gebhart/patrepeval huggingface dataset:
Enabling autonomous capabilities in underwater robotics (2008)

Underwater operations present unique challenges and opportunities for robotic applications. These can be attributed in part to limited sensing capabilities, and to locomotion behaviours requiring control schemes adapted to specific tasks or changes in the environment. From enhancing teleoperation procedures, to providing high-level instruction, all the way to fully autonomous operations, enabling autonomous capabilities is fundamental for the successful deployment of underwater robots. This paper presents an overview of the approaches used during underwater sea trials in the coral reefs of Barbados, for two amphibious mobile robots and a set of underwater sensor nodes. We present control mechanisms used for maintaining a preset trajectory during enhanced teleoperations and discuss their experimental results. This is followed by a discussion on amphibious data gathering experiments conducted on the beach. We then present a tetherless underwater communication approach based on pure vision for high-level control of an underwater vehicle. Finally the construction details together with preliminary results from a set of distributed underwater sensor nodes are outlined.
Working Document on Gloss Ontology (2010)

This document describes the Gloss Ontology. The ontology and associated class model are organised into several packages. Section 2 describes each package in detail, while Section 3 contains a summary of the whole ontology.
Single cell atlas identifies lipid-processing and immunomodulatory endothelial cells in healthy and malignant breast (2022)

Since a detailed inventory of endothelial cell (EC) heterogeneity in breast cancer (BC) is lacking, here we perform single cell RNA-sequencing of 26,515 cells (including 8433 ECs) from 9 BC patients and compare them to published EC taxonomies from lung tumors. Angiogenic ECs are phenotypically similar, while other EC subtypes are different. Predictive interactome analysis reveals known but also previously unreported receptor-ligand interactions between ECs and immune cells, suggesting an involvement of breast EC subtypes in immune responses. We also identify a capillary EC subtype (LIPEC (Lipid Processing EC)), which expresses genes involved in lipid processing that are regulated by PPAR-γ and is more abundant in peri-tumoral breast tissue. Retrospective analysis of 4648 BC patients reveals that treatment with metformin (an indirect PPAR-γ signaling activator) provides long-lasting clinical benefit and is positively associated with LIPEC abundance. Our findings warrant further exploration of this LIPEC/PPAR-γ link for BC treatment.
New IBD Markers: Definition of Disease Heterogeneity (1995)

There is emerging evidence that serum and mucosal markers differentiate Crohn′s disease from ulcerative colitis; moreover, subgroups can be defined within each disease. Subgroups have been defined on the basis of genetic, serum and mucosal markers, and are associated with different clinical phenotypes. Antineutrophil cytoplasmic antibodies (ANCA) define subgroups of patients with both ulcerative colitis and Crohn′s disease. A new serum marker, 20P‐1, has been found in 60 to 70% of patients with Crohn′s disease, 20% of ulcerative colitis patients and approximately 10% of the normal control population. The 20P‐1 marker further stratifies the subgroups of patients defined by ANCA. In addition to serum markers, genes regulating production of the cytokine tumour necrosis factor (TNF)‐α have been shown to be different across ulcerative colitis and Crohn′s disease, and within the ulcerative colitis group. Serum markers may reflect differential mucosal inflammatory responses as is best shown by ANCA. B cell clones within the mucosa of 60 to 70% of patients with ulcerative colitis produce ANCA spontaneously. Studies currently underway demonstrate different TNF‐ α production within the mucosa of patients with Crohn′s disease compared with ulcerative colitis patients. Correlation studies with TNF‐α microsatellites (genes) are being performed. These markers are the focus of a trial using molecularly engineered products that are capable of inhibiting TNF‐α to identify patients likely to respond to anti‐TNF therapy. In this constantly evolving climate of understanding and treating inflammatory bowel disease, serum, mucosal and genetic markers as well as genetic associations are being formed to determine clinical phenotypes that may be differentially responsive to very selected treatment modalities. These advances highlight the likelihood that the various markers define different types of mucosal inflammation. The different types of mucosal inflammation will determine the response or resistance to certain types of therapeutic options.
Analysis, Design and Experimental Validation of Modified Simple Soft Switching DC-DC Boost Converter (2015)

