gebhart/patrepeval huggingface dataset:
Automatic Extraction of Heap Reference Properties in Object-Oriented Programs (2008)

We present a new technique for helping developers understand heap referencing properties of object-oriented programs and how the actions of the program affect these properties. Our dynamic analysis uses the aliasing properties of objects to synthesize a set of roles; each role represents an abstract object state intended to be of interest to the developer. We allow the developer to customize the analysis to explore the object states and behavior of the program at multiple different and potentially complementary levels of abstraction. The analysis uses roles as the basis for three abstractions: role transition diagrams, which present the observed transitions between roles and the methods responsible for the transitions; role relationship diagrams, which present the observed referencing relationships between objects playing different roles; and enhanced method interfaces, which present the observed roles of method parameters. Together, these abstractions provide useful information about important object and data structure properties and how the actions of the program affect these properties. We have implemented the role analysis and have used this implementation to explore the behavior of several Java programs. Our experience indicates that, when combined with a powerful graphical user interface, roles are a useful abstraction for helping developers explore and understand the behavior of object-oriented programs.
Deposition Mechanism of a-Si: H Film in Disilane-Hydrogen Plasma (1984)

Deposition mechanism of a-Si: H film in Si 2 H 6 –H 2 plasma is investigated in terms of the deposition rate. It is found that the deposition rate is proportional to the square root of the electron concentration in the plasma at any Si 2 H 6 fraction. This relation is interpreted by a simple model of film deposition including a reduction step of the concentration of effective radicals for film deposition by collision between two radicals in the gas phase. The Si 2 H 6 fraction dependence of deposition rate at high Si 2 H 6 fraction also suggests the existence of a production step of oligomeric radicals by radical collision with Si 2 H 6 .
Support Structures for Additive Manufacturing: A Review (2018)

Additive manufacturing (AM) has developed rapidly since its inception in the 1980s. AM is perceived as an environmentally friendly and sustainable technology and has already gained a lot of attention globally. The potential freedom of design offered by AM is, however, often limited when printing complex geometries due to an inability to support the stresses inherent within the manufacturing process. Additional support structures are often needed, which leads to material, time and energy waste. Research in support structures is, therefore, of great importance for the future and further improvement of additive manufacturing. This paper aims to review the varied research that has been performed in the area of support structures. Fifty-seven publications regarding support structure optimization are selected and categorized into six groups for discussion. A framework is established in which future research into support structures can be pursued and standardized. By providing a comprehensive review and discussion on support structures, AM can be further improved and developed in terms of support waste in the future, thus, making AM a more sustainable technology.
High Performance Near-Infrared (NIR) Photoinitiating Systems Operating under Low Light Intensity and in the Presence of Oxygen (2018)

Photopolymerization under near-infrared (NIR) light is challenging due to the low energy of the absorbed photon but, if successful, presents significant advantages. For example, this lower energy wavelength is safer than UV light that is currently the standard photocuring light source. Also, NIR allows for a deeper light penetration within the material and therefore resulting in a more complete curing of thicker materials containing fillers for access to composites. In this study, we report the use of three-component systems for the NIR photopolymerization of methacrylates: (1) a dye used as a photosensitizer in the NIR range, (2) an iodonium salt as a photoinitiator for the free radical polymerization of the (meth)acrylates, and (3) a phosphine to prevent polymerization inhibition due to the oxygen and to regenerate the dye upon irradiation. Several NIR-absorbing dyes such as a cyanine borate and a silicon–phthalocyanine are presented and studied. Systems using borate dyes resulted in methacrylate monomer conversion over 80% in air. We report three types of irradiation system: low-power LED at 660 and 780 nm as well as a higher power laser diode at 785 nm. The excellent performance reported in this work is due to the crucial role of the added phosphine.
Hybrid Perovskites: Effective Crystal Growth for Optoelectronic Applications (2017)

