LLukas22/scidocs huggingface dataset:
Adrenocorticotrophic hormone (ACTH) responsiveness to ghrelin increases after 6 months of ketoconazole use in patients with Cushing's disease: comparison with GH-releasing peptide-6 (GHRP-6).

BACKGROUND
In Cushing's disease (CD), adrenocorticotrophic hormone (ACTH)/cortisol responses to growth hormone secretagogues (GHS), such as ghrelin and GHRP-6, are exaggerated. The effect of clinical treatment of hypercortisolism with ketoconazole on ACTH secretion in CD is controversial. There are no studies evaluating ACTH/cortisol responses to GHS after prolonged ketoconazole use in these patients.


OBJECTIVE
To compare ghrelin- and GHRP-6-induced ACTH/cortisol release before and after ketoconazole treatment in patients with CD.


DESIGN/PATIENTS
Eight untreated patients with CD (BMI: 28.5 +/- 0.8 kg/m(2)) were evaluated before and after 3 and 6 months of ketoconazole treatment and compared with 11 controls (BMI: 25.0 +/- 0.8).


RESULTS
After ketoconazole use, mean urinary free cortisol values decreased significantly (before: 613.6 +/- 95.2 nmol/24 h; 3rd month: 170.0 +/- 27.9; 6th month: 107.9 +/- 30.1). The same was observed with basal serum cortisol (before: 612.5 +/- 69.0 nmol/l; 3rd month: 463.5 +/- 44.1; 6th month: 402.8 +/- 44.1) and ghrelin- and GHRP-6-stimulated peak cortisol levels (before: 1183.6 +/- 137.9 and 1045.7 +/- 132.4; 3rd month: 637.3 +/- 69.0 and 767.0 +/- 91.0; 6th month: 689.8 +/- 74.5 and 571.1 +/- 71.7 respectively). An increase in basal ACTH (before: 11.2 +/- 1.6 pmol/l; 6th month: 19.4 +/- 2.7) and in ghrelin-stimulated peak ACTH values occurred after 6 months (before: 59.8 +/- 15.4; 6th month: 112.0 +/- 11.2). GHRP-6-induced ACTH release also increased (before: 60.7 +/- 17.2; 6th month: 78.5 +/- 12.1), although not significantly.


CONCLUSIONS
The rise in basal ACTH levels during ketoconazole treatment in CD could be because of the activation of normal corticotrophs, which were earlier suppressed by hypercortisolism. The enhanced ACTH responses to ghrelin after ketoconazole in CD could also be due to activation of the hypothalamic-pituitary-adrenal axis and/or to an increase in GHS-receptors expression in the corticotroph adenoma, consequent to reductions in circulating glucocorticoids.
Intensification of antiretroviral therapy with raltegravir or addition of hyperimmune bovine colostrum in HIV-infected patients with suboptimal CD4+ T-cell response: a randomized controlled trial.

BACKGROUND
Despite virally suppressive combination antiretroviral therapy (cART), some HIV-infected patients exhibit suboptimal CD4(+) T-cell recovery. This study aimed to determine the effect of intensification of cART with raltegravir or addition of hyperimmune bovine colostrum (HIBC) on CD4(+) T-cell count in such patients.


METHODS
We randomized 75 patients to 4 treatment groups to receive raltegravir, HIBC, placebo, or both raltegravir and HIBC in a factorial, double-blind study. The primary endpoint was time-weighted mean change in CD4(+) T-cell count from baseline to week 24. T-cell activation (CD38(+) and HLA-DR(+)), plasma markers of microbial translocation (lipopolysaccharide, 16S rDNA), monocyte activation (soluble (s) CD14), and HIV-RNA (lowest level of detection 4 copies/mL) were monitored. Analysis was performed using linear regression methods.


RESULTS
Compared with placebo, the addition of neither raltegravir nor HIBC to cART for 24 weeks resulted in a significant change in CD4(+) T-cell count (mean difference, 95% confidence interval [CI]: 3.09 cells/μL, -14.27; 20.45, P = .724 and 9.43 cells/μL, -7.81; 26.68, P = .279, respectively, intention to treat). There was no significant interaction between HIBC and raltegravir (P = .275). No correlation was found between CD4(+) T-cell count and plasma lipopolysaccharide, 16S rDNA, sCD14, or HIV-RNA.


