties of 1D natural photonic crystals (2020)

In the fabrication processes of photonic crystals, structural disorder arises in the synthesised structures from the limitations in the resolution of the synthesis processes. Elucidating the structural-disorder influence helps reducing its optical effects and allows using it in technological applications. Natural photonic structures are interesting examples to investigate due to their resilience to structural defects. The benefit and cost of these defects are so far not understood. In this contribution, we investigated the structural disorder in one-dimensional photonic crystals occurring on the wings of beetles. We performed optical simulations allowing to assess the optical benefit and cost of such disorder.
MHC-linked low-molecular mass polypeptide subunits define distinct subsets of proteasomes. Implications for divergent function among distinct proteasome subsets. (1993)

Proteasomes are 650-kDa, multisubunit endopeptidases that might be involved in the MHC class I Ag processing pathway. We demonstrate the existence of multiple structurally distinct subsets of proteasomes. Distinct forms of proteasomes share a hypothetical core to which unique subunits are added. One of these subsets, LMP2+ proteasome, contains the product of the MHC-linked Lmp-2 gene, and can be distinguished serologically and structurally from other proteasome subsets. The expression of LMP2+ and LMP2- proteasomes is variable among cell lines of different tissue types, and their relative abundance and subunit composition are regulated by IFN-gamma. LMP2+ proteasomes comprise 0 to 74% of total cellular proteasomes. Both LMP2+ and LMP2- proteasomes are proteolytically active. We suggest proteasome function might be regulated by subunit composition, and some, or all proteasome subsets, might participate in the production or delivery of peptides to MHC class I molecules. Both LMP2+ and LMP2- subsets can be further subdivided on the basis of the presence or absence of other unique subunits. Implications of the existence of structurally distinct forms of proteasomes in different tissue types is discussed.
Development of a Lapping Film Utilizing Agglomerative Superfine Silica Abrasives for Edge Finishing of a Silicon Wafer (2005)

In the present manufacturing process of a silicon wafer, wafer edge finishing with loose abrasives is essential for preventing wafer breakage and particle contamination due to micro cracks. Loose-abrasive machining, however, has problems involving inefficiency and an unclean working environment. Therefore, fixed-abrasive machining such as film lapping has received attention as an alternative technology, but conventional lapping films have problems involving low finishing efficiency or low finished surface quality. In this study, agglomerative superfine silica abrasives are adopted in the lapping film to overcome these problems. The finishing experiments revealed that a high edge surface quality can be achieved with high efficiency.
Abrogation of potent humoral vaccine responses in patients on long-term anti-CD25 therapy (B196) (2007)

Abstract Daclizumab, a monoclonal antibody that binds CD25, has been effective in the treatment of a number of autoimmune diseases. Despite continuous IL-2 receptor blockade for extended periods in these patients, there have been no instances of opportunistic infection and the rate of community-acquired infections is no greater than that of the general populace. This suggests that daclizumab dosing is balanced between prevention of autoimmunity and susceptibility to infection. To test this hypothesis, as a surrogate for infection we measured hepatitis vaccine responses in five patients with autoimmune uveitis who had been on daclizumab therapy for as long as 92 months. Surprisingly, only one equivocal vaccine response was observed. Given the high frequency of seroconversion (&amp;gt;95%) induced by these vaccines in healthy adults, this study is sufficiently powered to demonstrate statistically significant differences from the expected hepatitis vaccine response rate (p=0.0005). These results show that daclizumab can block the response to a potent immunogen in vivo. Given that alum based vaccine responses are highly dependent on IL-4, the known inhibition of Th2 cytokine production by daclizumab is likely to have contributed to the vaccine failures we observed. Our results indicate that, where possible, antibiotic/antiviral drug prophylaxis may be preferable to vaccination in patients on daclizumab therapy.
Application of Quantum Machine Learning to High Energy Physics Analysis at LHC using IBM Quantum Computer Simulators and IBM Quantum Computer Hardware (2021)