Abstract Outstanding material properties of organic‐inorganic hybrid perovskites have triggered a new insight into the next‐generation solar cells. Beyond solar cells, a wide range of controllable properties of hybrid perovskites, particularly depending on crystal growth conditions, enables versatile high‐performance optoelectronic devices such as light‐emitting diodes, photodetectors, and lasers. This article highlights recent progress in the crystallization strategies of organic–inorganic hybrid perovskites for use as effective light harvesters or light emitters. Fundamental background on perovskite crystalline structures and relevant optoelectronic properties such as optical band‐gap, electron‐hole behavior, and energy band alignment are given. A detailed overview of the effective crystallization methods for perovskites, including thermal treatment, additives, solvent mediator, laser irradiation, nanostructure, and crystal dimensionalityis reported offering a comprehensive correlation among perovskite processing conditions, crystalline morphology, and relevant device performance. Finally, future research directions to overcome current practical bottlenecks and move towards reliable high performance perovskite optoelectronic applications are proposed.
Tuning Fluorescent Molecules by Inclusion in a Metal–Organic Framework: An Experimental and Computational Study (2012)

Abstract Fluorescent molecules included within a metal–organic framework (MOF) offer a new opportunity to develop luminescent host–guest materials. Two linear π‐conjugated fluorescent molecules, 1,4‐bis‐ p ‐cyanostyrylbenzene (bpcb) and 1,4‐bis(5‐phenyloxazol‐2‐yl)benzene (bpob), incorporated into MOF‐5 systems are reported. The as‐obtained bpcb@MOF‐5 and bpob@MOF‐5 displayed tunable blue fluorescent properties (emission wavelength, fluorescent lifetime, and quantum yield) compared with the pure guest molecule and host matrix. Moreover, bpcb@MOF‐5 and bpob@MOF‐5 thin films were fabricated by the solvent‐evaporation method. The MOF‐based thin films exhibit well‐defined polarized blue emission with a fluorescent anisotropy of approximately 0.15, demonstrating the uniform dispersion and well‐oriented bpcb and bpob chromophores within the MOF matrix. Furthermore, a periodic density functional theoretical (DFT) calculation demonstrates that the photoactive molecule assembled MOFs systems feature energy and/or electron transfer between the guest and host framework during the photoexcitation process, thus suggesting that the encapsulated molecule can further modify the electronic structure of the host MOF materials. Based on the combination of experimental and theoretical studies on the fluorescent guests@MOF systems, this study not only presents a feasible method for fabricating MOF‐based powders and films with tunable luminescence, but also gives detailed information on the geometric and electronic structures of the photoactive molecule confined within the MOF matrix.
Core–Ring Structured NiCo<sub>2</sub>O<sub>4</sub> Nanoplatelets: Synthesis, Characterization, and Electrocatalytic Applications (2008)

Abstract An innovative nanostructure, namely the core–ring structure, is reported in this paper. It occurs in NiCo 2 O 4 nanoplatelets, synthesized by the coprecipitation decomposition method using sodium hydroxide as the precipitant. The yield of core–ring hexagonal NiCo 2 O 4 nanoplatelets is greater than 80% at 200 °C. A high‐resolution transmission electron microscopy and energy dispersive spectroscopy investigation reveals the typical core–ring nanostructure, which shows a strong enrichment of Co in the core with a Co content higher than 80%. A mechanism for the core–ring structure formation is proposed. The core–ring NiCo 2 O 4 can be used as an electrocatalyst for an oxygen evolution reaction (OER) in alkaline water electrolysis. Compared with the electrodes of ordinary NiCo 2 O 4 and Co 3 O 4 , or other NiCo 2 O 4 electrodes prepared by alternate methods, the electrode coated by core‐ring NiCo 2 O 4 nanoplatelets exhibits the greatest electrocatalytic properties, with an over‐potential of 0.315 V at a current density of 100 mA cm −2 .
Distrbution and Abstract Types in Emerald (1987)

Emerald is an object-based language for programming distributed subsystems and applications. Its novel features include 1) a single object model that is used both for programming in the small and in the large, 2) support for abstract types, and 3) an explicit notion of object location and mobility. This paper outlines the goals of Em-erald, relates Emerald to previous work, and describes its type system and distribution support. We are currently constructing a prototype implementation of Emerald.
Tell the Queen I'm Sorry (1984)