CONCLUSION
The determinants of poor CD4(+) T-cell recovery following cART require further investigation.


CLINICAL TRIALS REGISTRATION
ClinicalTrials.gov identifier: NCT00772590, Australia New Zealand Clinical Trials Registry: ACTRN12609000575235.
TM4L: Creating and browsing educational topic maps

In this article we describe TM4L an environment for building, maintaining, and using standards-based, ontology-aware e-learning repositories. It is based on the idea that concept-driven access to learning material implemented as a Topic Map can bridge the gap between a learner and targeted knowledge. One of the driving goals of this work is to increase the reusability of available educational resources by enabling the use of a developed subject ontology with courses on the same subject with different stricture. Another goal of TM4L is to support an efficient context-based retrieval of learning content tailored to the needs of a learner working on an educational task. The paper focuses on three aspects of the TM4L environment: domain modeling, editing capabilities and the interface for exploring the learning collection. The key features of the TM4L functionality are illustrated with some
Superpixel-Based Difference Representation Learning for Change Detection in Multispectral Remote Sensing Images

With the rapid technological development of various satellite sensors, high-resolution remotely sensed imagery has been an important source of data for change detection in land cover transition. However, it is still a challenging problem to effectively exploit the available spectral information to highlight changes. In this paper, we present a novel change detection framework for high-resolution remote sensing images, which incorporates superpixel-based change feature extraction and hierarchical difference representation learning by neural networks. First, highly homogenous and compact image superpixels are generated using superpixel segmentation, which makes these image blocks adhere well to image boundaries. Second, the change features are extracted to represent the difference information using spectrum, texture, and spatial features between the corresponding superpixels. Third, motivated by the fact that deep neural network has the ability to learn from data sets that have few labeled data, we use it to learn the semantic difference between the changed and unchanged pixels. The labeled data can be selected from the bitemporal multispectral images via a preclassification map generated in advance. And then, a neural network is built to learn the difference and classify the uncertain samples into changed or unchanged ones. Finally, a robust and high-contrast change detection result can be obtained from the network. The experimental results on the real data sets demonstrate its effectiveness, feasibility, and superiority of the proposed technique.
Usability evaluation of mobile applications using ISO 9241 and ISO 25062 standards

This paper presents an empirical study based on a set of measures to evaluate the usability of mobile applications running on different mobile operating systems, including Android, iOS and Symbian. The aim is to evaluate empirically a framework that we have developed on the use of the Software Quality Standard ISO 9126 in mobile environments, especially the usability characteristic. To do that, 32 users had participated in the experiment and we have used ISO 25062 and ISO 9241 standards for objective measures by working with two widely used mobile applications: Google Apps and Google Maps. The QUIS 7.0 questionnaire have been used to collect measures assessing the users' level of satisfaction when using these two mobile applications. By analyzing the results we highlighted a set of mobile usability issues that are related to the hardware as well as to the software and that need to be taken into account by designers and developers in order to improve the usability of mobile applications.
Distributed Position Localization and Tracking (DPLT) of Malicious Nodes in Cluster Based Mobile Ad hoc Networks (MANET)

In this paper, a robust distributed malicious node detection and precise localization and tracking method is proposed for Cluster based Mobile Ad hoc Network (MANET). Certificate Authority (CA) node is selected as the most stable node among trusted nodes, surrounded by Registration Authority nodes (RAs) in each cluster to generate the Dynamic Demilitarized Zone (DDMZ) to defend CA from probable attackers and mitigate the authentication overhead. The RAs also co-operate with member nodes to detect a target node and determine whether it is malicious or not, by providing the public key certificate and trust value. In addition, Internet Protocol (IP) based Triangulation and multi-lateration method are deployed based on using the average time difference of Time of Arrival (ToA) and Time of Departure (ToD) of the management packets. Triangulation uses three reference nodes which are elected within each cluster based on Best Criterion Function (BCF) to localize each member node inside the cluster in 2D. Multi-lateration is employed to localize the malicious target node in 2D using four neighbor nodes. After localization of two consecutive positions, the target node is continuously localized and tracked by a particular node using the modified real time Position Localization and Tracking (PL&T) algorithm by adaptive beam forming and mapping the energy contours of tracking zone into coverage radii distance. The performance of the proposed scheme demonstrates the significant accuracy in the detection of malicious nodes within each cluster. Key-Words: Koay Distributed Position, Localization, Tracking (PL&T), Malicious node, Mobile Ad hoc Networks.
A tutorial on task-parameterized movement learning and retrieval

