Miracle-dz/UniFAR-FTUs huggingface dataset:
Ecological constraints on planktonic nitrogen fixation in saline estuaries. I. Nutrient and trophic controls

Heterocystous, planktonic cyanobacteria capable of fixing atmospheric N2 into available nitrogen (N) are common and critically important to nutrient cycling in many lakes, yet they are rarely observed in estuaries at salinities >10 ppt, even when strongly N limited. In a series of meso- cosm experiments using water from Narragansett Bay (Rhode Island), we manipulated top-down (grazing) and bottom-up (nutrient) factors hypothesized to exclude heterocystous cyanobacteria from estuaries. We previously reported that planktonic, heterocystous cyanobacteria grew and fixed N in the absence of grazers. Here, we focus on responses to phosphorus (P) additions and grazer manipu- lations. Zooplankton (Acartia sp.) populations typical of temperate zone estuaries suppressed cyanobacteria, and their influence was direct through grazing rather than indirect on nutrient stoi- chiometry. Cyanobacterial abundance and heterocysts were low in treatments with no external P inputs. Concentrations of dissolved inorganic P comparable to those in Narragansett Bay were obtained only in P-fertilized mesocosms. Unlike previous estuarine mesocosm experiments with P fertilization, planktonic cyanobacteria grew and fixed N in our experimental systems. However, mean cell and heterocyst abundances under the most favorable conditions (high P, low N:P, and low grazers) were much lower than in comparable freshwater experiments, with N limitation maintained. These results support the hypothesis that intrinsic growth of heterocystous cyanobacteria in saline estuaries is slower than in freshwater, and that slower growth is unlikely to be due to systematic dif- ferences in P availability. Slow growth, combined with grazing, can severely limit development of planktonic, N-fixing cyanobacterial blooms in estuaries.
Adaptive Concurrency Control for Transactional Memory

Transactional applications may exhibit fluctuating amounts of contention during execution. Excessive numbers of threads executing transactions can produce phases with a high transaction abort ratio. while few threads executing transactions will under-perform in phases with low contention. This paper presents the first application of adaptive concurrency control to TM in order to dynamically adjust the number of threads executing transactions concurrently. Four adaptive schemes are implemented in DSTM2, a software TM implementation, and evaluated against a TM application with complex and realistic behavior. Adaptive concurrency control complements existing contention management policies that capture which transaction should be aborted when two transactions conflict.
Tables as Semi-structured Knowledge for Question Answering

Question answering requires access to a knowledge base to check facts and reason about information. Knowledge in the form of natural language text is easy to acquire, but difficult for automated reasoning. Highly-structured knowledge bases can facilitate reasoning, but are difficult to acquire. In this paper we explore tables as a semi-structured formalism that provides a balanced compromise to this trade-off. We first use the structure of tables to guide the construction of a dataset of over 9000 multiple-choice questions with rich alignment annotations, easily and efficiently via crowd-sourcing. We then use this annotated data to train a semi-structured feature-driven model for question answering that uses tables as a knowledge base. In benchmark evaluations, we significantly outperform both a strong unstructured retrieval baseline and a highly structured Markov Logic Network model.
Prospective associations between problematic eating attitudes in midchildhood and the future onset of adolescent obesity and high blood pressure123

Background: Clinically diagnosed eating disorders may have adverse cardiometabolic consequences, including overweight or obesity and high blood pressure. However, the link between problematic eating attitudes in early adolescence, which can lead to disordered eating behaviors, and future cardiometabolic health is, to our knowledge, unknown. Objective: We assessed whether variations in midchildhood eating attitudes influence the future development of overweight or obesity and high blood pressure. Design: Of 17,046 children who participated in the Promotion of Breastfeeding Intervention Trial (PROBIT), we included 13,557 participants (79.5% response rate) who completed the Children’s Eating Attitudes Test (ChEAT) at age 11.5 y and in whom we measured adiposity and blood pressure at ages 6.5, 11.5, and 16 y. We assessed whether ChEAT scores ≥85th percentile (indicative of problematic eating attitudes) compared with scores <85th percentile at age 11.5 y were associated with new-onset overweight, obesity, high systolic blood pressure, or high diastolic blood pressure between midchildhood and early adolescence. Results: After controlling for baseline sociodemographic confounders, we observed positive associations of problematic eating attitudes at age 11.5 y with new-onset obesity (OR: 2.18; 95% CI: 1.58, 3.02), new-onset high systolic blood pressure (OR: 1.34; 95% CI: 1.05, 1.70), and new-onset high diastolic blood pressure (OR: 1.25; 95% CI: 0.99, 1.58) at age 16 y. After further controlling for body mass index at age 6.5 y, problematic eating attitudes remained positively associated with new-onset obesity (OR: 1.80; 95% CI: 1.28, 2.53); however, associations with new-onset high blood pressure were attenuated (OR: 1.14; 95% CI: 0.89, 1.45 and OR: 1.09; 95% CI: 0.86, 1.39 for new-onset systolic and diastolic blood pressure, respectively). Conclusions: Problematic eating attitudes in midchildhood seem to be related to the development of obesity in adolescence, a relatively novel observation with potentially important public health implications for obesity control. PROBIT was registered at clinicaltrials.gov as NCT01561612 and isrctn.com as ISRCTN37687716.
An Encoder-Decoder Based Convolution Neural Network (CNN) for Future Advanced Driver Assistance System (ADAS)