Every afternoon just before four o'clock, Uncle got ready to go out. Not that he needed much preparation. He had never taken off his three-piece suit since he got back from England so all he had to do was put on his bowler hat and take up his walking stick and gloves. But even these simple actions were imbued with great purpose and deliberation, as was everything that Uncle did. His hat set at the right angle, his gloves precisely delineated in his right hand in relation to his cane, he would set out.
The Antitumor Drug LB-100 Is a Catalytic Inhibitor of Protein Phosphatase 2A (PPP2CA) and 5 (PPP5C) Coordinating with the Active-Site Catalytic Metals in PPP5C (2019)

LB-100 is an experimental cancer therapeutic with cytotoxic activity against cancer cells in culture and antitumor activity in animals. The first phase I trial (NCT01837667) evaluating LB-100 recently concluded that safety and efficacy parameters are favorable for further clinical testing. Although LB-100 is widely reported as a specific inhibitor of serine/threonine phosphatase 2A (PP2AC/<i>PPP2CA:PPP2CB</i>), we could find no experimental evidence in the published literature demonstrating the specific engagement of LB-100 with PP2A <i>in vitro</i>, in cultured cells, or in animals. Rather, the premise for LB-100 targeting PP2AC is derived from studies that measure phosphate released from a phosphopeptide (K-R-pT-I-R-R) or inferred from the ability of LB-100 to mimic activity previously reported to result from the inhibition of PP2AC by other means. PP2AC and PPP5C share a common catalytic mechanism. Here, we demonstrate that the phosphopeptide used to ascribe LB-100 specificity for PP2A is also a substrate for PPP5C. Inhibition assays using purified enzymes demonstrate that LB-100 is a catalytic inhibitor of both PP2AC and PPP5C. The structure of PPP5C cocrystallized with LB-100 was solved to a resolution of 1.65Å, revealing that the 7-oxabicyclo[2.2.1]heptane-2,3-dicarbonyl moiety coordinates with the metal ions and key residues that are conserved in both PP2AC and PPP5C. Cell-based studies revealed some known actions of LB-100 are mimicked by the genetic disruption of <i>PPP5C</i> These data demonstrate that LB-100 is a catalytic inhibitor of both PP2AC and PPP5C and suggest that the observed antitumor activity might be due to an additive effect achieved by suppressing both PP2A and PPP5C.
Collaborative ranking (2012)

Typical recommender systems use the root mean squared error (RMSE) between the predicted and actual ratings as the evaluation metric. We argue that RMSE is not an optimal choice for this task, especially when we will only recommend a few (top) items to any user. Instead, we propose using a ranking metric, namely normalized discounted cumulative gain (NDCG), as a better evaluation metric for this task. Borrowing ideas from the learning to rank community for web search, we propose novel models which approximately optimize NDCG for the recommendation task. Our models are essentially variations on matrix factorization models where we also additionally learn the features associated with the users and the items for the ranking task. Experimental results on a number of standard collaborative filtering data sets validate our claims. The results also show the accuracy and efficiency of our models and the benefits of learning features for ranking.
Defective in vitro production of gamma-interferon and tumor necrosis factor-alpha by circulating T cells from patients with the hyper-immunoglobulin E syndrome. (1989)

Circulating T cells from four patients with the hyper-IgE syndrome were found to produce significantly lower concentrations of interferon-gamma (IFN-gamma) in response to stimulation with phytohemagglutinin (PHA) than did T cells from eight age-matched healthy controls, three patients with atopic dermatitis and one patient with chronic granulomatous disease. A clonal analysis revealed that patients with hyper-IgE syndrome had markedly lower proportions of circulating T cells able to produce IFN-gamma and tumor necrosis factor-alpha (TNF-alpha) in comparison with controls. In contrast, the proportions of peripheral blood T cells able to produce IL-4 or IL-2 were not significantly different in patients and controls. All the four patients with hyper-IgE syndrome showed high proportions of circulating CD4+ helper T cells able to induce IgE synthesis in allogeneic B cells, as well. Such an activity for IgE synthesis appeared to be positively correlated with IL-4 production by T cells and inversely related to the ability of the same T cells to produce IFN-gamma. Since IFN-gamma exerts an inhibitory effect on the synthesis of IgE and both IFN-gamma and TNF-alpha play an important role in inflammatory reactions, we suggest that the defective production of IFN-gamma may be responsible for hyperproduction of IgE and the combined defect of IFN-gamma and TNF-alpha may contribute to the undue susceptibility to infections seen in patients with hyper-IgE syndrome.
Degradation of metal induced laterally crystallized n-type polysilicon TFTs under dynamic gate voltage stresses (2008)