Abstract This paper investigates a modified simple soft switching dc-dc converter for low power applications. This simple topology uses an auxiliary switch, an inductor and a capacitor to operate the converter without switching losses. The efficiency of the converter is improved by transferring the energy that would be dissipated during the switching to the load. The main switch turns-on with zero current switching (ZCS) and turns-off with zero voltage switching (ZVS), while the auxiliary switch turns-on and turns-off with zero voltage switching (ZVS). The detailed theoretical analysis and the design equations are described. In addition to that, the analysis of proposed converter is demonstrated by both simulation and experimental results for effectiveness of the study.
Testing the Complexity of a Valued CSP Language (2018)

A Valued Constraint Satisfaction Problem (VCSP) provides a common framework that can express a wide range of discrete optimization problems. A VCSP instance is given by a finite set of variables, a finite domain of labels, and an objective function to be minimized. This function is represented as a sum of terms where each term depends on a subset of the variables. To obtain different classes of optimization problems, one can restrict all terms to come from a fixed set $Γ$ of cost functions, called a language. Recent breakthrough results have established a complete complexity classification of such classes with respect to language $Γ$: if all cost functions in $Γ$ satisfy a certain algebraic condition then all $Γ$-instances can be solved in polynomial time, otherwise the problem is NP-hard. Unfortunately, testing this condition for a given language $Γ$ is known to be NP-hard. We thus study exponential algorithms for this meta-problem. We show that the tractability condition of a finite-valued language $Γ$ can be tested in $O(\sqrt[3]{3}^{\,|D|}\cdot poly(size(Γ)))$ time, where $D$ is the domain of $Γ$ and $poly(\cdot)$ is some fixed polynomial. We also obtain a matching lower bound under the Strong Exponential Time Hypothesis (SETH). More precisely, we prove that for any constant $δ&lt;1$ there is no $O(\sqrt[3]{3}^{\,δ|D|})$ algorithm, assuming that SETH holds.
Can Clinical Data Predict Progression to Dementia in Amnestic Mild Cognitive Impairment? (2008)

Patients presenting with amnestic MCI insufficient for the diagnosis of dementia are at high risk of developing dementia on follow-up. In our cohort, 56% were diagnosed with dementia over an average period of 5.9 years from symptom onset. The only clinical predictor for the eventual development of dementia was older age at symptom onset. Clinical features alone were insufficient to predict development of dementia.
Wafer bonding technique for fabricating 1.5-μm InGaAs/InGaAsP pillar-free microdisk lasers (1996)

A new wafer bonding-etching technique has been developed successfully for micro-disk laser fabrication. Pillar-free micro-disk lasers have been realized. The micro-disk is placed on low refractive index material such as SiO<SUB>2</SUB> and surrounded by SiO<SUB>2</SUB> and air. The pillar-free micro-disk laser shows more solid than the pillar-supported micro-disk lasers. It has similar threshold pump power compared with the pillar-supported micro-disk lasers.
Gastrointestinal stromal tumors–a review (2004)

Gastrointestinal stromal tumors (GISTs) may be defined as intraabdominal nonepithelial (mesenchymal) tumors that express the KIT protein or have an activating mutation in a class III receptor tyrosine kinase gene (KIT or PDGFRA). GISTs are diagnosed at a frequency of about 15 new cases annually per million, though small indolent GISTs are likely to occur more frequently in the general population. The clinical behavior is variable, and assessment of the malignancy potential is usually based mainly on the size and the proliferation characteristics of the tumor. The overwhelming majority of GISTs express the KIT protein, the transmembrane receptor tyrosine kinase for the stem cell factor. The majority of GISTs harbor a mutation in the KIT proto-oncogene that translates into constitutively activated KIT protein kinase, and a minority have mutated PDGFRA gene resulting in activated platelet-derived growth factor alpha receptor tyrosine kinase. Most GISTs respond to imatinib mesylate, which selectively inhibits both KIT and PDGFRA, and is now considered as the standard systemic therapy for advanced GIST. In contrast, responses to conventional chemotherapy are infrequent (generally less than 10%), but combination therapies with imatinib have not been explored. Research on adjuvant imatinib and novel targeted therapies is ongoing.
Combined experimental and theoretical investigations of clay–polymer nanocomposites: intercalation of single bifunctional organic compounds in Na+-montmorillonite and Na+-hectorite clays for the design of new materials (2003)

