nils-herrmann/clean_scirepeval huggingface dataset:
MD-Logic Artificial Pancreas System

Current state-of-the-art artificial pancreas systems are either based on traditional linear control theory or rely on mathematical models of glucose-insulin dynamics. Blood glucose control using these methods is limited due to the complexity of the biological system. The aim of this study was to describe the principles and clinical performance of the novel MD-Logic Artificial Pancreas (MDLAP) System.



The MDLAP applies fuzzy logic theory to imitate lines of reasoning of diabetes caregivers. It uses a combination of control-to-range and control-to-target strategies to automatically regulate individual glucose levels. Feasibility clinical studies were conducted in seven adults with type 1 diabetes (aged 19-30 years, mean diabetes duration 10 +/- 4 years, mean A1C 6.6 +/- 0.7%). All underwent 14 full, closed-loop control sessions of 8 h (fasting and meal challenge conditions) and 24 h.



The mean peak postprandial (overall sessions) glucose level was 224 +/- 22 mg/dl. Postprandial glucose levels returned to <180 mg/dl within 2.6 +/- 0.6 h and remained stable in the normal range for at least 1 h. During 24-h closed-loop control, 73% of the sensor values ranged between 70 and 180 mg/dl, 27% were >180 mg/dl, and none were <70 mg/dl. There were no events of symptomatic hypoglycemia during any of the trials.



The MDLAP system is a promising tool for individualized glucose control in patients with type 1 diabetes. It is designed to minimize high glucose peaks while preventing hypoglycemia. Further studies are planned in the broad population under daily-life conditions.
3D mesh compression

In this chapter, we discuss 3D compression techniques for reducing the delays in transmitting triangle meshes over the Internet. We first explain how vertex coordinates, which represent surface samples may be compressed through quantization, prediction, and entropy coding. We then describe how the connectivity, which specifies how the surface interpolates these samples, may be compressed by compactly encoding the parameters of a connectivity-graph construction process and by transmitting the vertices in the order in which they are encountered by this process. The storage of triangle meshes compressed with these techniques is usually reduced to about a byte per triangle. When the exact geometry and connectivity of the mesh are not essential, the triangulated surface may be simplified or retiled. Although simplification techniques and the progressive transmission of refinements may be used as a compression tool, we focus on recently proposed retiling techniques designed specifically to improve 3D compression. They are often able to reduce the total storage, which combines coordinates and connectivity, to half-a-bit per triangle without exceeding a mean square error of 1/10,000 of the diagonal of a box that contains the solid.
Validity of Antonovsky's sense of coherence scale: a systematic review.

The aim of this paper is to systematically review and analyse the validity and reliability of Antonovsky's life orientation questionnaire/sense of coherence scale (SOC).



The study is descriptive and analytical with a systematic integration of the contemporary knowledge base on the salutogenic research published 1992-2003. The review includes 458 scientific publications and 13 doctoral theses.



Worldwide, based on postgraduate scientific publications in eight authorized databases, doctoral theses, and available books.



The SOC questionnaire has been used in at least 33 languages in 32 countries with at least 15 different versions of the questionnaire. In 124 studies using SOC-29 the Cronbach's alpha ranges from 0.70 to 0.95. The alpha values in 127 studies using SOC-13 range from 0.70 to 0.92, and in 60 studies using a modified SOC scale range from 0.35 to 0.91. Test-retest correlation show stability and range from 0.69 to 0.78 (1 year), 0.64 (3 years), 0.42 to 0.45 (4 years), 0.59 to 0.67 (5 years) to 0.54 (10 years). The means of SOC-29 range 100.50 (SD 28.50) to 164.50 (SD 17.10) points and SOC-13 from 35.39 (SD 0.10) to 77.60 (SD 13.80) points. After 10 years SOC seems to be comparatively stable, but not as stable as Antonovsky initially assumed. SOC tends to increase with age. The factorial structure of SOC seems rather to be multidimensional than unidimensional. SOC predicts a positive outcome in a long term perspective, although there are divergent findings reported. The SOC scale seems to be a reliable, valid, and cross culturally applicable instrument measuring how people manage stressful situations and stay well.
An Event-B formalization of KAOS goal refinement patterns