Degradation behaviors of metal induced laterally crystallized n-type polysilicon TFTs under dynamic gate voltage stresses have been investigated. Device degradation occurs when the base voltage of gate pulses is lower than the flat-band voltage, and more degradation occurs with steeper falling edge and larger amplitude of the gate pulses. Device degradation is attributed to the hot carrier mechanism related to the transient voltage transition at the falling edge of the gate stress pulses.
When entities meet query recommender systems (2013)

The Web of Data is growing in popularity and dimension, and entities are gaining importance in many research fields. In this paper, we explore the use of entities that can be extracted from a query log to enhance query recommendation. In particular, we use a large query log recorded by the Europeana portal, a central access point to the descriptions of more than 20 million cultural heritage objects, and we extend a state-of-the-art query recommendation algorithm to take into account the semantic information associated with the submitted queries. Our novel method generates highly related and diversified suggestions. We assess it by means of a new evaluation technique. The manually annotated dataset used for performance comparisons has been made available to the research community to favor the repeatability of the experiments.
Effects of experimental variables on the synthesis of porous matrices (2001)

Macroporous beads, poly(ethylene glycol dimethacrylate-co-acrylic acid) [poly(EGDMA-co-AAc)], and poly(ethylene glycol dimethacrylate-co-hydroxyethyl methacrylate) [poly(EGDMA-co-HEMA)] were prepared by the suspension polymerization technique in the presence of a porogen agent. Different experimental conditions such as amount of initiator, porogen type, and temperature were studied to optimize the polymerization systems. These hydrophilic copolymers were characterized by IR spectroscopy, scanning electron microscopy, specific surface area, and swelling in water. A new parameter, H, defined as the ratio between the equilibrium weight swelling ratio (qw) and equilibrium volume swelling ratio (qv), allowed to select the reaction conditions from which matrices with high capacity of water sorption and low stretching degree were reached. © 2000 John Wiley & Sons, Inc. J Appl Polym Sci 79: 920–927, 2001
Ubiquitous computing with service adaptation using peer-to-peer communication framework (2004)

Mobile devices and wireless network infrastructures will be leading users to seamlessly use peer-to-peer services and ubiquitous computing by the growing of the infrastructures. In order to realize to use peer-to-peer services and ubiquitous services seamlessly, a new framework that enables users to use peer-to-peer services and ubiquitous computing is required. Hence, this paper describes a new ubiquitous computing framework, called VPC on KODAMA, using a peer-to-peer mechanism. Virtual Private Community (VPC) is an execution environment for peer-to-peer services, and provides a framework for definition of peer-to-peer services. Peer-to-peer services in VPC are defined as policy packages that have necessary elements to provide the services. Peer-to-peer services are offered in communities by collaboration among roles that are assigned to users. KODMA provides a network infrastructure for agents. Agents in KODAMA have their own community, and represent the communities. Communities have a hierarchy structure by agents residing in other agent's communities. Agents have message filtering policy, and refuse messages that are against the policy. By unifying VPC and KODAMA, a new framework that enables services to define roles and their behavior and to manage logical relationship among communities is provided. VPC on KODAMA enables users to use peer-to-peer services and appliances seamlessly with their mobile devices.
Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption (2017)

