Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabolic Factors Associated with Risk of Renal Cell Carcinoma

Previous studies have shown that obesity and hypertension are associated with increased risk of renal cell carcinoma (RCC), but less is known about the association to other metabolic factors. In the Metabolic Syndrome and Cancer project (Me-Can) data on body mass index (BMI, kg/m2), blood pressure, and circulating levels of glucose, cholesterol, and triglycerides were collected from 560,388 men and women in cohorts from Norway, Austria, and Sweden. By use of Cox proportional hazard models, hazard ratios (HR) were calculated for separate and composite metabolic exposures. During a median follow-up of 10 years, 592 men and 263 women were diagnosed with RCC. Among men, we found an increased risk of RCC for BMI, highest vs. lowest quintile, (HR = 1.51, 95% CI 1.13–2.03), systolic blood pressure, (HR = 3.40, 95% CI 1.91–6.06), diastolic blood pressure, (HR = 3.33, 95% CI 1.85–5.99), glucose, (HR = 3.75, 95% CI 1.46–9.68), triglycerides, (HR = 1.79, 95% CI 1.00–3.21) and a composite score of these metabolic factors, (HR = 2.68, 95% CI 1.75–4.11). Among women we found an increased risk of RCC for BMI, highest vs. lowest quintile, (HR = 2.21, 95% CI 1.32–3.70) and the composite score, (HR = 2.29, 95% CI 1.12–4.68). High levels of the composite score were also associated with risk of death from RCC among both men and women. No multiplicative statistical or biological interactions between metabolic factors on risk of RCC were found. High levels of BMI, blood pressure, glucose and triglycerides among men and high BMI among women were associated with increased risk of RCC.
Is Fine Grained Classification Different ?

We performed experiments on two fine-grained classification tasks using a state-of-the-art pipeline (descriptor + dictionary + LLC encoding + max pooling + linear SVM). We found that this standard pipeline out-performed a dictionary-free classification technique (stacked evidence trees) that was specifically designed for fine-grained classification. The success of the method depends on two factors: (a) having high-resolution images that capture the fine detail of the objects and (b) using very large dictionaries so that this fine detail is not lost during encoding.
THE SCENARIOS APPROACH TO ATTENUATION-BASED REMEDIES FOR INORGANIC AND RADIONUCLIDE CONTAMINANTS

Guidance materials based on use of conceptual model scenarios were developed to assist evaluation and implementation of attenuation-based remedies for groundwater and vadose zones contaminated with inorganic and radionuclide contaminants. The Scenarios approach is intended to complement the comprehensive information provided in the US EPA's Technical Protocol for Monitored Natural Attenuation (MNA) of Inorganic Contaminants by providing additional information on site conceptual models and extending the evaluation to consideration of Enhanced Attenuation approaches. The conceptual models incorporate the notion of reactive facies, defined as units with hydrogeochemical properties that are different from surrounding units and that react with contaminants in distinct ways. The conceptual models also incorporate consideration of biogeochemical gradients, defined as boundaries between different geochemical conditions that have been induced by waste disposal or other natural phenomena. Gradients can change over time when geochemical conditions from one area migrate into another, potentially affecting contaminant mobility. A recognition of gradients allows the attenuation-affecting conditions of a site to be projected into the future. The Scenarios approach provides a stepwise process to identify an appropriate category of conceptual model and refine it for a specific site. Scenario materials provide links to pertinent sections in the EPA technical protocol and present information about contaminant mobility and important controlling mechanism for attenuation-based remedies based on the categories of conceptual models.
HyperVerify: A VM-assisted Architecture for Monitoring Hypervisor Non-control Data

