LLukas22/scidocs huggingface dataset:
Customising agile methods to software practices at Intel Shannon

Received: 18 May 2005 Revised: 19 June 2005 Accepted: 9 January 2006 Abstract Tailoring of methods is commonplace in the vast majority of software development projects and organisations. However, there is not much known about the tailoring and engineering of agile methods, or about how these methods can be used to complement each other. This study investigated tailoring of the agile methods, eXtreme programming (XP) and Scrum, at Intel Shannon, and involved experienced software engineers who continuously monitored and reflected on these methods over a 3-year period. The study shows that agile methods may individually be incomplete in supporting the overall development process, but XP and Scrum complement each other well, with XP providing support for technical aspects and Scrum providing support for project planning and tracking. The principles of XP and Scrum were carefully selected (only six of the 12 XP key practices were implemented, for example) and tailored to suit the needs of the development environment at Intel Shannon. Thus, the study refutes the suggestion that agile methods are not divisible or individually selectable but achieve their benefits through the synergistic combination of individual agile practices; rather, this study shows that an a la carte selection and tailoring of practices can work very well. In the case of Scrum, some local tailoring has led to a very committed usage by developers, in contrast to many development methods whose usage is limited despite being decreed mandatory by management. The agile practices that were applied did lead to significant benefits, including reductions in code defect density by a factor of 7. Projects of 6-month and 1-year duration have been delivered ahead of schedule, which bodes well for future ability to accurately plan development projects. European Journal of Information Systems (2006) 15, 197–210. doi:10.1057/palgrave.ejis.3000605
Maternal gestational diabetes, birth weight, and adolescent obesity.

OBJECTIVE
Obesity increases risk of many adverse outcomes, but its early origins are obscure. Gestational diabetes mellitus (GDM) reflects a metabolically altered fetal environment associated with high birth weight, itself associated with later obesity. Previous studies of GDM and offspring obesity, however, have been few and conflicting. The objectives of this study were to examine associations of birth weight and GDM with adolescent body mass index (BMI) and to determine the extent to which the effect of GDM is explained by its influence on birth weight or by maternal adiposity.


METHODS
We conducted a survey of 7981 girls and 6900 boys, 9 to 14 years of age, who are participants in the Growing Up Today Study, a US nationwide study of diet, activity, and growth. In 1996, participants reported height, weight, diet, activity, and other variables by self-administered mailed questionnaire. We linked these data with information reported by their mothers, participants in the Nurses' Health Study II, including GDM, height, current weight, and child's birth weight. We excluded births <34 weeks' gestation and mothers who had preexisting diabetes. We defined overweight as BMI (kg/m(2)) >95th percentile, and at risk for overweight as 85th to 95th percentile, for age and gender from US national data.


RESULTS
Mean birth weight was 3.4 kg for girls and 3.6 kg for boys. Among the 465 subjects whose mothers had GDM, 17.1% were at risk for overweight and 9.7% were overweight in early adolescence. In the group without maternal diabetes, these estimates were 14.2% and 6.6%, respectively. In multiple logistic regression analysis, controlling for age, gender, and Tanner stage, the odds ratio for adolescent overweight for each 1-kg increment in birth weight was 1.4 (95% confidence interval: 1.2-1.6). Adjustment for physical activity, television watching, energy intake, breastfeeding duration, mother's BMI, and other maternal and family variables reduced the estimate to 1.3 (1.1-1.5). For offspring of mothers with GDM versus no diabetes, the odds ratio for adolescent overweight was 1.4 (1.1-2.0), which was unchanged after controlling for energy balance and socioeconomic factors. Adjustment for birth weight slightly attenuated the estimate (1.3; 0.9-1.9); adjustment for maternal BMI reduced the odds ratio to 1.2 (0.8-1.7).