This paper reports a study of the intercalation of single bifunctional poly(ethylene oxide)- and poly(propylene oxide)-based compounds, with and without modified end groups, in Na+-montmorillonite and Na+-hectorite clays as the starting point for the design of new non-exfoliated clay–polymer materials. The terminal functional groups employed on intercalated poly(ethylene oxide) and poly(propylene oxide) include acrylate, methacrylate and amine functions. For some of the monomers, in situ polymerisation was observed. Attempts to rationalise these behaviours are made on the basis of atomistic grand canonical Monte Carlo, canonical Monte Carlo and molecular dynamics simulations. Poly(ethylene oxide) diacrylate monomers, for which in situ polymerisation was observed, interact more strongly with the Na+-montmorillonite clay layers than the other monomers.
High-Performance Near-IR Photodiodes: A Novel Chemistry-Based Approach to Ge and Ge–Sn Devices Integrated on Silicon (2011)

Ge/Si heterostructure diodes based on n <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">++</sup> Si(100)/i-Ge/p-Ge and p <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">++</sup> Si(100)/i-Ge/n-Ge stacks and intrinsic region thickness of ~350 and ~900 nm, respectively, were fabricated using a specially developed synthesis protocol that allows unprecedented control of film microstructure, morphology, and purity at complementary metal-oxide-semiconductor compatible conditions. From a growth and doping perspective, a main advantage of our inherently low-temperature (390°C) soft-chemistry approach is that all high-energy processing steps are circumvented. Current-voltage measurements of circular mesas (60-250 μm in diameter) show dark current densities as low as 6 ×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> A/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> at -1 V bias, which is clearly improved over devices fabricated under low thermal budgets using traditional Ge deposition techniques. Spectral photocurrent measurements indicate external quantum efficiencies between 30 and 60% of the maximum theoretical value at zero bias, and approaching full collection efficiency at high reverse biases. The above Ge devices are compared to analogous low-temperature-grown (350°C) Ge <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0.98</sub> Sn <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0.02</sub> diodes. The latter display much higher dark currents but also higher collection efficiencies close to 70% at zero bias. Moreover, the quantum efficiency of these Ge <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0.98</sub> Sn <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0.02</sub> diodes remains strong at wavelengths longer than 1550 nm out to 1750 nm due to the reduced band gap of the alloy relative to Ge.
Towards Real-Time User QoE Assessment via Machine Learning on LTE Network Data (2019)

It is well known that current reactive network management would be unable to support the exponential increase in complexity and rapidity of change in future cellular networks. Keeping this in perspective, the goal of this paper is to investigate applicability of machine learning and predictive models to assess cell-level user quality of experience (QoE) in real-time. For this purpose, we leverage a 5 week LTE metrics data collected at cell level granularity for a national LTE network operator. Domain knowledge is applied to assess user QoE with network key performance indicators (KPIs), namely scheduled user throughput, inter-frequency handover success rate and intra-frequency handover success rate. Results indicate that applying boosted trees model on a subset of carefully selected non-collinear features allows high accuracy threshold-based estimation of user throughput and inter-frequency handover success rate. We also exploit the periodic nature of cell data characteristics and apply a recently developed time series prediction model known as PROPHET for future QoE estimation. By employing machine learning and data analytics on network data within an end-to-end framework, network operators can proactively identify low performance cell sites along with the influential factors that impact the cell performance. Based on the root cause analysis, appropriate corrective measures may then be taken for low performance cell sites.
140 GHz Urban Microcell Propagation Measurements for Spatial Consistency Modeling (2021)