Continuing bug reports and exploits in hyper visors indicate that hyper visors face similar integrity threats as tradition software. Previous approaches to protect a hyper visor that utilize hardware features are not easy to be extended. Besides, they mainly focus on code or control data integrity, without pay much attention to protecting non-control data. In this paper, we present Hyper Verify, a novel architecture to monitor hyper visor non-control data using a trusted VM. Since a VM cannot directly access a hyper visor's memory, Hyper Verify programs a popular device driver to read the hyper visor's hardware state in the trusted VM. Then a memory analysis library is used to translate the low-level hardware state into the high level hyper visor context. Several monitoring processes use such context to monitor hyper visor non-control data integrity. Each of the processes is responsible for monitoring one kind of non-control data. It is flexible for Hyper Verify to support monitoring new kinds of data structure. The experimental evaluation of our prototype shows that Hyper Verify incurs at most 4% performance overhead to end users.
Role of Central and Mixed Venous Oxygen Saturation Measurement in Perioperative Care

Complications after major surgery are a leading cause of morbidity and mortality. The etiology of postoperative complications is complex, but poor cardiorespiratory reserve appears to be a key factor. There is increasing interest in the use of central and mixed venous oxygen saturation to guide therapeutic interventions during the perioperative period. However, a detailed understanding of the physiologic principles of venous oximetry is essential for safe and effective use in clinical practice. Venous oxygen saturation reflects the balance between global oxygen delivery and oxygen consumption, which may be affected by a wide range of factors during the perioperative period. The purpose of this article is to describe the physiology and measurement of mixed and central venous oxygen saturation and to explore the findings of clinical investigations of their use in perioperative care.
Activity Recognition for a Smartphone Based Travel Survey Based on Cross-User History Data

In transport modeling and prediction, trip purposes play an important role. The most particular case is activity-based modeling, whereby mobility choices (e.g. mode, path, and departure time) are made in order to carry out specific activities. A current challenge, however, lies on getting appropriate data that relates observed trips with their purpose. Recently, a Smartphone-based travel survey (the Future Mobility Survey, FMS) was conducted in Singapore that collected location data from 793 participants. Each FMS user was required to collect data for at least 14 days and validate at least 5 of them. This dataset presents diverse opportunities in terms of developing machine learning models for the future versions of FMS, where the validation process is intelligent and easy to use (e.g. having pre-filled activities associated to the user traces). This paper proposes a learning model that, given a stop location, identifies the most likely activity associated to it. Our data often contains errors or noise due to limited functionality of physical sensors in a dense area, and human mistakes in the validation process. To alleviate this effect, we generate heterogeneous features by different spatial quantization techniques and apply ensemble learning for a good generalization performance.
Flow Control for Limited Buffer Multicast

Analyses a multiround flow control algorithm that attempts to minimize the time required to multicast a message to a group of recipients and receive responses directly from each group member. Such a flow control algorithm may be necessary because the hurry of responses to the multicast can overflow the buffer space of the process that issued the multicast. The condition that each recipient directly respond to the multicast prevents the use of reliable multicast protocols based on software combining trees or negative-acknowledgments. The flow control analysed algorithm directs the responding processes to hold their responses for some period of time, called the backoff time, before sending them to the originator. The backoff time depends on the number of recipients that respond, the originator's available buffer space and buffer service time distribution, and the number of times that the originator is willing to retransmit its message. This paper develops an approximate analysis of the service time distribution of the limited-buffer preemptive queuing process that occurs within the protocol processing layers of a multiprogrammed operating system. It then uses this model to calculate multicast backoff times. The paper reports experimental verification of the accuracy of this service time model and discusses its application to the multicast flow control problem. >
Automatic Hierarchical Object Decomposition for Object Recognition

