LLukas22/scidocs huggingface dataset:
Development of Geotechnical Resistance Factors and Downdrag Load Factors for LRFD Foundation Strength Limit State Design Reference Manual

NOTICE The contents of this report reflect the views of the author, who is responsible for the facts and accuracy of the data presented herein. The contents do not necessarily reflect policy of the Department of Transportation. This report does not constitute a standard, specification, or regulation. Abstract This report summarizes the historical development of the resistance factors developed for the geotechnical foundation design sections of the AASHTO LRFD Bridge Design Specifications, and recommends how to specifically implement recent developments in resistance factors for geotechnical foundation design. In addition, recommendations regarding the load factor for downdrag loads, based on statistical analysis of available load test data and reliability theory, are provided. The scope of this report is limited to shallow and deep foundation geotechnical design at the strength limit state. 17. Forward With the advent of the AASHTO Load and Resistance Factor (LRFD) Bridge Design Specifications in 1992, there has been considerable focus on the geotechnical aspects of those specifications, since most geotechnical engineers are unfamiliar with LRFD concepts. This is especially true regarding the quantification of the level of safety needed for design. Up to the time of writing of this report, the geotechnical profession has typically used safety factors within an allowable stress design (ASD) framework (also termed working stress design, or WSD). For those agencies that use Load Factor Design (LFD), the safety factors for the foundation design are used in combination with factored loads in accordance with the AASHTO Standard Specifications for Highway Bridges (2002). The adaptation of geotechnical design and the associated safety factors to what would become the first edition of the AASHTO LRFD Bridge Design Specifications began in earnest with the publication of the results of NCHRP Project 24-4 as NCHRP Report 343 (Barker, et al., 1991). The details of the calibrations they conducted are provided in an unpublished Appendix to that report (Appendix A). This is the primary source of resistance factors for foundation design as currently published in AASHTO (2004). Since that report was published, changes have occurred in the specifications regarding load factors and design methodology that have required re-evaluation of the resistance factors. Furthermore, new studies have been or are being conducted that are yet to be implemented in the LRFD specifications. In 2002, the AASHTO Bridge Subcommittee initiated an effort, with the help of the Federal Highway Administration (FHWA), to rewrite the foundation design sections of the AASHTO …
Randomized Trial Acupuncture-Analgesia Following a Single Treatment Session in Chronic Whiplash is Unrelated to Autonomic Nervous System Changes : A Randomized Cross-over Trial

Methods: Thirty-nine patients with chronic WAD received 2 treatment sessions of identical duration, with acupuncture and relaxation therapy randomly crossed over in the 2 visits. The primary outcome measurement was the registration of autonomic nervous system parameters (heart rate, skin conductance, and heart rate variability parameters) during the administration of experimental pain. Endogenous analgesia was the secondary outcome.
Methods of data collection in qualitative research: interviews and focus groups

This paper explores the most common methods of data collection used in qualitative research: interviews and focus groups. The paper examines each method in detail, focusing on how they work in practice, when their use is appropriate and what they can offer dentistry. Examples of empirical studies that have used interviews or focus groups are also provided.
Subtyping of Breast Cancer by Immunohistochemistry to Investigate a Relationship between Subtype and Short and Long Term Survival: A Collaborative Analysis of Data for 10,159 Cases from 12 Studies

BACKGROUND
Immunohistochemical markers are often used to classify breast cancer into subtypes that are biologically distinct and behave differently. The aim of this study was to estimate mortality for patients with the major subtypes of breast cancer as classified using five immunohistochemical markers, to investigate patterns of mortality over time, and to test for heterogeneity by subtype.