We propose a practical Convolution Neural Network (CNN) model termed the CNN for Semantic Segmentation for driver Assistance system (CSSA). It is a novel semantic segmentation model for probabilistic pixel-wise segmentation, which is able to predict pixel-wise class labels of a given input image. Recently, scene understanding has turned out to be one of the emerging areas of research, and pixel-wise semantic segmentation is a key tool for visual scene understanding. Among future intelligent systems, the Advanced Driver Assistance System (ADAS) is one of the most favorite research topic. The CSSA is a road scene understanding CNN that could be a useful constituent of the ADAS toolkit. The proposed CNN network is an encoder-decoder model, which is built on convolutional encoder layers adopted from the Visual Geometry Group’s VGG-16 net, whereas the decoder is inspired by segmentation network (SegNet). The proposed architecture mitigates the limitations of the existing methods based on state-of-the-art encoder-decoder design. The encoder performs convolution, while the decoder is responsible for deconvolution and un-pooling/up-sampling to predict pixel-wise class labels. The key idea is to apply the up-sampling decoder network, which maps the low-resolution encoder feature maps. This architecture substantially reduces the number of trainable parameters and reuses the encoder’s pooling indices to up-sample to map pixel-wise classification and segmentation. We have experimented with different activation functions, pooling methods, dropout units and architectures to design an efficient CNN architecture. The proposed network offers a significant improvement in performance in segmentation results while reducing the number of trainable parameters. Moreover, there is a considerable improvement in performance in comparison to the benchmark results over PASCAL VOC-12 and the CamVid.
An on-line imitative test of speech-pattern contrast perception (OlimSpac): developmental effects in normally hearing children.

PURPOSE The goal was to assess the effects of maturation and phonological development on performance, by normally hearing children, on an imitative test of auditory capacity (On-Line Imitative Test of Speech-Pattern Contrast Perception [OlimSpac]; Boothroyd, Eisenberg, & Martinez, 2006; Eisenberg, Martinez, & Boothroyd, 2003, 2007). METHOD Thirty-four hearing children (aged between 1;8 [years;months] and 6;7) were asked to imitate nonword utterances. Responses were evaluated by a blinded listener in an 8-alternative forced-choice task, giving information on the children's ability to convey, by imitation, information about 6 binary phonemic contrasts. RESULTS Four children declined participation. Among 30 children aged 2;7 or older, performance improved significantly with age and varied with contrast. All children 3 years of age or older attained passing scores (7 or 8 correct responses in 8 binary trials) on at least 5 of the 6 contrasts. Post-alveolar consonant place was the contrast most often failed. CONCLUSIONS When evaluated on a pass/fail basis, normally hearing children 3 years of age or older are likely to demonstrate auditory perception of most phonemic contrasts using this imitative test. Phonological development and other task-related factors have only a modest effect on performance by normally hearing children after 3 years of age. The effects of hearing loss, hearing age, sensory assistance, and listening experience in children with hearing loss remain to be determined.
Of packets and people: a user-centered approach to quality of service

Multimedia communication has gained increasing attention, both from the application side and the network provider side. While resource provisioning for QoS support in packet switched networks has led to the design and development of sophisticated QoS architectures, notably ATM, IntServ or DiffServ, research has not exactly been user or application-context centered. In the cause of the evolution of QoS architectures, the integrated service network approach has lost momentum, and with it, the notion of QoS guarantees. Differentiation of QoS classes within the DiffServ framework is based on the definition of various per-hop behaviors. What is currently missing is a technique for specification and mapping of application and user QoS preferences onto evolving service profiles. In addition, adaptation of applications (and users) is becoming increasingly important in the face of dominating weak QoS-assurance paradigms, both in wireline and wireless environments. As a prerequisite, this paper investigates cognitive and perceptive conditioning of users and applications in a situated setting. The contribution of this paper is twofold: first, essential empirical results on user QoS preferences and QoS graduations are presented, and second, methodological foundations are laid for investigating user-centered QoS.
Cancer Management and Research Dovepress Pegylated Liposomal Doxorubicin: Appraisal of Its Current Role in the Management of Epithelial Ovarian Cancer

