Miracle-dz/UniFAR-FTUs huggingface dataset:
Staged Detection–Identification Framework for Cell Nuclei in Histopathology Images

Histopathology image is an important basis for pathologists to evaluate disease at the cellular level and colon cancer tissue sections usually contain many different types of nuclei, which should be automatically detected and identified. However, the detection and the identification of cell nuclei are challenging tasks due to the complex tissue structure and the diversity of nuclear morphology. In this paper, a staged detection–identification framework is proposed for cell nuclei in colon cancer histopathology images. First, nuclei positions are detected by a position of interest network, which encodes context-aware representation on input image and decodes features on proximity map. Meanwhile, a cascade residual fusion block is presented to enhance the detection performance during the decoding process. Second, a multicropping network is developed to identify the detected cell nuclei. For reducing the impact of uncertainty, a multicropping module is designed for effectively capturing contextual feature contents around the center of a nucleus. The proposed detection–identification framework is evaluated on an available colorectal adenocarcinoma images data set, which has 100 images including more than 20 000 marked nuclei. Compared with state-of-the-art methods, the proposed approach demonstrates excellent performance with better prediction scores.
Analysis of Injection Locking and Pulling in Single-Loop Optoelectronic Oscillator

Injection-locking characteristics of a single-loop optoelectronic oscillator (OEO) under an independent sinusoidal RF signal injection are investigated. The mathematical model of the unlocked-driven system is developed to represent phase perturbation of the generated output RF signal caused by the RF injection signal. The closed-form expressions of the output RF spectra distorted due to RF signal injection are derived to formulate the behavior of the injection-pulled OEO. Using the phase dynamics equation, a phase noise model is developed to quantify the influence of RF injection signal on the phase noise performance of the oscillator. It is shown that our analytical model is capable of predicting the injection locking and estimating the injection pulling behavior of the single-loop OEO under RF signal injection. The theoretical results are validated by the experimental results.
Molecular Methods in Biological Systems

The application of molecular methods in engineered and natural environments became more widespread in 2001. Methods targeting the 16S-like and 23S-like ribosomal ribonucleic acid (rRNA) of the domains Bacteria, Archaea, Eukarya were used in a variety of environments, and additional molecular methods targeting other genes were developed and demonstrated. The greater impetus for combining molecular methods in environmental engineering was the focus of a Water Environment Research Editorial (Stensel, 2001). A session on Molecular Methods was included in one of the Research Symposium sessions for WEFTEC 2001. In this session and in papers published in 2001, molecular tools were used to investigate microorganisms that are important to public health, as well as microorganisms responsible for various biochemical functions in bioreactors, in situ remediation, and natural systems. This review summarizes relevant literature published in 2001.
Photosensing Wireless Tags for Geometric Procedures

Interacting with a self-describing, self-locating world sprinkled with RFIG tags, physical objects come alive through augmented reality labels and context-sensitive annotation. Radio-frequency tags enable physical objects to be self-describing, communicating their identities to a nearby RF reader. Our goal is to build a radio frequency identity and geometry (RFIG) transponder that also communicates geometry, inter-tag location history, and context sensitive user-defined annotation (www.merl.com/projects/rfig/). We achieve this functionality by augmenting each tag (Figure 1, top) with a photosensor (Figure 1, bottom). We use modulated light to provide optical communication with this composite RF-photosensing tag. Here, we explore tag/reader communications using a projector paired with the tag-RF-reader. The projector performs the dual operation of sending optical data to the tag (like a TV IR remote control) and providing visual feedback by projecting instructions on objects. Although conventional tag/reader combinations operate in broadcast mode with no regard for directional communication, RFID tags can be located
SURFACE at Syracuse University SURFACE at Syracuse University

Description/Abstract Information and communication technologies (ICTs) are reshaping many industries, often by reshaping how information is shared. Information intensive industries, by their nature, show the greatest impacts due to ICTs that enable information sharing and the bypassing of traditional information intermediaries. However, while the effects and uses of ICT are often associated with organizations (and industries), their use occurs at the individual level. In other words, it is changes to individual work related to the use of ICTs that reshape both organization and industry structures, and vice versa. To explore the relationships between individual uses of ICT and changes to organization and industry structures, we examined the residential real estate industry. Real estate is a revelatory industry for the study of ICT uses because it is information-intensive and realtors are information intermediaries between buyers and sellers. As agents, buyers and sellers increase their uses of ICT, they also change how they approach their daily work. We use structuration theory to provide an analytic perspective within this setting. Data reveal historical structures of this industry guiding the day-to-day work of agents, buyers and sellers. Many of these structures are embodied in a set of explicit contracts that reify existing structures and legitimize realtors’ actions. However, the increasing uses of ICT are simultaneously altering industry structures by subverting some of the realtors’ control over information while also reinforcing the existing contract-based structures. This structurational perspective and our findings help to explain why information intermediaries persist when technology-based perspectives would suggest their disappearance.
The PASCAL Visual Object Classes Challenge 2005 Development Kit