METHODS AND FINDINGS
We pooled data from more than 10,000 cases of invasive breast cancer from 12 studies that had collected information on hormone receptor status, human epidermal growth factor receptor-2 (HER2) status, and at least one basal marker (cytokeratin [CK]5/6 or epidermal growth factor receptor [EGFR]) together with survival time data. Tumours were classified as luminal and nonluminal tumours according to hormone receptor expression. These two groups were further subdivided according to expression of HER2, and finally, the luminal and nonluminal HER2-negative tumours were categorised according to expression of basal markers. Changes in mortality rates over time differed by subtype. In women with luminal HER2-negative subtypes, mortality rates were constant over time, whereas mortality rates associated with the luminal HER2-positive and nonluminal subtypes tended to peak within 5 y of diagnosis and then decline over time. In the first 5 y after diagnosis the nonluminal tumours were associated with a poorer prognosis, but over longer follow-up times the prognosis was poorer in the luminal subtypes, with the worst prognosis at 15 y being in the luminal HER2-positive tumours. Basal marker expression distinguished the HER2-negative luminal and nonluminal tumours into different subtypes. These patterns were independent of any systemic adjuvant therapy.


CONCLUSIONS
The six subtypes of breast cancer defined by expression of five markers show distinct behaviours with important differences in short term and long term prognosis. Application of these markers in the clinical setting could have the potential to improve the targeting of adjuvant chemotherapy to those most likely to benefit. The different patterns of mortality over time also suggest important biological differences between the subtypes that may result in differences in response to specific therapies, and that stratification of breast cancers by clinically relevant subtypes in clinical trials is urgently required.
Predicting walking-induced oxygen desaturations in COPD patients: a statistical model.

BACKGROUND
Oxygen desaturation during walking can have important consequence on prognosis of COPD patients. However, a standard 6-min walk test (6MWT), useful in detecting desaturation in COPD patients, can be difficult to execute in some settings of COPD management, as in the community healthcare service. We evaluated a new scoring system for the risk of oxygen desaturation during walking in COPD patients: the walking desaturation score.


METHODS
We collected data from symptomatic COPD in-patients admitted for rehabilitation (derivation cohort) and out-patients referred to the local community health service (validation cohort). S(pO2) was monitored during 6MWT, and the subjects were classified as walking desaturators or non-desaturators. By a regression analysis model we assigned a weighted score proportional to the measured percentage of explained variance for each variable. Risk estimates were computed as odds ratios. A receiver operating characteristic curve analysis and a Hosmer-Lemeshow goodness-of-fit test were then performed to measure discrimination and calibration of walking desaturation score.


RESULTS
Baseline characteristics in the derivation cohort (n = 435, 74% of whom were walking desaturators) and the validation cohort (n = 238, 37% of whom were walking desaturators) were different. Resting arterial oxygen saturation measured from an arterial blood sample, P(aO2), and percent-of-predicted FEV1 were the variables that predicted walking desaturation. The proportion of walking desaturators (and odds ratio estimate) gradually increased according to walking desaturation score (range 0-6) and associated categories of desaturation risk (total walking desaturation score: low 0 or 1, high 2-3, very high 4-6) (chi-square P < .001). There was considerable predictive discrimination (area under the curve 0.90, 95% CI 0.86-0.93, P < .001), and calibration (Hosmer-Lemeshow chi-square 1.31, P = .86) values have been shown.


CONCLUSIONS
Walking desaturation score accurately predicts and classifies the risk of walking desaturation in COPD patients. ClinicalTrials.gov Number NCT01303913.
Ontological Pathfinding : Mining First-Order Knowledge from Large Knowledge Bases

Recent years have seen a drastic rise in the construction of webscale knowledge bases (e.g., Freebase, YAGO, DBPedia). These knowledge bases store structured information about real-world people, places, organizations, etc. However, due to limitations of human knowledge and information extraction algorithms, these knowledge bases are still far from complete. In this paper, we study the problem of mining first-order inference rules to facilitate knowledge expansion. We propose the Ontological Pathfinding algorithm (OP) that scales to web-scale knowledge bases via a series of parallelization and optimization techniques: a relational knowledge base model to apply inference rules in batches, a new rule mining algorithm that parallelizes the join queries, a novel partitioning algorithm to break the mining tasks into smaller independent sub-tasks, and a pruning strategy to eliminate unsound and resource-consuming rules before applying them. Combining these techniques, we develop the first rule mining system that scales to Freebase, the largest public knowledge base with 112 million entities and 388 million facts. We mine 36,625 inference rules in 34 hours; no existing approach achieves this scale.
Final report : Dynamic Asset Allocation Using Reinforcement Learning