Sub-Terahertz frequencies (frequencies above 100 GHz) have the potential to satisfy the unprecedented demand on data rate on the order of hundreds of Gbps for sixth-generation (6G) wireless communications and beyond. Accurate beam tracking and rapid beam selection are increasingly important since antenna arrays with more elements generate narrower beams to compensate for additional path loss within the first meter of propagation distance at sub-THz frequencies. Realistic channel models for above 100 GHz are needed, and should include spatial consistency to model the spatial and temporal channel evolution along the user trajectory. This paper introduces recent outdoor urban microcell (UMi) propagation measurements at 142 GHz along a 39 m × 12 m rectangular route (102 m long), where each consecutive and adjacent receiver location is 3 m apart from each other. The measured power delay profiles and angular power spectrum at each receiver location are used to study spatial autocorrelation properties of various channel parameters such as shadow fading, delay spread, and angular spread along the track. Compared to the correlation distances reported in the 3GPP TR 38.901 for frequencies below 100 GHz, the measured correlation distance of shadow fading at 142 GHz (3.8 m) is much shorter than the 10-13 m as specified in 3GPP; the measured correlation distances of delay spread and angular spread at 142 GHz (both 12 m) are comparable to the 7-10 m as specified in 3GPP. This result may guide the development of a statistical spatially consistent channel model for frequencies above 100 GHz in the UMi street canyon environment.
ChemInform Abstract: Trifluoroacetaldehyde: A Useful Industrial Bulk Material for the Synthesis of Trifluoromethylated Amino Compounds. (2010)

Abstract The application of the title compound for the synthesis of trifluoromethylated amino compounds via reductive amination reactions, and in the synthesis of chiral α‐substituted trifluoroethylamino compounds via chiral sulfinimine (X) is reported.
Multifunctional integrated photonic switches (2005)

Traditional optical-electronic-optical (o-e-o) conversion in today's optical networks requires cascading separately packaged electronic and optoelectronic chips and propagating high-speed electrical signals through and between these discrete modules. This increases the packaging and component costs, size, power consumption, and heat dissipation. As a remedy, we introduce a novel, chip-scale photonic switching architecture that operates by confining high-speed electrical signals in a compact optoelectronic chip and provides multiple network functions on such a single chip. This new technology features low optical and electrical power consumption, small installation space, high-speed operation, two-dimensional scalability, and remote electrical configurability. We present both theoretical and experimental discussion of our monolithically integrated photonic switches that incorporate quantum-well waveguide modulators directly driven by on-chip surface-illuminated photodetectors. These switches can be conveniently arrayed two-dimensionally on a single chip to realize a number of network functions. Of those, we have experimentally demonstrated arbitrary wavelength conversion across 45 nm and dual-wavelength broadcasting over 20 nm, both spanning the telecommunication center band (1530-1565 nm) at switching speeds up to 2.5 Gb/s. Our theoretical calculations predict the capability of achieving optical switching at rates in excess of 10 Gb/s using milliwatt-level optical and electrical switching powers.
Studies of the synthesis, structure, and reactivity of a tetranuclear mixed-metal imido cluster, (η5-C5H5)WRu3(CO)9(µ-NPh)(CCPh) (1989)

The title complex (η5-C5H5)WRu3(CO)9(µ-NPh)(CCPh), containing a bridging imido ligand and a µ4-η2-acetylide ligand, has been prepared by means of the condensation between (η5-C5H5)W(CO)3CCPh and Ru3(CO)10(µ3-NPh), and its reactions with dihydrogen and disubstituted alkyne ligands are presented; the products have been fully characterized by spectroscopic methods and X-ray diffraction studies for two complexes.
A Dual Palladium and Copper Hydride Catalyzed Approach for Alkyl–Aryl Cross‐Coupling of Aryl Halides and Olefins (2017)