1.2 Detection task For each of the four classes predict the bounding boxes of each object of that class in a test image (if any). Each bounding box should be output with an associated real-valued confidence of the detection so that a precision/recall curve can be drawn. To be considered a correct detection, the area of overlap ao between the predicted bounding box Bp and ground truth bounding box Bgt must exceed 50% by the formula: ao = area(Bp ∩ Bgt) area(Bp ∪ Bgt) (1)
Scalable Estimation for High Velocity Survival Data Able to Accommodate Addition of Covariates

Scalable Estimation for High Velocity Survival Data Able to Accommodate Addition of Covariates Abstract: With the rapidly increasing availability of large-scale streaming data, there has been a growing interest in developing methods that allow the processing of the data in batches without requiring storage of the full dataset. In this paper, we propose a hybrid likelihood approach for scalable estimation of the Cox model using individual-level data in the current data batch and summary statistics calculated from historical data. We show that the proposed scalable estimator is asymptotically as efficient as the maximum likelihood estimator calculated using the entire dataset with low data storage requirements and low loading and computation time. A challenge in analyzing survival data batches that is not accommodated in ex-tant methods is that new covariates may become available midway through data collection. To accommodate addition of covariates, we develop a hybrid empirical likelihood approach to incorporate the historical covariate effects evaluated in a reduced Cox model. The extended scalable estimator is asymptotically more efficient than the maximum likelihood estimator obtained using only the data batches that include the additional covariates. The proposed approaches are evaluated by numerical simulations and illustrated with an analysis of Surveillance, Epidemiology, and End Results breast data.
Power Control Scheme for NOMA Random Access with Imperfect SIC

In this paper, power control is considered to improve the performance of uplink random access in non-orthogonal multiple access (NOMA) employing imperfect successive interference cancellation (SIC). First, the effect of imperfect SIC is modeled exploiting the sigmoid function. Then, in order to improve the performance of the NOMA SIC receiver, we propose an uncoordinated power control method that makes the power received from each terminal different. Based on the simulation results, it is shown that the proposed scheme results in performance improvement compared to the conventional power control method in the orthogonal multiple access (OMA) or other power control schemes in NOMA.
Plant Water Use and Growth in Response to Soil Salinity in Irrigated Agriculture

Soil salinity levels are an important determinant of plant evapotranspiration and carbon uptake. In this dissertation I develop, evaluate, and test a model of plant evapotranspiration and carbon uptake in the context of a saline soil environment, and drive the model using leaf physiological parameters determined from field measurements. This modeling work is performed in the context of three research questions: (1) How are leaf gas exchange parameters characterizing photosynthesis in perennial pepperweed best determined for seasonal scale landscape flux analysis? (2) How can the effects of soil salinity on root water uptake be represented in order to account for changes in the diurnal cycle and in the uptake of carbon dioxide by plants? (3) How sensitive are modeled results to changes in model input parameters, and how may these sensitivities limit the predictive abilities of the model? These questions are assessed using data from a relatively wet pasture-peatlands in the San Francisco Bay - Sacrament River Delta region of California, with the dominant land-cover species perennial pepperweed (Lepidium latifolium), a mildly salt-tolerant and invasive herbaceous weed. Presented in this research is a characterization of pepperweed as a highly capable invasive species, able to take advantage of local resources such as light, carbon, water, and nitrogen. Modeling results from each section also demonstrate its ability to photosynthesize under higher temperatures and vapor pressure deficits than standard plant models suggest. Incorporating soil salinity into a whole-plant model increases the ability to describe how different soil and atmospheric parameters influence evapotranspiration and photosynthesis in such an environment. The model's sensitivity analysis reveals two pairs of parameters that may constrain each other, and demonstrates how improved measurements of plant conductance and leaf water potential can constrain other portions of the parameter space.
COPD and Osteoporosis: Associated Factors in Patients Treated with Inhaled Corticosteroids