One of the major objectives of the experimental programs at the LHC is the discovery of new physics. This requires the identification of rare signals in immense backgrounds. Using machine learning algorithms greatly enhances our ability to achieve this objective. With the progress of quantum technologies, quantum machine learning could become a powerful tool for data analysis in high energy physics. In this study, using IBM gate-model quantum computing systems, we employ the quantum variational classifier method and the quantum kernel estimator method in two recent LHC flagship physics analyses: $t\bar{t}H$ (Higgs boson production in association with a top quark pair) and $H\rightarrow\mu\mu$ (Higgs boson decays to two muons). We have obtained early results with 10 qubits on the IBM quantum simulator and the IBM quantum hardware. On the quantum simulator, the quantum machine learning methods perform similarly to classical algorithms such as SVM (support vector machine) and BDT (boosted decision tree), which are often employed in LHC physics analyses. On the quantum hardware, the quantum machine learning methods have shown promising discrimination power, comparable to that on the quantum simulator. This study demonstrates that quantum machine learning has the ability to differentiate between signal and background in realistic physics datasets.
Biotechnological approaches to enhance salidroside, rosin and its derivatives production in selected Rhodiola spp. in vitro cultures (2014)

<i>Rhodiola</i> (Crassulaceae) an arctic-alpine plant, is extensively used in traditional folk medicine in Asian and European countries. A number of investigations have demonstrated that <i>Rhodiola</i> preparations exhibit adaptogenic, neuroprotective, anti-tumour, cardioprotective, and anti-depressant effects. The main compounds responsible for these activities are believed to be salidroside, rosin and its derivatives which became the target of biotechnological investigations. This review summarizes the results of the diverse biotechnological approaches undertaken to enhance the production of salidroside, rosin and its derivatives in callus, cell suspension and organ in vitro cultures of selected <i>Rhodiola</i> species.
Poster Abstract: Interconnecting Low-Power Wireless and Power-Line Communications using IPv6 (2010)

Wireless sensor networks for building automation and energy management has made great progress in recent years, but the inherent indoor radio range limitations can make communication unpredictable and system deployments difficult. Low-power radio can be combined with low-power Power-Line Communication (PLC) to extend the range and predictability of indoor communication for building management and automation systems. We take the first steps towards exploring the system implications for integration of low-power wireless and PLC in the same network. We leverage IPv6, which allow networks to exist over multiple physical communication media as well as the RPL routing protocol for low-power lossy networks.
Myeloid‐Derived Suppressor Cells and Therapeutic Strategies in Cancer (2015)

Development of solid cancer depends on escape from host immunosurveillance. Various types of immune cells contribute to tumor-induced immune suppression, including tumor associated macrophages, regulatory T cells, type 2 NKT cells, and myeloid-derived suppressor cells (MDSCs). Growing body of evidences shows that MDSCs play pivotal roles among these immunosuppressive cells in multiple steps of cancer progression. MDSCs are immature myeloid cells that arise from myeloid progenitor cells and comprise a heterogeneous immune cell population. MDSCs are characterized by the ability to suppress both adaptive and innate immunities mainly through direct inhibition of the cytotoxic functions of T cells and NK cells. In clinical settings, the number of circulating MDSCs is associated with clinical stages and response to treatment in several cancers. Moreover, MDSCs are reported to contribute to chemoresistant phenotype. Collectively, targeting MDSCs could potentially provide a rationale for novel treatment strategies in cancer. This review summarizes recent understandings of MDSCs in cancer and discusses promissing clinical approaches in cancer patients.
New polymorphic microsatellite markers in the human MHC class I region (1999)

The human major histocompatibility complex (MHC) class I region is believed to contain a large number of genes encoding susceptible factors for diseases such as Behcet's disease, Graves disease and psoriasis vulgaris. To identify the causative genes of those diseases, we have conducted large-scale genomic sequencing and determined the 1.8 Mb entire HLA class I region from the MICB gene to the HLA-F gene. During the course of genomic sequencing, a total of 731 microsatellite sequences with dinucleotide to pentanucleotide repeats were found in this region. Previously, we reported that 26 microsatellites between MICB and S on the most centromeric side of the class I region, and between HSR1 and HLA-92/L in the midst of the class I region were highly polymorphic, and served as excellent genetic markers. In this paper, in order to fill the gaps with no known polymorphic microsatellites available in the HLA class I region, 12 new polymorphic microsatellite markers were recruited from the 1.8 Mb region including the remaining class I segments, namely between S and HSR1, and between HLA-92/L and HLA-F The average number of alleles at these new microsatellite loci was 8.2 with a polymorphism content value (PIC) of 0.63. These 38 markers in total almost uniformly interspersed in the HLA class I region will enable us to search precisely for the location of disease susceptible loci within the HLA class I region by association and for linkage analyses.