Industrial applications of 2D object recognition such as quality control often demand robustness, highest accuracy, and real-time computation from the object recognition approach. Simultaneously fulfilling all of these demands is a hard problem and has recently drawn considerable attention within the research community of close-range photogrammetry and computer vision. The problem is complicated when dealing with objects or models consisting of several rigid parts that are allowed to move with respect to each other. In this situation, approaches searching for rigid objects fail since the appearance of the model may substantially change under the variations caused by the movements. In this paper, an approach is proposed that not only facilitates the recognition of such partsbased models but also fulfills the above demands. The object is automatically decomposed into single rigid parts based on several example images that express the movements of the object parts. The mutual movements between the parts are analyzed and represented in a graph structure. Based on the graph, a hierarchical model is derived that minimizes the search effort during a subsequent recognition of the object in an arbitrary image.
UNDERWATER PHOTOGRAMMETRY IN THE NORTH SEA

Underwater photogrammetry is being used in the particularly hostile environment of the North Sea where it has been put into commercially viable operation. The authors discuss underwater photogrammetry related to other means of inspection of oil platforms. They also deal with operational experience of 35 mm and 70 mm cameras, camera calibration, the provision of control and photogrammetric observations and data analysis. The demand for underwater photogrammetry continues to grow.
Making Sense of Microposts (#MSM2013) Concept Extraction Challenge

Microposts are small fragments of social media content that have been published using a lightweight paradigm (e.g. Tweets, Facebook likes, foursquare check-ins). Microposts have been used for a variety of applications (e.g., sentiment analysis, opinion mining, trend analysis), by gleaning useful information, often using third-party concept extraction tools. There has been very large uptake of such tools in the last few years, along with the creation and adoption of new methods for concept extraction. However, the evaluation of such efforts has been largely consigned to document corpora (e.g. news articles), questioning the suitability of concept extraction tools and methods for Micropost data. This report describes the Making Sense of Microposts Workshop (#MSM2013) Concept Extraction Challenge, hosted in conjunction with the 2013 World Wide Web conference (WWW'13). The Challenge dataset comprised a manually annotated training corpus of Microposts and an unlabelled test corpus. Participants were set the task of engineering a concept extraction system for a defined set of concepts. Out of a total of 22 complete submissions 13 were accepted for presentation at the workshop; the submissions covered methods ranging from sequence mining algorithms for attribute extraction to part-of-speech tagging for Micropost cleaning and rule-based and discriminative models for token classification. In this report we describe the evaluation process and explain the performance of different approaches in different contexts.
CO2-system development in young sea ice and CO2 gas exchange at the ice/air interface mediated by brine and frost flowers in Kongsfjorden, Spitsbergen

Abstract In March and April 2010, we investigated the development of young landfast sea ice in Kongsfjorden, Spitsbergen, Svalbard. We sampled the vertical column, including sea ice, brine, frost flowers and sea water, to determine the CO2 system, nutrients, salinity and bacterial and ice algae production during a 13 day interval of ice growth. Apart from the changes due to salinity and brine rejection, the sea-ice concentrations of total inorganic carbon (C T), total alkalinity (A T), CO2 and carbonate ions (CO3 2–) in melted ice were influenced by dissolution of calcium carbonate (CaCO3) precipitates (25–55 μmol kg-1) and played the largest role in the changes to the CO2 system. The C T values were also influenced by CO2 gas flux, bacterial carbon production and primary production, which had a small impact on the C T. The only exception was the uppermost ice layer. In the top 0.05 m of the ice, there was a CO2 loss of ∼20 μmol kg-1 melted ice (1 mmol m-2) from the ice to the atmosphere. Frost flowers on newly formed sea ice were important in promoting ice-air CO2 gas flux, causing a CO2 loss to the atmosphere of 140-800 μmol kg--1 d-1 melted frost flowers (7-40 mmol m-2 d–1).
Exploiting Type Annotations