Purpose: Osteoporosis is a systemic skeletal disease with a consequent increase in fractures rates. Osteoporosis may be primary which is related with normal aging, or secondary which occurs in the presence of an underlying disease or medication. Osteoporosis is one of the significant comorbidities in chronic obstructive pulmonary disease (COPD). In this study, we aimed to investigate the presence of osteoporosis and the influencing factors in COPD patients. Patients and Methods: This is a two-group comparison study that was conducted among 30 COPD patients on inhaled corticosteroid (ICS) and 33 controls. It was conducted in the outpatient clinics at the Departments of Physical Medicine and Rehabilitation and Pulmonary Diseases in Bursa Uludag University Hospital, a tertiary reference center, in the northwest region of Turkey. For both groups, demographic variables, osteoporosis risk questioning, body mass index (BMI), bone mineral density (BMD), biochemical blood tests, vertebral fractures on lumbar and thoracic x-rays were recorded. COPD patients were also evaluated for lung functions via spirometry. Results: Thirty patients with COPD (Group 1) and 33 controls (Group 2) were included in the study. Comparing the demographic and biochemical data, no difference was found between the groups except smoking (pack/year) (p<0.001) and erythrocyte sedimentation rate (p<0.001), which were significantly high in COPD group. BMD in the COPD group was significantly lower in both hip and lumbar regions compared with the controls. There were significant correlations between L2 BMD values and pulmonary function tests. BMI was significantly low in osteoporotic COPD patients when compared with the non-osteoporotic COPD patients (p=0.002). Conclusion: In patients with COPD using inhaled corticosteroids, BMD was significantly low compared with the controls. Osteoporotic COPD patients had significantly lower BMI than non-osteoporotic. These findings suggest that pulmonary dysfunction and low BMI are associated with osteoporosis in COPD patients.
A Zoom Architecture Using Linear-Exponential Incremental ADC

This paper presents a zoom linear-exponential incremental analog-to-digital convertor (LE-IADC). A two-phase LE-IADC using second-order noise coupling (NC) is employed as the fine ADC. The second-order NC could further expedite the accumulation of the IADC, compared with the prior art using first-order NC. Therefore, it results in a higher theoretical resolution. However, such higher-order NC gives rise to an extremely poor maximum stable amplitude (MSA). Thanks to the zoom topology, the MSA loss could be inherently compensated. Mathematical analysis and behavioral-level simulation results are presented to confirm the principle of the proposed zoom LE-IADC.
ResearchMaterials Genome Engineering—Article Data Centric Design: A New Approach to Design of Microstructural Material Systems

Building processing, structure, and property (PSP) relations for computational materials design is at the heart of the Materials Genome Initiative in the era of high-throughput computational materials science. Recent technological advancements in data acquisition and storage, microstructure characterization and reconstruction (MCR), machine learning (ML), materials modeling and simulation, data processing, manufacturing, and experimentation have signiﬁcantly advanced researchers’ abilities in building PSP relations and inverse material design. In this article, we examine these advancements from the perspective of design research. In particular, we introduce a data-centric approach whose fundamental aspects fall into three categories: design representation, design evaluation, and design synthesis. Developments in each of these aspects are guided by and beneﬁt from domain knowledge. Hence, for each aspect, we present a wide range of computational methods whose integration realizes data-centric materials discovery and design. (cid:1) 2022 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Increasing the value of an early bird incentive in a mixed-mode longitudinal survey

This paper investigates the effect on response rates of changing the value of an early bird incentive (EBI) sent to respondents completing an online questionnaire during the first five weeks of fieldwork. The experiment analysed in this paper, which was embedded in wave 12 of Understanding Society, a longitudinal mixed-mode survey, tested two different values of the EBI, £10 and £20. The experiment covered two groups, one that had been administered a web-first design in previous waves and had been offered the EBI, and another that transitioned from a CAPIonly design to a web-first sequential mixed-mode design in wave 12 and was therefore offered the EBI for the first time. We also examined the effect of the higher incentives on fieldwork efforts and sample composition. We found that increasing the value of the incentive had a positive effect on response rates for panel members who had been offered the incentive previously.
9.03.03 Orthoptic Training for the Treatment of Vision or Learning Disabilities

[TOP] Office-based vergence/accommodative therapy may be considered medically necessary for patients with symptomatic convergence insufficiency if, following a minimum of 12 weeks of home-based therapy (e.g., push-up exercises using an accommodative target; push-up exercises with additional base-out prisms; jump to near convergence exercises; stereogram convergence exercises; recession from a target; and maintaining convergence for 30-40 seconds), symptoms have failed to improve.
Industrial-strength Rule Interoperability using Model Driven Engineering

Model Driven Engineering (MDE) is rapidly maturing and is being deployed in several situations. We report here on an experiment conducted in the context of ILOG, a leader in the development of Business Rule Management Systems (BRMS). BRMSs aim at enabling business users automating their business policies. There is a growing number of BRMS supporting different languages, but also a lack of tools for bridging them. In this paper, we present an approach based on MDE techniques for bridging rule languages; the solution has been fully implemented and tested on different BRMS. The success of the experiment has led to the development of a significant number of model transformations. At the same time, this deployment has shown new problems arising from the management of a high number of artifacts. We discuss the positive assessment of MDE in this field, but also the need to address the complexity generated.
IDENTIFICATION AND ESTIMATION OF TREATMENT EFFECTS WITH A REGRESSION-DISCONTINUITY DESIGN