Pegylated liposomal doxorubicin (PLD) has become a major component in the routine management of epithelial ovarian cancer. The drug is frequently employed as a single agent in the platinum-resistant setting, and recently reported data reveal the superiority of the combination of PLD plus carboplatin, compared with the platinum drug plus paclitaxel, in delaying the time to disease progression in women with recurrent (potentially platinum-sensitive) disease. Current research efforts involving PLD in ovarian cancer are focusing on adding novel targeted drugs to this cytotoxic agent. The utility of such approaches in the platinum-resistant population, compared with the sequential administration of single agents active in this setting, remains to be determined. Standard management of epithelial ovarian cancer Initial management of epithelial ovarian cancer includes surgical staging and an attempt at optimal and, if possible, complete surgical cytoreduction. 1 Surgery is followed by delivery of platinum-based chemotherapy, which in the setting of small volume residual disease may include the delivery of at least the platinum agent via the intraperitoneal route. Multiple trials conducted over the past decade have failed to document the superiority of a variety of approaches compared with the standard doublet of a platinum (carboplatin or cisplatin) agent plus a taxane (paclitaxel or docetaxel). 3 An important Phase 3 trial conducted by the Japanese Gynecologic Oncology Group revealed the striking improvement in progression-free survival (PFS) associated with the weekly administration of paclitaxel compared with the standard every-3-week regimen, with an improvement in 3-year overall survival. 4 Data regarding median overall survival are likely to be reported within the next year. Two preliminary reports of Phase 3 trials that compared a carboplatin plus pacli-taxel regimen to this two-drug program plus the addition of the anti-angiogenic agent, bevacizumab, revealed the novel program significantly improved PFS. 5,6 Data on overall survival are pending. An alternative approach to initial treatment of advanced ovarian cancer in the setting where the presence of extensive disease would appear to prevent successful initial surgical cytoreduction would be to deliver several cycles (generally 3 or 4) of platinum/taxane chemotherapy (after obtaining histological documentation of a malignancy consistent with an ovarian or primary peritoneal cancer) and to follow
Designing Business Models for the Internet of Things

This article investigates challenges pertaining to business model design in the emerging context of the Internet of Things (IOT). The evolution of business perspectives to the IOT is driven by two underlying trends: i) the change of focus from viewing the IOT primarily as a technology platform to viewing it as a business ecosystem; and ii) the shift from focusing on the business model of a firm to designing ecosystem business models. An ecosystem business model is a business model composed of value pillars anchored in ecosystems and focuses on both the firm's method of creating and capturing value as well as any part of the ecosystem's method of creating and capturing value. The article highlights three major challenges of designing ecosystem business models for the IOT, including the diversity of objects, the immaturity of innovation, and the unstructured ecosystems. Diversity refers to the difficulty of designing business models for the IOT due to a multitude of different types of connected objects combined with only modest standardization of interfaces. Immaturity suggests that quintessential IOT technologies and innovations are not yet products and services but a "mess that runs deep". The unstructured ecosystems mean that it is too early to tell who the participants will be and which roles they will have in the evolving ecosystems. The study argues that managers can overcome these challenges by using a business model design tool that takes into account the ecosystemic nature of the IOT. The study concludes by proposing the grounds for a new design tool for ecosystem business models and suggesting that "value design" might be a more appropriate term when talking about business models in ecosystems. New web-based business models being hatched for the Internet of Things are bringing together market players who previously had no business dealings with each other. Through partnerships and acquisitions, […] they have to sort out how they will coordinate their business development efforts with customers and interfaces with other stakeholders.
Trade-Induced Investment-Led Growth

This paper presents five theoretical openness-and-growth links that can account for trade-induced investment-led growth. The links are all demonstrated with neoclassical growth models developed in the context of trade models that allow for imperfect competition and scale economies. This sort of old-growth-theory-in-a-new-trade-model has not been thoroughly explored in the literature since the profession skipped from old-growth-old-trade models straight to new-growth-new- trade models. Nonetheless, such models are necessary to explain several key aspects of the econometric evidence on trade and growth. For example, cross-country data suggests that openness influences growth only via its effect on investment, and suggests that openness promotes investment in all countries whatever the capital-intensive of their exports (contrary to predictions of the old-growth-old-trade models).
A conceptual model for the link between Central American biomass burning aerosols and severe weather over the south central United States