CONCLUSIONS
Higher birth weight predicted increased risk of overweight in adolescence. Having been born to a mother with GDM was also associated with increased adolescent overweight. However, the effect of GDM on offspring obesity seemed only partially explained by its influence on birth weight, and adjustment for mother's own BMI attenuated the GDM associations. Our results only modestly support a causal role of altered maternal-fetal glucose metabolism in the genesis of obesity in the offspring. Alternatively, GDM may program risk for a postnatal insult leading to obesity, or it may merely be a risk marker, not in the causal pathway.
Quality of care for primary care patients with depression in managed care.

OBJECTIVE
To evaluate the process and quality of care for primary care patients with depression under managed care organizations.


METHOD
Surveys of 1204 outpatients with depression at the time of and after a visit to 1 of 181 primary care clinicians from 46 primary care clinics in 7 managed care organizations. Patients had depressive symptoms in the previous 30 days, with or without a 12-month depressive disorder by diagnostic interview. Process indicators were depression counseling, mental health referral, or psychotropic medication management at index visit and the use of appropriate antidepressant medication during the last 6 months.


RESULTS
Of patients with depressive disorder and recent symptoms, 29% to 43% reported a depression-specific process of care in the index visit, and 35% to 42% used antidepressant medication in appropriate dosages in the prior 6 months. Patients with depressive disorders rather than symptoms only and those with comorbid anxiety had higher rates of depression-specific processes and quality of care (P < .005). Recurrent depression, suicidal ideation, and alcohol abuse were not uniquely associated with such rates. Patients visiting for old problems or checkups received more depression-specific care than those with new problems or unscheduled visits. The 7 managed care organizations varied by a factor of 2-fold in rates of depression counseling and appropriate anti-depressant use.


CONCLUSIONS
Rates of process and quality of care for depression as reported by patients are moderate to low in managed primary care practices. Such rates are higher for patients with more severe forms of depression or with comorbid anxiety, but not for those with severe but "silent" symptoms like suicide ideation. Visit context factors, such as whether the visit is scheduled, affect rates of depression-specific care. Rates of care for depression are highly variable among managed care organizations, emphasizing the need for process monitoring and quality improvement for depression at the organizational level.
Clinical features of the initial cases of 2009 pandemic influenza A (H1N1) virus infection in an university hospital of Morocco

BACKGROUND
The first case of 2009 pandemic influenza A (H1N1) virus infection in our center was documented on June 15. Subsequently, persons with suspected cases of infection and contacts of those with suspected infection were tested. Persons in whom infection was confirmed were hospitalized and quarantined, and some of them were closely observed for the purpose of investigating the nature and duration of the disease. The aim of the present study was to describe baseline characteristics, treatment, outcomes, hospital length of stay and mortality of the first 186 cases of influenza A (H1N1) virus infection, with special interest in those developing severe respiratory failure with intensive care unit (ICU) care requirement.


METHODS
observational study of 186 consecutive cases of influenza A (H1N1) virus infection admitted in 3 departments that were reference centers for the care of patients with influenza A and 4 ICU in Ibn Sina university hospital (Rabat, Morocco) between June and December 2009. Real time reverse-transcriptase-polymerase-chain-reaction (RT-PCR) testing was used to confirm infection. Demographic data, symptoms, comorbid conditions, illness progression, laboratory and chest radiologic findings, treatments, clinical outcomes and ICU care requirement were closely monitored.


RESULTS
The mean age of the 186 patients was 17.6 ± 14.8 years, 47.8% had less than 14 years and 57% were male. The median duration of symptoms before hospital admission was 3 days (interquartile range (IQR): 2-5). The most common symptoms were fever (in 91.5% of the patients), cough in 92.5%, and nasal congestion in 62.4%. Twenty four percent of patients had comorbid respiratory disorders and 7.5% were pregnant. Abnormalities in chest radiography were detected in 26.3% of 186 patients on admission or after hospitalization. Twenty patients have required ICU care and 10 have required mechanical ventilation. The hospital length of stay was 5 days (IQR: 4-5). The following were risk factors of ICU admission: older age (p = 0.03), long duration of symptoms (p = 0.07), asthma (p = 0.01), obesity (P < 0.001), abnormalities of chest radiography (P < 0.001), leukocytosis (p = 0.005), and higher C-reactive protein (CRP) (P < 0.001). The ICU length of stay was 4 days (IQR: 3-6.7). The mortality rate was 3.5% among all patients and 30% among ICU patients.