Consider two data providers, each maintaining private records of different feature sets about common entities. They aim to learn a linear model jointly in a federated setting, namely, data is local and a shared model is trained from locally computed updates. In contrast with most work on distributed learning, in this scenario (i) data is split vertically, i.e. by features, (ii) only one data provider knows the target variable and (iii) entities are not linked across the data providers. Hence, to the challenge of private learning, we add the potentially negative consequences of mistakes in entity resolution. Our contribution is twofold. First, we describe a three-party end-to-end solution in two phases ---privacy-preserving entity resolution and federated logistic regression over messages encrypted with an additively homomorphic scheme---, secure against a honest-but-curious adversary. The system allows learning without either exposing data in the clear or sharing which entities the data providers have in common. Our implementation is as accurate as a naive non-private solution that brings all data in one place, and scales to problems with millions of entities with hundreds of features. Second, we provide what is to our knowledge the first formal analysis of the impact of entity resolution's mistakes on learning, with results on how optimal classifiers, empirical losses, margins and generalisation abilities are affected. Our results bring a clear and strong support for federated learning: under reasonable assumptions on the number and magnitude of entity resolution's mistakes, it can be extremely beneficial to carry out federated learning in the setting where each peer's data provides a significant uplift to the other.
Continuous intraoperative vagus nerve stimulation for identification of imminent recurrent laryngeal nerve injury (2012)

CIONM reliably signaled impending nerve injury, enabling immediate corrective action.
Evaluation of New NLMS and RLS Chip Equalizers using Tentative Decision Data for HSDPA Systems (2006)

Equalizers are currently being studied to improve the performance of wideband code division multiple access (WCDMA) downlinks. Especially for high data rate wireless systems (e.g. high-speed downlink packet access (HSDPA)), reduction of multiple access interference (MAI) and inter symbol interference (ISI) are key issues. We propose a new chip equalizer using tentative decision data and show that it has a high throughput performance for HSDPA systems. The normalized least mean square (NLMS) algorithm or the recursive least square (RLS) algorithm is used as the adaptive algorithm for the equalizer because these equalizers are well known to have lower complexity than the maximum mean square error (MMSE) equalizer. In the proposed method, high-speed physical downlink shared channel (HS-PDSCH) data is tentatively determined and used as a training signal to add to the common pilot channel (CPICH). In this paper, we show that the proposed equalizer has a good throughput performance compared with the conventional equalizer, and that the proposed RLS equalizer has a throughput performance that is approximately 73% of the ideal MMSE
MicroRNAs in colorectal cancer metastasis (2011)

Metastatic disease is the major cause of death in colorectal cancer (CRC) patients. The metastatic process is highly inefficient and comprises multiple sequential steps. While many genetic factors relevant in this process have already been identified, the epigenetic factors underlying each step still remain obscure. MicroRNAs (miRNAs) are key regulators in tumourigenesis, but their role in the development of cancer metastasis is poorly investigated. The majority of miRNAs involved in the metastatic process have been identified in breast cancer cell lines, and in CRC less data are available. We review the role of miRNAs in the metastatic pathway of CRC, including escape of apoptosis, epithelial-mesenchymal transition (EMT), angiogenesis, and invasion. Better understanding of the complex role of miRNAs in the development of CRC metastases may provide new insights that could be of therapeutic consequence.
Scalable Production of Graphene Nanoplatelets for Energy Storage (2020)

The difficulty of scaling up the production of high-quality graphene nanoplatelets remains a major challenge for the graphene community and inhibits commercialization across a variety of market segments and applications. Here, we demonstrate a compressed, permeable reactor that produces graphene nanoplatelets via electrochemical exfoliation and controlled pressure. In contrast to prior controlled-volume reactors, the second-generation reactor allows for both direct control of pressure on the graphite source and arbitrarily large batch sizes. We have measured how graphene production is affected by the electrode type and arrangement (working electrode and counter electrode), reactor dimensions, and reaction kinetics. The data indicate that the reactor must be thin in at least one dimension to avoid diffusion limitations, but the long dimension can be scaled up without decreases in the yield. As in other batch processes, the highest production rate occurs in the initial stage followed by a plateau in conversion. An expandable graphite feedstock results in a substantial increase in yield compared to graphite flake feedstocks under identical reactor conditions.