LLukas22/scidocs huggingface dataset:
Development of an Economic Model to Assess the Cost Effectiveness of Asthma Management Strategies

Background and objective: Asthma is a chronic-episodic disease characterised by acute, symptomatic episodes of varying severity. We developed a Markov model that can be used to estimate the cost effectiveness of alternative asthma treatments. Because of the costs they incur, asthma exacerbations (‘attacks’) requiring intervention by a healthcare professional were a central consideration in the development of the model. Methods: Treatment success was assessed as asthma control, a composite measure based on goals defined in world-wide asthma management guidelines and in terms of quality-adjusted life-years (QALYs). The data from which the transition probabilities were derived came from patients with asthma who received either salmeterol/fluticasone propionate combination (SFC) 50/100μg or fluticasone propionate (FP) 100μg, administered twice daily via an inhaler, in a 12-week, randomised, double-blind, clinical trial. Costs were estimated from resource profiles defined for each of the model states. A key aspect of the model was the use of probabilistic sensitivity analysis techniques to examine the uncertainty in the cost-effectiveness results. Distributions were fitted to transition probabilities and to cost input parameters and values were sampled at random from these distributions using a second order Monte Carlo simulation technique. This produced a distribution for incremental cost effectiveness that was employed to construct 95% uncertainty intervals and to construct cost effectiveness acceptability curves. Results: In this analysis, the model was run over a 12-week period using transition probabilities derived from the trial data. The results showed that treatment with SFC resulted in a higher proportion of successfully controlled weeks per patient than treatment with FP(66 vs 47%), and higher mean weekly direct asthma management costs (£15.77 vs £11.83; 2000 values). The average incremental cost per successfully controlled week with SFC was £20.83. Probabilistic sensitivity analysis showed that the 95% uncertainty intervals for the incremental cost-effectiveness ratio was −£64.94 to £112.66. In approximately 25% of cases, SFC was dominant (more effective and less costly), but in the remaining cases, it was both more effective and more costly. It was shown that if decision makers are willing to pay approximately £45 for an additional successfully controlled week, SFC will be the more cost-effective strategy in this patient population for 80% of the time. Conclusions: This is one of the first decision-analytic models of asthma to incorporate probabilistic sensitivity analysis techniques to explore uncertainty. The model’s flexible yet standardised framework permits the cost effectiveness of alternative asthma management strategies in different healthcare settings to be established.
An internet-based physical activity intervention for adolescents with cerebral palsy: a randomized controlled trial.

AIM
To determine the effectiveness of an 8-week internet-based, lifestyle physical-activity intervention for adolescents with cerebral palsy (CP).


METHOD
A randomized controlled trial using concealed allocation with blinded assessments at baseline, 10, and 20 weeks. Forty-one adolescents with CP participated (26 males, 15 females; mean age 13y 7mo, SD 1y 8mo, range 11-17y; Gross Motor Function Classification System levels: I, n=21; II, n=17; III, n=3; unilateral distribution n=16, bilateral n=25). Primary outcome was physical activity (NL-1000 accelerometers and self-report [Multimedia Activity Recall for Children and Adolescents: MARCA]). Secondary outcomes were exercise knowledge (a purpose-designed scale), attitudes, intention and self-efficacy (Lifestyle Education for Activity Program II scales), self-reported sedentary behaviour (MARCA), and functional capacity (6-min walk test).


RESULTS
At 10 weeks the intervention group showed no increased physical activity compared with the comparison group (weekly steps: change of +2420 vs -12189 steps p=0.06; weekly moderate-to-vigorous physical activity: change of +70 vs +8min, p=0.06; weekly distance walked: change of +3 vs -9.1km, p=0.05) and exercise knowledge (12% vs 1% improvement, p=0.08). There were no statistically significant differences for these outcomes at 20 weeks, or in self-reported physical activity at 10 or 20 weeks.