Ž. THE REGRESSION DISCONTINUITY RD data design is a quasi-experimental design with the defining characteristic that the probability of receiving treatment changes discontinuously as a function of one or more underlying variables. This data design arises frequently in economic and other applications but is only infrequently exploited as a source of identifying information in evaluating effects of a treatment. In the first application and discussion of the RD method, Thistlethwaite and Campbell Ž. 1960 study the effect of student scholarships on career aspirations, using the fact that awards are only made if a test score exceeds a threshold. More recently, Van der Klaauw Ž. 1997 estimates the effect of financial aid offers on students’ decisions to attend a particular college, taking into account administrative rules that set the aid amount partly on the basis of a discontinuous function of the students’ grade point average and SAT Ž. score. Angrist and Lavy 1999 estimate the effect of class size on student test scores, taking advantage of a rule stipulating that another classroom be added when the average Ž. class size exceeds a threshold level. Finally, Black 1999 uses an RD approach to estimate parents’ willingness to pay for higher quality schools by comparing housing prices near geographic school attendance boundaries. Regression discontinuity methods have potentially broad applicability in economic research, because geographic boundaries or rules governing programs often create discontinuities in the treatment assignment mechanism that can be exploited under the method. Although there have been several discussions and applications of RD methods in the literature, important questions still remain concerning sources of identification and ways of estimating treatment effects under minimal parametric restrictions. Here, we show that identifying conditions invoked in previous applications of RD methods are often overly strong and that treatment effects can be nonparametrically identified under an RD design by a weak functional form restriction. The restriction is unusual in that it requires imposing continuity assumptions in order to take advantage of the known discontinuity in the treatment assignment mechanism. We also propose a way of nonparametrically estimating treatment effects and offer an interpretation of the Wald estimator as an RD estimator.
Investigation of thermal interactions between the exhaust jet and airplane skin in small aircrafts

An advanced numerical model of the exhaust jet and its thermal interaction with the aircraft body (fuselage, wings and flaps) was developed in this paper and then applied for investigations of two aircraft prototypes in different configurations. Both airplanes were equipped with new turboprop engines. Therefore their new exhaust systems should be carefully analysed. The first of the investigated airplanes in the tractor configuration with one engine located in the fuselage (TR1) had the exhaust outlets below the nacelle. The second one was also in the tractor configuration with two engines located on the wings (TR2) and had the exhaust outlets on the rear part of the nacelles. The aim of the performed analyses was to check if the exhaust systems were properly designed and streams of hot exhaust gases would not contribute to airplane cover softening or even melting for the most adverse flight conditions.
Progress in the development of a therapeutic vaccine for breast cancer

Correspondence: Andrew L Coveler Tumor vaccine Group, Center for Translational Medicine in women’s Health, University of washington, 815 Mercer Street, Box 358050, Seattle, wA 98109, USA Tel +1 206 288 7509 Fax +1 206 685 3128 email acoveler@u.washington. edu Abstract: Various human malignancies are immunogenic and recent cancer vaccine trials have demonstrated potential survival benefit. Breast cancer is immunogenic and there are several tumor associated antigens for which breast cancer vaccines have been developed. Breast cancer vaccines are designed to stimulate the immune response at various steps in the native antigen processing pathway for immunosurveillance. Human epidermal growth factor receptor 2 (HER-2/neu), mucin 1 (MUC-1), and human telomerase reverse transcriptase (hTERT) are some of the most studied antigens actively being targeted for vaccination in breast cancer patients. These vaccines are designed to elicit cytotoxic and/or helper T cell responses. Over the last several years, there has been reported progress in human clinical trials for these antigens. Cancer vaccines have repeatedly been shown to be safe with production of minimal toxicity. Recent clinical advances in the development of cancer vaccines demonstrate the potential clinical benefit that cancer vaccines hold.
Chalcogenic orbital density waves in the weak- and strong-coupling limit

Stimulated by recent works highlighting the indispensable role of Coulomb interactions in the formation of helical chains and chiral electronic order in the elemental chalcogens, we explore the p-orbital Hubbard model on a one-dimensional helical chain. By solving it in the Hartree approximation we find a stable ground state with a period-three orbital density wave. We establish that the precise form of the emerging order strongly depends on the Hubbard interaction strength. In the strong coupling limit, the Coulomb interactions support an orbital density wave that is qualitatively different from that in the weak-coupling regime. We identify the phase transition separating these two orbital ordered phases, and show that realistic values for the inter-orbital Coulomb repulsion in elemental chalcogens place them in the weak coupling phase, in agreement with observations of the order in the elemental chalcogens.