The Haskell type system has been designed in such a way that all allowed types can be inferred automatically; any explicit type specification only serves as a means of documentation and safeguarding. Consequently, a programmer is free to omit any type signature, and the program will still type check. The price to be paid for this convenience is limited expressiveness of the type system: even if a programmer is willing to explicitly provide higher-ranked types with polymorphic arguments, this is not allowed. In an effort to obtain the same expressiveness as System F, the use of universally quantified types on higher ranked positions in types in particular has received much attention in recent years. Because type inference for such types in general is not possible, much work has been done to investigate which limitations on higher ranked types still allow type inference. In this paper we explore an alternative, algorithmic, approach to this problem, which does not limit expressiveness: we propagate explicitly specified type information to all program locations where this information provides starting information for a standard Hindley-Milner type inference algorithm.
Back to the future: a non-automated method for constructing transfer models

Representing domain knowledge is important for constructing educational software, and automated approaches have been proposed to construct and refine such models. In this paper, instead of applying automated and computationally intensive approaches, we simply start with existing hand- constructed transfer models at various levels of granularity and use them as a lens to examine student learning. Specifically, we are interested in seeing whether we can evaluate schools by examining the grain-size at which its students are best represented. Also, we are curious about whether different types of students are best represented by different transfer models. We found that better schools and stronger students are best represented by models with a fewer number of skills. Weaker students and schools are best represented, for our data, by models that allow no transfer of knowledge in between skills. Perhaps surprisingly, to accurately predict the level at which a student represents knowledge it is sufficient to know his standardized test score rather than indicators of socio economic status or his school.
Specifying timing constraints and composite events: an application in the design of electronic brokerages

Increasingly, business applications need to capture consumers' complex preferences interactively and monitor those preferences by translating them into event-condition-action (ECA) rules and syntactically correct processing specification. An expressive event model to specify primitive and composite events that may involve timing constraints among events is critical to such applications. Relying on the work done in active databases and real-time systems, this research proposes a new composite event model based on real-time logic (RTL). The proposed event model does not require fixed event consumption policies and allows the users to represent the exact correlation of event instances in defining composite events. It also supports a wide-range of domain-specific temporal events and constraints, such as future events, time-constrained events, and relative events. This event model is validated within an electronic brokerage architecture that unbundles the required functionalities into three separable components - business rule manager, ECA rule manager, and event monitor - with well-defined interfaces. A proof-of-concept prototype was implemented in the Java programming language to demonstrate the expressiveness of the event model and the feasibility of the architecture. The performance of the composite event monitor was evaluated by varying the number of rules, event arrival rates, and type of composite events.
‘The Class is Always Cheaper on the Other Side’: Socioeconomic discrepancies in the cost of using recreational facilities

Abstract While the socioeconomic gradient associated with physical activity is well mapped, the affordability of accessing facilities has been unexplored relative to other participation barriers. This study investigated socioeconomic differences in access to, and the cost of participating in, a range of popular recreational activities. Data from surveys of all formal facilities in metropolitan Perth was analysed. The study found that it was generally more expensive to participate in facility‐based activities in low socioeconomic areas than in more advantaged areas. In no instances was the cost of undertaking activities substantially lower in low socioeconomic areas. These findings suggest that pricing structures further disadvantage people living in low socioeconomic areas — the same people that are under‐represented in achieving recommended levels of physical activity.
Cilia have high cAMP levels that are inhibited by Sonic Hedgehog-regulated calcium dynamics