Task-parameterized models of movements aims at automatically adapting movements to new situations encountered by a robot. The task parameters can for example take the form of positions of objects in the environment, or landmark points that the robot should pass through. This tutorial aims at reviewing existing approaches for task-adaptive motion encoding. It then narrows down the scope to the special case of task parameters that take the form of frames of reference, coordinate systems, or basis functions, which are most commonly encountered in service robotics. Each section of the paper is accompanied with source codes designed as simple didactic examples implemented in Matlab with a full compatibility with GNU Octave, closely following the notation and equations of the article. It also presents ongoing work and further challenges that remain to be addressed, with examples provided in simulation and on a real robot (transfer of manipulation behaviors to the Baxter bimanual robot). The repository for the accompanying source codes is available at http://www.idiap.ch/software/pbdlib/.
Increasing fruit and vegetable intake and decreasing fat and sugar intake in families at risk for childhood obesity.

OBJECTIVE
The goal of this study was to evaluate the effect of a parent-focused behavioral intervention on parent and child eating changes and on percentage of overweight changes in families that contain at least one obese parent and a non-obese child.


RESEARCH METHODS AND PROCEDURES
Families with obese parents and non-obese children were randomized to groups in which parents were provided a comprehensive behavioral weight-control program and were encouraged to increase fruit and vegetable intake or decrease intake of high-fat/high-sugar foods. Child materials targeted the same dietary changes as their parents without caloric restriction.


RESULTS
Changes over 1 year showed that treatment influenced targeted parent and child fruit and vegetable intake and high-fat/high-sugar intake, with the Increase Fruit and Vegetable group also decreasing their consumption of high-fat/high-sugar foods. Parents in the increased fruit and vegetable group showed significantly greater decreases in percentage of overweight than parents in the decreased high-fat/high-sugar group.


DISCUSSION
These results suggest that focusing on increasing intake of healthy foods may be a useful approach for nutritional change in obese parents and their children.
Pneumonia in multiple injured patients: a prospective controlled trial on early prediction using clinical and immunological parameters

Objective and design: In a prospective trial 266 multiple injured patients were included to evaluate clinical risk factors and immune parameters related to pneumonia.¶Methods: Clinical and humoral parameters were assessed and multivariate analysis performed.¶Results: The multivariate analysis (odds ratio with 95% confidence interval (CI)) revealed male gender (3.65), traumatic brain injury (TBI) (2.52), thorax trauma (AISthorax≤ 3) (2.05), antibiotic prophylaxis (1.30), injury severity score (ISS) (1.03 per ISS point) and the age (1.02 per year) as risk factors for pneumonia. The main pathogens were Acinetobacter Baumannii (40%) and Staphylococcus aureus (25%). A tendency towards higher Procalcitonin (PCT) and Interleukin (IL)-6 levels two days after trauma was observed for pneumonia patients.¶Conclusion: The immune parameters (PCT, IL-6, IL-10, soluble tumor necrosis factor p-55 and p-75) could not confirm the diagnosis of pneumonia earlier than the clinical parameters.
Geographies of Sustainability: Low Impact Developments and Radical Spaces of Innovation