INTERPRETATION
There was a positive short-term pattern for improvement in physical activity and knowledge. Internet-based programs may offer an alternative for participants unable to attend regular face-to-face physical activity programs.
Clustering Time Series Data Stream - A Literature Survey

Mining Time Series data has a tremendous growth of interest in today’s world. To provide an indication various implementations are studied and summarized to identify the different problems in existing applications. Clustering time series is a trouble that has applications in an extensive assortment of fields and has recently attracted a large amount of research. Time series data are frequently large and may contain outliers. In addition, time series are a special type of data set where elements have a temporal ordering. Therefore clustering of such data stream is an important issue in the data mining process. Numerous techniques and clustering algorithms have been proposed earlier to assist clustering of time series data streams. The clustering algorithms and its effectiveness on various applications are compared to develop a new method to solve the existing problem. This paper presents a survey on various clustering algorithms available for time series datasets. Moreover, the distinctiveness and restriction of previous research are discussed and several achievable topics for future study are recognized. Furthermore the areas that utilize time series clustering are also summarized. KeywordsData Mining, Data Streams, Clustering, Time Series, Machine Learning, Unsupervised Learning, Feature Extraction and Feature Selection.
e-Manufacturing System for Next-generation Semiconductor Production

OVERVIEW: Next-generation semiconductor factories need to support miniaturization below 100 nm and have higher production efficiency, mainly of 300-mm-diameter wafers. Particularly to reduce the price of semiconductor devices, shorten development time [thereby reducing the TAT (turn-around time)], and support frequent product changeovers, semiconductor manufacturers must enhance the productivity of their systems. To meet these requirements, Hitachi proposes solutions that will support e-manufacturing on the next-generation semiconductor production line (see Fig. 1). Yasutsugu Usami Isao Kawata Hideyuki Yamamoto Hiroyoshi Mori Motoya Taniguchi, Dr. Eng.
A 25-to-28 Gb/s High-Sensitivity ( $-$9.7 dBm) 65 nm CMOS Optical Receiver for Board-to-Board Interconnects

To address the two main challenges concerning the design of a transimpedance amplifier (TIA), namely, improving the sensitivity of the TIA without sacrificing bandwidth and suppressing inter-symbol interference (ISI) due to insertion loss, a 25 Gb/s optical receiver (RX) based on 65 nm CMOS technology, including a TIA and a PD operating at 1.3 μm wavelength, was developed. The key components of the TIA are a two-stage offset-cancelation scheme and a low-voltage output driver with peaking gain of 7.7 dB at 12.5 GHz. This driver performance is achieved by separating the equalizer function and output buffer of the driver. The TIA attains a sensitivity of -9.7 dBm (86- μApp) OMA and an eye opening of 65% at data rate of 25 Gb/s. The optical RX operates at 28 Gb/s with sensitivity of -8.2 dBm (121- μApp) OMA. Utilizing the CMOS TIA, an implemented VCSEL-based optical link operating at 850 nm wavelength achieves sensitivity of -7.3 dBm (98- μApp) OMA. Power consumption and power efficiency of the optical RX at data rate of 28 Gb/s are respectively 137.5 mW and 4.9 mW/Gb/s.
Efficient Chosen Ciphertext Secure Public Key Encryption under the Computational Diffie-Hellman Assumption

Recently Cash, Kiltz, and Shoup [20] showed a variant of the Cramer-Shoup (CS) public key encryption (PKE) scheme [21] whose chosen-ciphertext (CCA) security relies on the computational Diffie-Hellman (CDH) assumption. The cost for this high security is that the size of ciphertexts is much longer than the CS scheme. In this paper, we show how to achieve CCAsecurity under the CDH assumption without increasing the size of ciphertexts. We further show a more efficient scheme under the hashed Diffie-Hellman (HDH) assumption such that the size of ciphertexts is the same as that of the Kurosawa-Desmedt (KD) scheme [42]. Note that the CDH and HDH assumptions are weaker than the decisional Diffie-Hellman assumption which the CS and KD schemes rely on. Both of our schemes are based on a certain broadcast encryption (BE) scheme while the Cash-Kiltz-Shoup scheme is based on a different paradigm which is called the Twin DH problem. As an independent interest, we also show a generic method of constructing CCA-secure PKE schemes from BE schemes such that the existing CCA-secure constructions can be viewed as special cases.
Content-Aware Collaborative Music Recommendation Using Pre-trained Neural Networks