The role of portfolio managers is to optimize the allocation of capital across various financial assets such as stocks, bonds or funds to maximize a chosen performance metric like expected returns or risk-adjusted returns. This task is traditionally performed in two steps as described in [4]. First, it is necessary to predict the expected returns, and the covariance matrix of the returns of the assets considered. Then a quadratic programming problem can be solved to either minimize the risk of the portfolio for a constrained return or maximize its return for a given risk. Finding an optimal way of allocating assets in a portfolio in order to outperform the market is still a very active research area in finance as recently reviewed in [8]. Reinforcement learning, as a global procedure to maximize cumulative reward from a random underlying environment, fits perfectly with the problem of asset allocation [6], [5]. Hence we need to model our problem as a Markov Decision process (MDP). Finding the optimal policy from this model can then be solved using model based reinforcement learning [3] or Q-learning [9], [7].
Co-digestion of cattle manure with organic kitchen waste to increase biogas production using rumen fluid as inoculums.

Anaerobic co-digestion strategies are needed to enhance biogas production when treating certain residues such as cattle/pig manure. Co-digestion of food waste with animal manure or other feedstocks with low carbon content can improve process stability and methane production. In this study, anaerobic digestion and co-digestion of cattle manure with organic kitchen waste using rumen fluid as inoculums have been experimentally tested to determine the biogas potential. Co-digestion substantially increased the biogas yields by 24 to 47% over the control (organic kitchen waste and dairy manure only). The highest methane yield of 14,653.5 ml/g-VS was obtained with 75% organic kitchen waste (OKW) and 25% cattle manure (CM) additions. In contrast, addition of 75% cattle manure caused inhibition of the anaerobic digestion process, and its cumulative methane yield was 23% lower than that with 25% cattle manure addition.
Cost-effectiveness of an activating intervention by social workers for patients with minor mental disorders on sick leave: a randomized controlled trial.

BACKGROUND
Sickness absence often occurs in patients with emotional distress or minor mental disorders. In several European countries, these patients are over-represented among those receiving illness benefits, and interventions are needed. The aim of this study was to evaluate the cost-effectiveness of an intervention conducted by social workers, designed to reduce sick leave duration in patients absent from work owing to emotional distress or minor mental disorders.


METHODS
In this Randomized Controlled Trial, patients were recruited by GPs. The intervention group (N = 98) received an activating, structured treatment by social workers, the control group (N = 96) received routine GP care. Sick leave duration, clinical symptoms, and medical consumption (consumption of medical staffs' time as well as consumption of drugs) were measured at baseline and 3, 6, and 18 months later.


RESULTS
Neither for sick leave duration nor for clinical improvement over time were significant differences found between the groups. Also the associated costs were not significantly lower in the intervention group.


CONCLUSIONS
Compared with usual GP care, the activating social work intervention was not superior in reducing sick leave duration, improving clinical symptoms, and decreasing medical consumption. It was also not cost-effective compared with GP routine care in the treatment of minor mental disorders. Therefore, further implementation of the intervention is not justified. Potentially, programmes aimed at reducing sick leave duration in patients with minor mental disorders carried out closer to the workplace (e.g. by occupational physicians) are more successful than programmes in primary care.
The ADO index as a predictor of two-year mortality in general practice-based chronic obstructive pulmonary disease cohorts.

BACKGROUND
Existing prediction models for mortality in chronic obstructive pulmonary disease (COPD) patients have not yet been validated in primary care, which is where the majority of patients receive care.


OBJECTIVES
Our aim was to validate the ADO (age, dyspnoea, airflow obstruction) index as a predictor of 2-year mortality in 2 general practice-based COPD cohorts.