Each spring, smoke particles from fires over the Yucatan Peninsula and south Mexico cross over the Gulf of Mexico into the United States (US) under the control of moist oceanic air flow from the southwestern branch of the subtropical (Bermuda) high. Smoke can be transported deep into the south central US, where dry lines and warm conveyor belts are frequently formed and cause deep convection and severe weather. Lyons et al (1998 Science 282 77–80) and Murray et al (2000 Geophys. Res. Lett. 27 2249–52) noticed a ∼50% increase of lightning along the smoke transport path over the south central US during the May 1998 Central American smoke episode. Here we present a conceptual model of coherent microphysical and meteorological mechanisms through which smoke may impact convective clouds and subsequently result in more severe weather over the south central US. The conceptual model depicts a chain of processes in which smoke particles are first activated as cloud condensation nuclei when they are entrained into the warm conveyor belt, a convective zone formed over the south central US as a result of the encounter between the mid-latitude trough and the subtropical Bermuda high. As the convection continues with deepening of the mid-latitude trough, the greater concentration of water cloud condensation nuclei delays the warm rain processes, enhances the development of ice clouds, and invigorates the updrafts, all of which contribute to the formation of severe weather such as hail and lightning. The conceptual model is based on the reasoning of physical mechanisms revealed in previous studies (over the tropical biomass region), and is supported here through the analysis of satellite data, ground observations, aerosol transport model results, and idealized cloud resolving simulations of a day in May 2003 when record tornado events occurred over the south central US. Further assessment of this conceptual model is discussed for future investigations.
18F-FDG PET-CT Findings Before and After Laparoscopic Cryoablation of Small Renal Mass: An Initial Report

The aim of this study was to describe the characteristics of positron emission tomography (PET) molecular imaging combined with low-dose computed tomography (CT) in small renal mass (SRM) treated with cryoablation (CA). Currently, treatment success is defined by the absence of contrast enhancement at CT. However, the use of contrast is relatively contraindicated in patients with renal function impairment, mandating alternative follow-up strategies. Several reasons were identified as criteria for performing PET-CT before and/or after SRM-CA in 9 patients, and the results were retrospectively studied. The histology revealed renal cell carcinoma in 7 patients and oncocytoma in 2 patients. In 6 patients, a PET-CT was performed before and after CA. In one patient, the PET-CT was performed only before CA and in 2 patients only after CA. Before CA, clearly there was metabolic uptake of fluorine-18 fluorodeoxyglucose (18F-FDG) in the SRM in all patients. Following CA, the absence of 18F-FDG uptakes in the SRM could clearly be noticed. However, the tracer cannot always be distinguished from focal recurrence or reactive inflammatory tissue. In one patient, asymptomatic metastatic bone lesions were noticed when performing PET-CT at follow-up. This pilot study with 18F-FDG PET-CT for the follow-up of SRM cryosurgery showed that 18F-FDG PET-CT imaging could be used to characterize cryoablative tissue injury at different times after CA.
Differentially Private Feature Selection via Stability Arguments, and the Robustness of the Lasso

We design differentially private algorithms for statistical model selection. Given a data set and a large, discrete collection of “models”, each of which is a family of probability distributions, the goal is to determine the model that best “fits” the data. This is a basic problem in many areas of statistics and machine learning. We consider settings in which there is a well-defined answer, in the following sense: Suppose that there is a nonprivate model selection proceduref which is the reference to which we compare our performance. Our differentially private algorithms output the correct valuef(D) wheneverf is stable on the input data setD. We work with two notions, perturbation stability and subsampling stability. We give two classes of results: generic ones, that apply to any function with discrete output set; and specific algorithms for the problem of sparse linear regression. The algorithms we describe are efficient and in some cases match the optimal nonprivate asymptotic sample complexity. Our algorithms for sparse linear regression require analyzing the stability properties of the popular LASSO estimator. We give sufficient conditions for the LASSO estimator to be robust to small changes in the data set, and show that these conditions hold with high probability under essentially the same stochastic assumptions that are used in the literature to analyze convergence of the LASSO.
Does Family Background Matter? - Returns to Education and Family Characteristics in Germany

This paper examines the impact of family background on wages and returns to education. Using data from the GSOEP, we show that family background matters in the determination of wages. Moreover, returns to education appear to be heterogeneous with family background accounting for part of this heterogeneity. Estimated returns to education are higher for individuals from families with lower education levels. However, a simple regression analysis suffers from serious endogeneity problems. The construction of a sibling sample allows to control for unobserved characteristics that are shared by family members. Using a family fixed-effects estimation we attempt to reduce the endogeneity bias. Our results suggest that the conventional estimates overstate the returns to education. Moreover, family background accounts or a large part of the variation in wages in the sibling sample.
Propagation Path Loss Models for Parking Buildings

This paper proposes a method to predict path loss in parking buildings. We performed measurements in two different of parking buildings at a frequency of 1.8 GHz and proposed new upper- and lower-bound models. The actual breakpoint distance was shorter than theoretical one because of the effective floor height due to cars. These models also include time-variant effect, cars in parking area. This time-variant effect influence on the wave propagation very high. The results have shown that the upper- and lower-bound models will be useful for the system and cell design of indoor wireless communication systems