CONCLUSIONS
Close observation of patients infected with the 2009 pandemic influenza A (H1N1) virus infection provided us with several information. The influenza A (H1N1) virus infection affected young people particularly, with comorbid respiratory disorders. Risk factors of ICU admission were older age, long duration of symptoms, asthma, obesity, abnormalities of chest radiography, leukocytosis and higher CRP. Clinicians should be aware of complications of influenza A (H1N1) virus infection, particulary in patients with risk factors.
Convolutional Gaussian Processes

We present a practical way of introducing convolutional structure into Gaussian processes, making them more suited to high-dimensional inputs like images. The main contribution of our work is the construction of an inter-domain inducing point approximation that is well-tailored to the convolutional kernel. This allows us to gain the generalisation benefit of a convolutional kernel, together with fast but accurate posterior inference. We investigate several variations of the convolutional kernel, and apply it to MNIST and CIFAR-10, where we obtain significant improvements over existing Gaussian process models. We also show how the marginal likelihood can be used to find an optimal weighting between convolutional and RBF kernels to further improve performance. This illustration of the usefulness of the marginal likelihood may help automate discovering architectures in larger models.
Reduced risk of relapse after long-term nucleos(t)ide analogue consolidation therapy for chronic hepatitis B.

BACKGROUND
Before stopping nucleos(t)ide analogue (NA) treatment in chronic hepatitis B (CHB), 6-12 months of consolidation therapy is recommended.


AIM
To investigate the effect of consolidation therapy on off-treatment outcomes in CHB patients.


METHODS
We included 94 patients who stopped NA after at least 1 year of therapy. Patients could be HBeAg-positive or HBeAg-negative at start-of-treatment, but were HBeAg-negative and had undetectable HBV DNA at time of discontinuation. Consolidation therapy was defined as treatment after the first undetectable HBV DNA (and HBeAg loss for HBeAg-positive patients) until NA cessation.


RESULTS
At 3 years, 74% of the start-of-treatment HBeAg-positive and 75% of the start-of-treatment HBeAg-negative patients developed HBV DNA >2000 IU/mL at a single time point, whereas a persistent virological relapse (≥2 tests of HBV DNA >2000 IU/mL 6 months apart within 1 year) developed in 49% of the start-of-treatment HBeAg-positive and 53% of the start-of-treatment HBeAg-negative patients. For both HBeAg-positive and HBeAg-negative patients, consolidation therapy of ≥3 years was associated with lower persistent virological relapse rates compared to <1 year (1-year relapse rate: 25% vs. 54%; P = 0.063 and 24% vs. 57%; P = 0.036, respectively). At 3 years, 9% of the HBeAg-positive and 14% of the HBeAg-negative patients became HBsAg-negative. Prolonged consolidation therapy increased the likelihood of HBsAg loss. Two cirrhotic patients developed hepatic decompensation but both recovered.


CONCLUSIONS
After nucleos(t)ide analogue discontinuation, relapse was common in patients with chronic hepatitis B. Prolongation of consolidation therapy beyond 3 years decreased the risk of persistent virological relapse and increased the likelihood of HBsAg loss.
Mental health care in Nepal: current situation and challenges for development of a district mental health care plan

BACKGROUND
Globally mental health problems are a serious public health concern. Currently four out of five people with severe mental illness in Low and Middle Income Countries (LMIC) receive no effective treatment. There is an urgent need to address this enormous treatment gap. Changing the focus of specialist mental health workers (psychiatrists and psychologists) from only service delivery to also designing and managing mental health services; building clinical capacity of the primary health care (PHC) workers, and providing supervision and quality assurance of mental health services may help in scaling up mental health services in LMICs. Little is known however, about the mental health policy and services context for these strategies in fragile-state settings, such as Nepal.