METHODS
Six hundred and forty-six patients with COPD with GOLD (Global Initiative for Chronic Obstructive Lung Disease) stages I-IV were enrolled by their general practitioners and followed for 2 years. The ADO regression equation was used to predict a 2-year risk of all-cause mortality in each patient and this risk was compared with the observed 2-year mortality. Discrimination and calibration were assessed as well as the strength of association between the 15-point ADO score and the observed 2-year all-cause mortality.


RESULTS
Fifty-two (8.1%) patients died during the 2-year follow-up period. Discrimination with the ADO index was excellent with an area under the curve of 0.78 [95% confidence interval (CI) 0.71-0.84]. Overall, the predicted and observed risks matched well and visual inspection revealed no important differences between them across 10 risk classes (p = 0.68). The odds ratio for death per point increase according to the ADO index was 1.50 (95% CI 1.31-1.71).


CONCLUSIONS
The ADO index showed excellent prediction properties in an out-of-population validation carried out in COPD patients from primary care settings.
Incidence of difficult bag-mask ventilation in children: a prospective observational study.

BACKGROUND
Difficult airway (DA), including difficult bag-mask ventilation (DBMV), and difficult intubation (DI) is an important challenge for the pediatric anesthesiologist. While expected DBMV can be successfully managed with appropriate equipment and personnel, unexpected DBMV relies on the resources available and the experience of the anesthesiologist at the time of the emergency. The incidence and risk factors of unexpected DA in otherwise healthy children, including DBMV among pediatric patients are not known. The aim of this study was to expand the scientific knowledge of unexpected DBMV among pediatric patients.


METHODS
Patients between the ages of 0 and 8 years, undergoing elective surgery requiring bag-mask ventilation BMV and intubation at the Montreal Children's Hospital were recruited in this prospective observational study. Data on the incidence of DBMV and risk factors were collected over a 3-year period.


RESULTS
In a sample of 484 children, the incidence of unexpected difficult BMV was 6.6% (95% CI [4.6, 9.2]). The incidence of expected DA among the screened patients (N = 4865) was 0.5% (95% CI [0.3, 0.7]). In a logistic regression analysis, age (OR 0.98; 95%CI [0.97, 0.99]), undergoing otolaryngology (ENT) surgery (OR 2.92; 95% CI [1.08, 7.95]) and use of neuromuscular blocking agents (OR 3.49; 95%CI [1.50-8.11]) were independently associated with DBMV. The incidence of DI was 1.2%. No association between DBMV and DI was found (Fisher's exact test, P = 1.0).


CONCLUSIONS
This is the first published report of the incidence of unexpected DBMV among healthy pediatric patients.
Input-Series and Output-Series Connected Modular Output Capacitor Full-Bridge PWM DC–DC Converter

This paper proposes a modular isolated dc-dc converter, based on the input-series and output-series association of the full-bridge PWM dc-dc converter with capacitive filter. The main attribute of the proposed architecture is its ability to provide self-balance of the input and output voltages across the individual converters, without voltage loop control scheme, both in the steady-state and transient operations. Circuit operation, theoretical analysis, and modeling are included in this paper, along with experimental results taken from a laboratory prototype with four modules, 1600-Vdc total input voltage, 1600-Vdc total output voltage, 4-kW output power, and 40-kHz switching frequency. Possible applications include high-voltage power supplies, solid-state transformers, dc current distribution systems, and renewable electric energy systems.
From Napoleon to the Second International : essays on nineteenth century Europe