Although content is fundamental to our music listening preferences, the leading performance in music recommendation is achieved by collaborative-filtering-based methods which exploit the similarity patterns in user’s listening history rather than the audio content of songs. Meanwhile, collaborative filtering has the well-known “cold-start” problem, i.e., it is unable to work with new songs that no one has listened to. Efforts on incorporating content information into collaborative filtering methods have shown success in many non-musical applications, such as scientific article recommendation. Inspired by the related work, we train a neural network on semantic tagging information as a content model and use it as a prior in a collaborative filtering model. Such a system still allows the user listening data to “speak for itself”. The proposed system is evaluated on the Million Song Dataset and shows comparably better result than the collaborative filtering approaches, in addition to the favorable performance in the cold-start case.
*Smarter Task Assignment or Greater Effort: The Impact of Incentives on Team Performance

We use an experiment to study the impact of team-based incentives, exploiting rich data from personnel records and management information systems. Using a triple difference design, we show that the incentive scheme had an impact on team performance, even with quite large teams. We examine whether this effect was due to increased effort from workers or strategic task reallocation. We find that the provision of financial incentives did raise individual performance but that managers also disproportionately reallocated efficient workers to the incentivised tasks. We show that this reallocation was the more important contributor to the overall outcome.
[What is your diagnosis? Mid-dermal elastolysis].

a Cabinet de dermatologie, Le Clos Sévigné, 9, avenue du Général-de-Gaulle, 13410 Lambesc, France b Laboratoire d’anatomopathologie, CHU La-Timone, Assistance publique—Hôpitaux de Marseille, université de la Méditerranée Aix-Marseille II, 264, rue Saint-Pierre, 13005 Marseille cedex 05, France c Service de dermatologie, CHU La-Timone, Assistance publique—Hôpitaux de Marseille, université de la Méditerranée Aix-Marseille II, 264, rue Saint-Pierre, 13005 Marseille cedex 05, France
Formalism in Ethics and Non-Formal Ethics of Values

A lengthy critique of Kant's apriorism precedes discussions on the ethical principles of eudaemonism, utilitarianism, pragmatism, and positivism.
A Machine Learning Approach for Assessment and Prediction of Teamwork Effectiveness in Software Engineering Education

One of the challenges in effective software engineering (SE) education is the lack of objective assessment methods of how well student teams learn the critically needed teamwork practices, defined as the ability: (i) to learn and effectively apply SE processes in a teamwork setting, and (ii) to work as a team to develop satisfactory software (SW) products. In addition, there are no effective methods for predicting learning effectiveness in order to enable early intervention in the classroom. Most of the current approaches to assess achievement of SE teamwork skills rely solely on qualitative and subjective data taken as surveys at the end of the class and analyzed only with very rudimentary data analysis. In this paper we present a novel approach to address the assessment and prediction of student learning of teamwork effectiveness in software engineering education based on: a) extracting only objective and quantitative student team activity data during their team class project; b) pairing these data with related independent observations and grading of student team effectiveness in SE process and SE product components in order to create “training database”; and c) applying a machine learning (ML) approach, namely random forest classification (RF), to the above training database in order to create ML models, ranked factors and rules that can both explain (e.g. assess) as well as provide prediction of the student teamwork effectiveness. These student team activity data are being collected in joint and already established (since 2006) SE classes at San Francisco State University (SFSU), Florida Atlantic University (FAU) and Fulda University, Germany (Fulda), from approximately 80 students each year, working in about 15 teams, both local and global (with students from multiple schools). Keywords-assessment; software engineering teamwork; software engineering education; assessment; machine learning.
Differences in Attitude towards Cadaveric Organ Donation: Observations in a Multiracial Malaysian Society