METHOD
A standard situation analysis tool was developed by the PRogramme for Improving Mental health carE (PRIME) consortium to systematically analyze and describe the current gaps in mental health care in Nepal, in order to inform the development of a district level mental health care plan (MHCP). It comprised six sections; general information (e.g. population, socio-economic conditions); mental health policies and plans; mental health treatment coverage; district health services; and community services. Data was obtained from secondary sources, including scientific publications, reports, project documents and hospital records.


RESULTS
Mental health policy exists in Nepal, having been adopted in 1997, but implementation of the policy framework has yet to begin. In common with other LMICs, the budget allocated for mental health is minimal. Mental health services are concentrated in the big cities, with 0.22 psychiatrists and 0.06 psychologists per 100,000 population. The key challenges experienced in developing a district level MHCP included, overburdened health workers, lack of psychotropic medicines in the PHC, lack of mental health supervision in the existing system, and lack of a coordinating body in the Ministry of Health and Population (MoHP). Strategies to overcome these challenges included involvement of MoHP in the process, especially by providing psychotropic medicines and appointing a senior level officer to facilitate project activities, and collaboration with National Health Training Centers (NHTC) in training programs.


CONCLUSIONS
This study describes many challenges facing mental health care in Nepal. Most of these challenges are not new, yet this study contributes to our understanding of these difficulties by outlining the national and district level factors that have a direct influence on the development of a district level mental health care plan.
MR-based synthetic CT generation using a deep convolutional neural network method.

PURPOSE
Interests have been rapidly growing in the field of radiotherapy to replace CT with magnetic resonance imaging (MRI), due to superior soft tissue contrast offered by MRI and the desire to reduce unnecessary radiation dose. MR-only radiotherapy also simplifies clinical workflow and avoids uncertainties in aligning MR with CT. Methods, however, are needed to derive CT-equivalent representations, often known as synthetic CT (sCT), from patient MR images for dose calculation and DRR-based patient positioning. Synthetic CT estimation is also important for PET attenuation correction in hybrid PET-MR systems. We propose in this work a novel deep convolutional neural network (DCNN) method for sCT generation and evaluate its performance on a set of brain tumor patient images.


METHODS
The proposed method builds upon recent developments of deep learning and convolutional neural networks in the computer vision literature. The proposed DCNN model has 27 convolutional layers interleaved with pooling and unpooling layers and 35 million free parameters, which can be trained to learn a direct end-to-end mapping from MR images to their corresponding CTs. Training such a large model on our limited data is made possible through the principle of transfer learning and by initializing model weights from a pretrained model. Eighteen brain tumor patients with both CT and T1-weighted MR images are used as experimental data and a sixfold cross-validation study is performed. Each sCT generated is compared against the real CT image of the same patient on a voxel-by-voxel basis. Comparison is also made with respect to an atlas-based approach that involves deformable atlas registration and patch-based atlas fusion.


RESULTS
The proposed DCNN method produced a mean absolute error (MAE) below 85 HU for 13 of the 18 test subjects. The overall average MAE was 84.8 ± 17.3 HU for all subjects, which was found to be significantly better than the average MAE of 94.5 ± 17.8 HU for the atlas-based method. The DCNN method also provided significantly better accuracy when being evaluated using two other metrics: the mean squared error (188.6 ± 33.7 versus 198.3 ± 33.0) and the Pearson correlation coefficient(0.906 ± 0.03 versus 0.896 ± 0.03). Although training a DCNN model can be slow, training only need be done once. Applying a trained model to generate a complete sCT volume for each new patient MR image only took 9 s, which was much faster than the atlas-based approach.