Drawing upon low impact development (LID), a radical approach to housing, livelihoods and everyday living, this article interrogates the notion of sustainability and argues for greater attention to be paid to its geographies. We wish to reconceptualise the geographies of sustainability to do five things: (i) pay close attention to ‘actually existing sustainabilities’; (ii) consider radical solutions; (iii) consider sustainability as holistic, integrating social, economic and environmental factors; (iv) be more assertively political; and (v) include a clearer consideration of scale. Drawing on a detailed case study of LID, we identify seven insights into how geographers, and others, can further shape debates about geographies of sustainability. LID emphasises flexibility, holism, engaging with questions of scale, transferability, mixed and modern approaches, and popular participation whilst acknowledging the difficulties of practising sustainability. All of this allows LID to offer valuable insights into how geographers could be considering questions of sustainability.
Construction Simulation Research at the University of Michigan

AT THE UNIVERSITY OF MICHIGAN Robert I. Carr Professor of Civil Engineering Introduction The paper summarizes three current research thrusts at the University of Michigan to advance the state of the art of computer modeling of construction. They can be classified as (1) process simulation, (2) project simulation, and (3) project time-cost tradeoff. The research was born out of a concern for the limited capacity of available techniques to model construction realities. Construction managers select methods to assertible material resources using human and equipment resources. Tasks are linked as activities, which are performed in a sequence dictated by physical and resource constraints. Objectives in selecting alternative methods and resource assignments are to complete the project quickly and inexpensively. Most human and equipment resources and methods are shared among several activities, as are supervision, weather, and other duration and cost related variables. Some of the variables, such as construction methods and personnel and equipment assignments are selected by managers and are therefore decision variables. The magnitudes of other variables, such as crew and equipment productivities and weather, are uncertain and can be considered selected by nature and are therefore random variables. In reality, managers make decisions as they are needed, based on progress and information available to date, and they monitor
Effectiveness of virtual reality using Wii gaming technology in stroke rehabilitation: a pilot randomized clinical trial and proof of principle.

BACKGROUND AND PURPOSE
Hemiparesis resulting in functional limitation of an upper extremity is common among stroke survivors. Although existing evidence suggests that increasing intensity of stroke rehabilitation therapy results in better motor recovery, limited evidence is available on the efficacy of virtual reality for stroke rehabilitation.


METHODS
In this pilot, randomized, single-blinded clinical trial with 2 parallel groups involving stroke patients within 2 months, we compared the feasibility, safety, and efficacy of virtual reality using the Nintendo Wii gaming system (VRWii) versus recreational therapy (playing cards, bingo, or "Jenga") among those receiving standard rehabilitation to evaluate arm motor improvement. The primary feasibility outcome was the total time receiving the intervention. The primary safety outcome was the proportion of patients experiencing intervention-related adverse events during the study period. Efficacy, a secondary outcome measure, was evaluated with the Wolf Motor Function Test, Box and Block Test, and Stroke Impact Scale at 4 weeks after intervention.


RESULTS
Overall, 22 of 110 (20%) of screened patients were randomized. The mean age (range) was 61.3 (41 to 83) years. Two participants dropped out after a training session. The interventions were successfully delivered in 9 of 10 participants in the VRWii and 8 of 10 in the recreational therapy arm. The mean total session time was 388 minutes in the recreational therapy group compared with 364 minutes in the VRWii group (P=0.75). There were no serious adverse events in any group. Relative to the recreational therapy group, participants in the VRWii arm had a significant improvement in mean motor function of 7 seconds (Wolf Motor Function Test, 7.4 seconds; 95% CI, -14.5, -0.2) after adjustment for age, baseline functional status (Wolf Motor Function Test), and stroke severity.


CONCLUSIONS
VRWii gaming technology represents a safe, feasible, and potentially effective alternative to facilitate rehabilitation therapy and promote motor recovery after stroke.
Amazons and Warrior Women. Varieties of Feminism in Seventeenth-Century Drama

Analyzes the roles of both strong-minded and antagonistic women in the plays of seventeenth-century English authors including Shakespeare, Ben Jonson, and Thomas Dekker.
Comparing T2 and T2–T3 ablation in thoracoscopic sympathectomy for palmar hyperhidrosis: a randomized control trial