Significance Primary cilia are immotile organelles composed of specialized structural and signaling proteins that are essential for Hedgehog (HH) signaling. cAMP-dependent protein kinase (PKA) critically regulates HH signaling, maintaining transcriptional repression. Ciliary PKA activity is critical for HH regulation; however, the signaling steps regulating PKA activity within cilia remain unclear/unexplored. Targeted sensors were used to measure signaling molecules specifically within cilia. We found that cilia have basally high cAMP and PKA activity, controlled by phosphatidylinositol (3,4,5)-trisphosphate, not G proteins. Sonic Hedgehog stimulation reduces ciliary cAMP and PKA activity, which is dependent on Ca2+ dynamics. Protein kinase A (PKA) phosphorylates Gli proteins, acting as a negative regulator of the Hedgehog pathway. PKA was recently detected within the cilium, and PKA activity specifically in cilia regulates Gli processing. Using a cilia-targeted genetically encoded sensor, we found significant basal PKA activity. Using another targeted sensor, we measured basal ciliary cAMP that is fivefold higher than whole-cell cAMP. The elevated basal ciliary cAMP level is a result of adenylyl cyclase 5 and 6 activity that depends on ciliary phosphatidylinositol (3,4,5)-trisphosphate (PIP3), not stimulatory G protein (Gαs), signaling. Sonic Hedgehog (SHH) reduces ciliary cAMP levels, inhibits ciliary PKA activity, and increases Gli1. Remarkably, SHH regulation of ciliary cAMP and downstream signals is not dependent on inhibitory G protein (Gαi/o) signaling but rather Ca2+ entry through a Gd3+-sensitive channel. Therefore, PIP3 sustains high basal cAMP that maintains PKA activity in cilia and Gli repression. SHH activates Gli by inhibiting cAMP through a G protein-independent mechanism that requires extracellular Ca2+ entry.
Wildland fire in ecosystems: effects of fire on cultural resources and archaeology

This state-of-knowledge review provides a synthesis of the effects of fire on cultural resources, which can be used by fire managers, cultural resource (CR) specialists, and archaeologists to more effectively manage wildland vegetation, fuels, and fire. The goal of the volume is twofold: (1) to provide cultural resource/archaeological professionals and policy makers with a primer on fuels, fire behavior, and fire effects to enable them to work more effectively with the fire management community to protect resources during fuels treatment and restoration projects and wildfire suppression activities; and (2) to provide fire and land management professionals and policy makers with a greater understanding of the value of cultural resource protection and the methods available to evaluate and mitigate risks to CR. The synthesis provides a conceptual fire effects framework for planning, managing, and modeling fire effects (chapter1) and a primer on fire and fuel processes and fire effects prediction modeling (chapter 2). A synthesis of the effects of fire on various cultural resource materials is provided for ceramics (chapter 3), lithics (chapter 4), rock art (chapter 5), historic-period artifacts/materials (chapter 6), and below-ground features (chapter 7). Chapter 8 discusses the importance of cultural landscapes to indigenous peoples and emphasizes the need to actively involve native people in the development of collaborative management plans. The use and practical implications of this synthesis are the subject of the final chapter (chapter 9).
Ad-hoc on-demand distance vector routing

An ad-hoc network is the cooperative engagement of a collection of mobile nodes without the required intervention of any centralized access point or existing infrastructure. We present Ad-hoc On Demand Distance Vector Routing (AODV), a novel algorithm for the operation of such ad-hoc networks. Each mobile host operates as a specialized router, and routes are obtained as needed (i.e., on-demand) with little or no reliance on periodic advertisements. Our new routing algorithm is quite suitable for a dynamic self starting network, as required by users wishing to utilize ad-hoc networks. AODV provides loop-free routes even while repairing broken links. Because the protocol does not require global periodic routing advertisements, the demand on the overall bandwidth available to the mobile nodes is substantially less than in those protocols that do necessitate such advertisements. Nevertheless we can still maintain most of the advantages of basic distance vector routing mechanisms. We show that our algorithm scales to large populations of mobile nodes wishing to form ad-hoc networks. We also include an evaluation methodology and simulation results to verify the operation of our algorithm.
DLV - A System for Declarative Problem Solving

DLV is an efficient logic programming and non-monotonic reasoning (LPNMR) system with advanced knowledge representation mechanisms and interfaces to classic relational database systems. Its core language is disjunctive datalog (function-free disjunctive logic programming) under the Answer Set Semantics with integrity constraints, both default and strong (or explicit) negation, and queries. Integer arithmetics and various built-in predicates are also supported. In addition DLV has several frontends, namely brave and cautious reasoning, abductive diagnosis, consistency-based diagnosis, a subset of SQL3, planning with action languages, and logic programming with inheritance.