Accident Prone, or What Happened Next The Historian as a Biographer Fiction in History Tory History The Thing British Pamphleteers Napoleon - On Himself, The Verdict of History Charles James Fox Talleyrand's Cut Metternich Metternich and His "System" for Europe Cobbett - Voice of the Many, The People's Champion Castlereagh Wellington - Silly Soldier Man? Sir Robert Peel - Orange Peel, The Cotton Spinner's Son Macaulay - The Man Who was Always Right, Leviathan of History Carlyle - Trevelyan's Carlyle, Carlyle Warts and All Lord John Russell - The Last Great Whig Genocide 1848 - Year of Revolution, The French Revolution, Vienna and Berlin, The Slav Congress 1848 - Opening of an Era The Last of Old Europe Crimea - The War That Would Not Boil John Bright and the Crimean War John Bright - Hero or Humbug? Ranke - The Dedicated Historian Cavour and Garibaldi Men of 1862 - Napoleon III, Francis Joseph, Emperor of Austria, Lord Palmerston, Alexander I1, Tsar of Russia, Karl Marx, Bismarck Bismarck and Europe Marx's Better Half The Paris Commune Dizzy The G 0 M Parnell - The Uncrowned King Lord Salisbury - Last Tory and First Unionist John Morley - Intellectual in Politics Keir Hardie - Labour's Moses The Second International The Vienna of Schnitzler York Manchester Edge of Britain - A Lancashire Journey - A Southport Childhood, The Boarding House Culture, Across the Morecambe Sands, Preston Revisited.
Noncausal Autoregressive Model in Application to Bitcoin/USD Exchange Rates

This paper introduces a noncausal autoregressive process with Cauchy errors in application to the exchange rates of the Bitcoin electronic currency against the US Dollar. The dynamics of the daily Bitcoin/USD exchange rate series displays episodes of local trends, which can be modelled and interpreted as speculative bubbles. The bubbles may result from the speculative component in the on-line trading. The Bitcoin/USD exchange rates are modelled and predicted. JEL number: C14 · G32 · G23
Are Licensing Agreements Appropriate Instruments to Cut Through the Patent Thicket

We study whether licensing agreements can help firms to cut through the patent thicket and to prevent hold-up problems. Using a data set covering the semiconductor industry between 1989 and 1999, descriptive results reveal a puzzling picture: while the number of patents more than doubled over the time period, the number of licensing agreements followed an inverse U-shape. This relationship is surprising given the fact that licensing agreements are supposed to resolve the hold-up problem. A more detailed analysis and the distinction between ex ante and ex post licensing contracts give the following results: the degree to which firms block each other in the technology space explains firms’ licensing choices. Ex ante licensing agreements represent useful instruments for firms to avoid getting into patent races if the degree of blocking is expected to be high. The type of contracts also allows firms to avoid high investments in Research and Development. Ex post licensing agreements are more important for firm pairs which mistakenly expect blocking to matter little, and which are characterized by larger and more similar market shares. Worryingly, our empirical results show that firms’ tendency to engage in licensing deals decreases as property rights become more fragmented. Moreover, ex ante licensing agreements are characterized by significant transaction and contracting costs which diminish with experience. JEL: L13, L49, L63.
Emergence of virtual reality as a tool for upper limb rehabilitation: incorporation of motor control and motor learning principles.

The primary focus of rehabilitation for individuals with loss of upper limb movement as a result of acquired brain injury is the relearning of specific motor skills and daily tasks. This relearning is essential because the loss of upper limb movement often results in a reduced quality of life. Although rehabilitation strives to take advantage of neuroplastic processes during recovery, results of traditional approaches to upper limb rehabilitation have not entirely met this goal. In contrast, enriched training tasks, simulated with a wide range of low- to high-end virtual reality-based simulations, can be used to provide meaningful, repetitive practice together with salient feedback, thereby maximizing neuroplastic processes via motor learning and motor recovery. Such enriched virtual environments have the potential to optimize motor learning by manipulating practice conditions that explicitly engage motivational, cognitive, motor control, and sensory feedback-based learning mechanisms. The objectives of this article are to review motor control and motor learning principles, to discuss how they can be exploited by virtual reality training environments, and to provide evidence concerning current applications for upper limb motor recovery. The limitations of the current technologies with respect to their effectiveness and transfer of learning to daily life tasks also are discussed.