Background: Willingness to donate organs is affected by socio-cultural and religious values. The Malaysian society is made up of three ethnic groups: Malay, Chinese, and Indian, with Islam, Buddhism and Hinduism as their religions respectively. This study examined the knowledge and perception towards organ donation for each group. Methods: This study was conducted at University Malaya Medical Centre, Kuala Lumpur, Malaysia. Relatives of patients awaiting treatment at the emergency department answered a questionnaire on knowledge and attitude on organ transplantation. Results: A total of 904 questionnaires were completed; 90.6% would accept organs, 43.6% would donate, and 4.0% carried donor cards. The reasons for reluctance to donate included: fear of organs being used for research (18.8%), desire to be buried whole (18.0%), fear of less active treatment if patient is known to be a donor (12.8%). Malays were less willing to accept organs from a different race (63.5%) compared to Chinese (83.3%) and Indians (83.8%) (OR=0.35, 95%CI: 0.23-0.54 and OR=0.34, 95%CI: 0.22-0.51 respectively) and also less likely to donate organs (29.8%) as compared to Chinese (42.1%) and Indians (63.2%) (OR=0.57, 95%CI 0.40-0.83 and OR=0.24, 95%CI 0.17-0.35 respectively). Malays were less willing to donate organs to another race compared to Chinese or Indians (OR=0.48, 95%CI 0.33-0.70 and OR=0.22, 95%CI 0.15-0.31 respectively). Only 34.7% of Muslims are aware of fatwa supporting organ donation. Conclusions: The awareness of organ donation was low. Clear differences exist among ethnic groups. Cultural-religious attitudes and lack of trust in the medical systems were reasons for reluctance to donation. Identifying socio-cultural barriers and reassuring donors regarding medical care are required. (Hong Kong j.emerg.med. 2010;17:236-243)
A heterogeneous computing environment to solve the 768-bit RSA challenge

In December 2009 the 768-bit, 232-digit number RSA-768 was factored using the number field sieve. Overall, the computational challenge would take more than 1700 years on a single, standard core. In the article we present the heterogeneous computing approach, involving different compute clusters and Grid computing environments, used to solve this problem.
Variability of respiratory symptoms in severe COPD.

INTRODUCTION
While it is known that asthma symptoms have a very variable pattern, the general belief is that the respiratory symptoms in COPD patients usually present little or no variability. Nevertheless, COPD patients report having "bad days". The objective of this present study was to evaluate the variability of the respiratory symptoms and their impact on the daily activities of a cohort of Spanish COPD patients.


METHOD
We present the results of the Spanish patients who participated in a cross-sectional epidemiological study carried out in 17 European countries. Pulmonologists and Family Care physicians recruited patients with stable severe COPD (FEV1<50%). The perception of the patients on the variation in their symptoms was recorded by telephone interviews.


RESULTS
A total of 472 patients provided data that was valid for analysis. Mean age was 68.6; 93% were men; mean FEV1(%) was 41%. 84.1% of the patients experimented at least one respiratory symptom in the previous week and 60.9% affirmed that their symptoms varied over the course of the day or week. The moment of the day when the symptoms were perceived to be more intense was during the morning.


CONCLUSIONS
An important proportion of severe COPD patients perceive variability in their respiratory symptoms, with a greater intensity in the morning. The observation can have implications in treating patients with severe COPD as variability can be an initial sign of decompensation of the disease.
Exploring variation in pressure ulcer prevalence in Sweden and the USA: benchmarking in action.

AIM
To compare overall unit-level pressure ulcer (PU) prevalence, hospital-acquired pressure ulcer (HAPU) prevalence and prevention strategies, as well as nurse staffing and workload in two hospitals in Sweden with data from the USA.


METHODS
Medical and surgical units in a university hospital and a general hospital in Sweden were compared with 207 hospitals in the USA participating in the Collaborative Alliance for Nursing Outcomes (CALNOC) benchmarking registry. All adult inpatients in university hospital (n = 630), general hospital (n = 253) and CALNOC hospitals (n = 3506) were included in the study. Outcome indicators were pressure ulcer prevalence for all types (PU) and HAPU prevalence, specifically. Process indicators were risk assessment and PU prevention strategies. Structure indicators were nurse staffing (hours of care, and skill mix) and workload (admissions, discharges and transfers).