We report an efficient means of sp<sup>2</sup> -sp<sup>3</sup> cross coupling for a variety of terminal monosubstituted olefins with aryl electrophiles using Pd and CuH catalysis. In addition to its applicability to a range of aryl bromide substrates, this process was also suitable for electron-deficient aryl chlorides, furnishing higher yields than the corresponding aryl bromides in these cases. The optimized protocol does not require the use of a glovebox and employs air-stable Cu and Pd complexes as precatalysts. A reaction on 10 mmol scale further highlighted the practical utility of this protocol. Employing a similar protocol, a series of cyclic alkenes were also examined. Cyclopentene was shown to undergo efficient coupling under these conditions. Lastly, deuterium-labeling studies indicate that deuterium scrambling does not take place in this sp<sup>2</sup> -sp<sup>3</sup> cross coupling, implying that β-hydride elimination is not a significant process in this transformation.
Model-Based Deep Learning (2023)

Signal processing traditionally relies on classical statistical modeling techniques. Such model-based methods utilize mathematical formulations that represent the underlying physics, prior information and additional domain knowledge. Simple classical models are useful but sensitive to inaccuracies and may lead to poor performance when real systems display complex or dynamic behavior. More recently, deep learning approaches that use deep neural networks are becoming increasingly popular. Deep learning systems do not rely on mathematical modeling, and learn their mapping from data, which allows them to operate in complex environments. However, they lack the interpretability and reliability of model-based methods, typically require large training sets to obtain good performance, and tend to be computationally complex. Model-based signal processing methods and data-centric deep learning each have their pros and cons. These paradigms can be characterized as edges of a continuous spectrum varying in specificity and parameterization. The methodologies that lie in the middle ground of this spectrum, thus integrating model-based signal processing with deep learning, are referred to as model-based deep learning, and are the focus here. This monograph provides a tutorial style presentation of model-based deep learning methodologies. These are families of algorithms that combine principled mathematical models with data-driven systems to benefit from the advantages of both approaches. Such model-based deep learning methods exploit both partial domain knowledge, via mathematical structures designed for specific problems, as well as learning from limited data. We accompany our presentation with running examples, in super-resolution, dynamic systems, and array processing. We show how they are expressed using the provided characterization and specialized in each of the detailed methodologies.
The Role of CXCL13 in Antibody Responses to HIV-1 Infection and Vaccination (2021)

CXCL13 signals through the G protein-coupled chemokine receptor CXCR5 to drive development of secondary lymphoid tissue as well as B cell and Tfh cell trafficking to germinal centers (GC), which leads to the differentiation of B cells to plasma cells and memory B cells. CXCL13 has been proposed as a general plasma biomarker for GC activities. In HIV-1 infected individuals, plasma CXCL13 levels have been associated with the rate of disease progression to AIDS. Moreover, CXCL13 production has been reported to be increased in HIV-1-infected lymph nodes, which may drive increased downregulation of CXCR5. In this review, we address the role of CXCL13 in HIV-1 infected individuals with regard to GC formation, generation of broadly neutralizing antibodies after infection and vaccination, and AIDS-related B cell lymphoma.
Localization Value of Magnetoencephalography Interictal Spikes in Adult Nonlesional Neocortical Epilepsy (2012)

Few studies have included magnetoencephalography (MEG) when assessing the diagnostic value of presurgical modalities in a nonlesional epilepsy population. Here, we compare single photon emission computed tomography (SPECT), positron emission tomography (PET), video-EEG (VEEG), and MEG, with intracranial EEG (iEEG) to determine the value of individual modalities to surgical decisions. We analyzed 23 adult epilepsy patients with no abnormal MRI findings who had undergone surgical resection. Localization of individual presurgical tests was determined for hemispheric and lobar locations based on visual analysis. Each localization result was compared with the ictal onset zone (IOZ) defined by using iEEG. The highest to the lowest hemispheric concordance rates were MEG (83%) > ictal VEEG (78%) > PET (70%) > ictal SPECT (57%). The highest to lowest lobar concordance rates were ictal VEEG = MEG (65%) > PET (57%) > ictal SPECT (52%). Statistical analysis showed MEG to have a higher hemispheric concordance than that of ictal SPECT (P = 0.031). We analyzed the effects of MEG clustered-area resection on surgical outcome. Patients who had resection of MEG clusters showed a better surgical outcome than those without such resection (P = 0.038). It is suggested that MEG-based localization had the highest concordance with the iEEG-defined IOZ. Furthermore, MEG cluster resection has prognostic significance in predicting surgical outcome.