CONCLUSIONS
A DCNN model method was developed, and shown to be able to produce highly accurate sCT estimations from conventional, single-sequence MR images in near real time. Quantitative results also showed that the proposed method competed favorably with an atlas-based method, in terms of both accuracy and computation speed at test time. Further validation on dose computation accuracy and on a larger patient cohort is warranted. Extensions of the method are also possible to further improve accuracy or to handle multi-sequence MR images.
Determination of Protein Concentration Using Bradford Microplate Protein Quantification Assay

Background: Bradford protein assay is popular due to its ease of performance and relative sensitivity. Many researchers and laboratories in Iran use standard assay of Bradford by cuvette. No commercial kit was available for Bradford microplate assay in Iran. Meanwhile, imported Bradford commercial kits are very expensive and have a long delivery time in Iran. Till now no study or document on Bradford microplate protein quantification assay was reported in Iran, so this study aimed to design and carried out this assay. Methods: In the current study, antigen B of hydatid cyst fluid was used as sample and the assay was performed in microplate wells. The absorbance values were measured at 595 nm and standard curve was generated by Microsoft Office Excel software. The protein concentration of sample was calculated using the equation of the standard curve. Results: Average protein concentration of the sample was 1175 μg/ml. The total time needed for reading of absorbance was two minutes approximately. Conclusion: Bradford microplate protein assay is a fast and suitable method. This method could be replacing the time consuming method with cuvette. In addition, if this assay produces as a low price kit it could have many benefits for students and laboratories that need to determine protein concentration by Bradford assay.
Fuzzy logic , trading uncertainty and technical trading

From the market microstructure perspective, technical analysis can be profitable when informed traders make systematic mistakes or when uninformed traders have predictable impacts on price. However, chartists face a considerable degree of trading uncertainty because technical indicators such as moving averages are essentially imperfect filters with a nonzero phase shift. Consequently, technical trading may result in erroneous trading recommendations and substantial losses. This paper presents an uncertainty reduction approach based on fuzzy logic that addresses two problems related to the uncertainty embedded in technical trading strategies: market timing and order size. The results of our high-frequency exercises show that ‘fuzzy technical indicators’ dominate standard moving average technical indicators and filter rules for the Euro-US dollar (EUR-USD) exchange rates, especially on high-volatility days. 2012 Elsevier B.V. All rights reserved.
Frame Selected Approach for Hiding Data within MPEG Video Using Bit Plane Complexity Segmentation

-Bit Plane Complexity Segmentation (BPCS) digital picture steganography is a technique to hide data inside an image file. BPCS achieves high embedding rates with low distortion based on the theory that noise-like regions in an image’s bit-planes can be replaced with noise-like secret data without significant loss in image quality. . In this framework we will propose a collaborate approach for select frame for Hiding Data within MPEG Video Using Bit Plane Complexity Segmentation. This approach will invent high secure data hidden using select frame form MPEG Video and furthermore we will assign the well-built of the approach; during this review the author will answer the question why they used select frame steganography. In additional to the security issues we will use the digital video as a cover to the data hidden. The reason behind opt the video cover in this approach is the huge amount of single frames image per sec which in turn overcome the problem of the data hiding quantity, as the experiment result shows the success of the hidden data within select frame, extract data from the frames sequence. These function without affecting the quality of the video.
Dietary Reference Intakes: summary of applications in dietary assessment.

OBJECTIVE
To summarise the applications and appropriate use of Dietary Reference Intakes (DRIs) as guidance for nutrition and health research professionals in the dietary assessment of groups and individuals.


DESIGN
Key points from the Institute of Medicine report, Dietary Reference Intakes: Applications in Dietary Assessment, are summarised in this paper. The different approaches for using DRIs to evaluate the intakes of groups vs. the intakes of individuals are highlighted.


RESULTS
Each of the new DRIs is defined and its role in the dietary assessment of groups and individuals is described. Two methods of group assessment and a new method for quantitative assessment of individuals are described. Illustrations are provided on appropriate use of the Estimated Average Requirement (EAR), the Adequate Intake (AI) and the Tolerable Upper Intake Level (UL) in dietary assessment.


CONCLUSIONS
Dietary assessment of groups or individuals must be based on estimates of usual (long-term) intake. The EAR is the appropriate DRI to use in assessing groups and individuals. The AI is of limited value in assessing nutrient adequacy, and cannot be used to assess the prevalence of inadequacy. The UL is the appropriate DRI to use in assessing the proportion of a group at risk of adverse health effects. It is inappropriate to use the Recommended Dietary Allowance (RDA) or a group mean intake to assess the nutrient adequacy of groups.