Thoracoscopic sympathectomy is a useful therapeutic option for palmar hyperhidrosis. Surgeons differ in the level of the sympathetic chain ablated. This study aimed to compare the blockade of the T2 with levels T2 and T3 to verify the effectiveness of different ablation levels in relieving hyperhidrosis symptoms. For patients undergoing bilateral thoracoscopic sympathectomy for palmar hyperhidrosis, T2–T3 ablation is performed bilaterally. In our series, 25 consecutive patients were blindly randomized to undergo unilateral T2 and T3 ablation followed by contralateral ablation of level T2 only. The patients were followed up and analyzed for comparison of symptoms bilaterally, compensatory hyperhidrosis, and levels of satisfaction postoperatively. The study group consisted of 25 patients with a male:female ratio of 3:2 and a mean age of 32 years (range, 19–50 years). The mean operative time was 35 min. The patients were followed up for a mean period of 23 months (range, 2–65 months). All 25 patients confirmed that their palmar sweating resolved postoperatively, with both palms equally dry. Of the 25 patients, 20 (80%) complained of compensatory hyperhidrosis, which also was bilaterally symmetric. The areas involved were trunk (80%), lower limbs (32%), and armpits (12%). Overall, 80% of the patients were very satisfied with the procedure. The remaining 20% experienced mild to moderate compensatory hyperhidrosis, which did not seem to affect their lifestyle. The findings show that T2 ablation in thoracoscopic sympathectomy for palmar hyperhidrosis is as effective as T2–T3 ablation in terms of symptomatic relief, recurrence, compensatory hyperhidrosis, and patient satisfaction.
Actinomycetes from Sediments in the Trondheim Fjord, Norway:  Diversity and Biological Activity

The marine environment represents a largely untapped source for isolation of new microorganisms with potential to produce biologically active secondary metabolites. Among such microorganisms, Gram-positive actinomycete bacteria are of special interest, since they are known to produce chemically diverse compounds with a wide range of biological activities. We have set out to isolate and characterize actinomycete bacteria from the sediments in one of the largest Norwegian fjords, the Trondheim fjord, with respect to diversity and antibiotic-producing potential. Approximately 3,200 actinomycete bacteria were isolated using four different agar media from the sediment samples collected at different locations and depths (4.5 to 450 m). Grouping of the isolates first according to the morphology followed by characterization of isolates chosen as group representatives by molecular taxonomy revealed that Micromonospora was the dominating actinomycete genus isolated from the sediments. The deep water sediments contained a higher relative amount of Micromonospora compared to the shallow water samples. Nine percent of the isolates clearly required sea water for normal growth, suggesting that these strains represent obligate marine organisms. Extensive screening of the extracts from all collected isolates for antibacterial and antifungal activities revealed strong antibiotic-producing potential among them. The latter implies that actinomycetes from marine sediments in Norwegian fjords can be potential sources for the discovery of novel anti-infective agents.
Fusing LIDAR and images for pedestrian detection using convolutional neural networks

In this paper, we explore various aspects of fusing LIDAR and color imagery for pedestrian detection in the context of convolutional neural networks (CNNs), which have recently become state-of-art for many vision problems. We incorporate LIDAR by up-sampling the point cloud to a dense depth map and then extracting three features representing different aspects of the 3D scene. We then use those features as extra image channels. Specifically, we leverage recent work on HHA [9] (horizontal disparity, height above ground, and angle) representations, adapting the code to work on up-sampled LIDAR rather than Microsoft Kinect depth maps. We show, for the first time, that such a representation is applicable to up-sampled LIDAR data, despite its sparsity. Since CNNs learn a deep hierarchy of feature representations, we then explore the question: At what level of representation should we fuse this additional information with the original RGB image channels? We use the KITTI pedestrian detection dataset for our exploration. We first replicate the finding that region-CNNs (R-CNNs) [8] can outperform the original proposal mechanism using only RGB images, but only if fine-tuning is employed. Then, we show that: 1) using HHA features and RGB images performs better than RGB-only, even without any fine-tuning using large RGB web data, 2) fusing RGB and HHA achieves the strongest results if done late, but, under a parameter or computational budget, is best done at the early to middle layers of the hierarchical representation, which tend to represent midlevel features rather than low (e.g. edges) or high (e.g. object class decision) level features, 3) some of the less successful methods have the most parameters, indicating that increased classification accuracy is not simply a function of increased capacity in the neural network.