RESULTS
The prevalence of PU (categories 1-4) was 17.6% (university hospital) and 9.5% (general hospital) compared with 6.3-6.7% in the CALNOC sample. The prevalence of full thickness HAPU (categories 3 and 4) was 2.7% (university hospital) and 2.0% (general hospital) compared with 0-0.5% in the CALNOC sample. Risk and skin assessment varied between 6% and 60% in the Swedish hospitals compared with 100% in the CALNOC sample. Total hours per patient day were 8.4 in both Swedish hospitals and 9.5 to 9.8 in the CALNOC hospitals


CONCLUSIONS
The findings suggest a link between processes of care and outcomes that is exciting to observe internationally and suggest the opportunity to expedite performance improvement through global benchmarking. Using HAPU as a complement to point prevalence of PU in Sweden has revealed this indicator as a more valid measure for patient care quality.
Clinical and radiographic outcomes at 2 years and the effect of tocilizumab discontinuation following sustained remission in the second and third year of the ACT-RAY study

OBJECTIVE
To assess the efficacy and safety of tocilizumab (TCZ) plus methotrexate/placebo (MTX/PBO) over 2 years and the course of disease activity in patients who discontinued TCZ due to sustained remission.


METHODS
ACT-RAY was a double-blind 3-year trial. Patients with active rheumatoid arthritis despite MTX were randomised to add TCZ to ongoing MTX (add-on strategy) or switch to TCZ plus PBO (switch strategy). Using a treat-to-target approach, open-label conventional synthetic disease-modifying antirheumatic drugs (csDMARDs), other than MTX, were added from week 24 if Disease Activity Score in 28 joints based on erythrocyte sedimentation rate (DAS28-ESR) >3.2. Between weeks 52 and 104, patients in sustained clinical remission (DAS28-ESR <2.6 at two consecutive visits 12 weeks apart) discontinued TCZ and were assessed every 4 weeks for 1 year. If sustained remission was maintained, added csDMARDs, then MTX/PBO, were discontinued.


RESULTS
Of the 556 randomised patients, 76% completed year 2. Of patients entering year 2, 50.4% discontinued TCZ after achieving sustained remission and 5.9% achieved drug-free remission. Most patients who discontinued TCZ (84.0%) had a subsequent flare, but responded well to TCZ reintroduction. Despite many patients temporarily stopping TCZ, radiographic progression was minimal, with differences favouring add-on treatment. Rates of serious adverse events and serious infections per 100 patient-years were 12.2 and 4.4 in add-on and 15.0 and 3.7 in switch patients. In patients with normal baseline values, alanine aminotransferase elevations >3×upper limit of normal were more frequent in add-on (14.3%) versus switch patients (5.4%).


CONCLUSIONS
Treat-to-target strategies could be successfully implemented with TCZ to achieve sustained remission, after which TCZ was stopped. Biologic-free remission was maintained for about 3 months, but most patients eventually flared. TCZ restart led to rapid improvement.


TRIAL REGISTRATION NUMBER
NCT00810199.
Report on non-temperature related variations in CO2 efflux rates from young tree stems in the dormant season

Respiration rates are reported to increase exponentially with temperature. Respiration rates of woody tissues are commonly measured as CO2 efflux rates ( $$F_{{\rm CO}_{\rm 2}}$$ ) from that tissue. However, this paper describes clear variations in stem $$F_{{\rm CO}_{\rm 2}}$$ that were not related to temperature for the case of a young beech (Fagus sylvatica L.) and oak (Quercus robur L.) tree during the dormant season. The CO2 concentration ([CO2]) in the xylem of the beech tree showed similar temperature-independent variations. The trees were grown in a growth chamber in which radiation patterns and temperature were kept constant. $$F_{{\rm CO}_{\rm 2}}$$ was measured with an IRGA connected to cuvettes surrounding a stem segment. Xylem [CO2] was measured in situ using a CO2 microelectrode. Depressions in $$F_{{\rm CO}_{\rm 2}}$$ and [CO2] occurred during the light period, despite equal temperatures in the light and dark period. Explanations found in literature for discrepancies in the exponential relationship between temperature and $$F_{{\rm CO}_{\rm 2}}$$ are the influence of (1) sap flow or (2) decreased cell water content. However, (1) the variations were observed in the dormant season, when no sap flow was observed yet, and (2) reduced cell water content was not likely to be apparent as differences in stem transpiration rates between the dark and light period were not significant. Hence, previously formulated theories failed to explain our results. This work therefore provides a new ground for discussion on other possible causes of daytime depressions in $$F_{{\rm CO}_{\rm 2}}$$ . One might be the refixation of respired CO2 by corticular photosynthesis in the stem parts adjacent to the stem segment enclosed by the cuvette.