Goals play an important role in requirements engineering process, and consequently in systems development process. Whereas specifications allow us to answer the question ”WHAT the system does”, goals allow us to address the ”WHY, WHO, WHEN” questions . Up to now, the main software development approaches using formal methods, such as Event-B, begins at the specification level. Our objective is to include requirements analysis within this process, and more precisely the KAOS method, which is a goal-oriented methodology for requirements engineering. The latter allows analysts to build requirements models and to derive requirements documents. Existing work that combine KAOS with formal methods generate a formal specification model from a KAOS requirements model. We aim at expressing KAOS goal models with a formal language (Event-B), hence staying at the same abstraction level. Thus we take advantage from the Event-B method: (i) it is possible to use the method during the whole development process and (ii) we can benefit from the industrial maturity of tools supporting the method. For that purpose, we propose a constructive approach in which Event-B models are built incrementally from KAOS goal models, driven by goal refinement patterns.
Non-contact video-based pulse rate measurement on a mobile service robot

Non-contact image photoplethysmography has gained a lot of attention during the last 5 years. Starting with the work of Verkruysse et al. , various methods for estimation of the human pulse rate from video sequences of the face under ambient illumination have been presented. Applied on a mobile service robot aimed to motivate elderly users for physical exercises, the pulse rate can be a valuable information in order to adapt to the users conditions. For this paper, a typical processing pipeline was implemented on a mobile robot, and a detailed comparison of methods for face segmentation was conducted, which is the key factor for robust pulse rate extraction even, if the subject is moving. A benchmark data set is introduced focusing on the amount of motion of the head during the measurement.
Applications Know Best: Performance-Driven Memory Overcommit with Ginkgo

Memory over commitment enables cloud providers to host more virtual machines on a single physical server, exploiting spare CPU and I/O capacity when physical memory becomes the bottleneck for virtual machine deployment. However, over commiting memory can also cause noticeable application performance degradation. We present Ginkgo, a policy framework for over omitting memory in an informed and automated fashion. By directly correlating application-level performance to memory, Ginkgo automates the redistribution of scarce memory across all virtual machines, satisfying performance and capacity constraints. Ginkgo also achieves memory gains for traditionally fixed-size Java applications by coordinating the redistribution of available memory with the activities of the Java Virtual Machine heap. When compared to a non-over commited system, Ginkgo runs the Day Trader 2.0 and SPEC Web 2009 benchmarks with the same number of virtual machines while saving up to 73% (50% omitting free space) of a physical server's memory while keeping application performance degradation within 7%.
Radio Frequency Time-of-Flight Distance Measurement for Low-Cost Wireless Sensor Localization

Location-aware wireless sensor networks will enable a new class of applications, and accurate range estimation is critical for this task. Low-cost location determination capability is studied almost entirely using radio frequency received signal strength (RSS) measurements, resulting in poor accuracy. More accurate systems use wide bandwidths and/or complex time-synchronized infrastructure. Low-cost, accurate ranging has proven difficult because small timing errors result in large range errors. This paper addresses estimation of the distance between wireless nodes using a two-way ranging technique that approaches the Cramér-Rao Bound on ranging accuracy in white noise and achieves 1-3 m accuracy in real-world ranging and localization experiments. This work provides an alternative to inaccurate RSS and complex, wide-bandwidth methods. Measured results using a prototype wireless system confirm performance in the real world.
Unusual suicidal smothering by means of multiple loops of adhesive gummed tape.

In suicidal asphyxia smothering is very rare, especially when caused by winding strips of adhesive tape around the head to cover the nose and mouth. The authors report a very unusual case in which the deceased, a 66-year-old man, was found with two strips of tape wound around his head: the first, more superficial tape was wrapped six times and the second was wrapped nine times. Only integration of the crime scene data with those of the autopsy and the patient's psychological profile enabled identification of the event as suicide.
Resolving the Predicament of Android Custom Permissions

Android leverages a set of system permissions to protect platform resources. At the same time, it allows untrusted third-party applications to declare their own custom permissions to regulate access to app components. However, Android treats custom permissions the same way as system permissions even though they are declared by entities of different trust levels. In this work, we describe two new classes of vulnerabilities that arise from the ‘predicament’ created by mixing system and custom permissions in Android. These have been acknowledged as serious security flaws by Google and we demonstrate how they can be exploited in practice to gain unauthorized access to platform resources and to compromise popular Android apps. To address the shortcomings of the system, we propose a new modular design called Cusper for the Android permission model. Cusper separates the management of system and custom permissions and introduces a backward-compatible naming convention for custom permissions to prevent custom permission spoofing. We validate the correctness of Cusper by 1) introducing the first formal model of Android runtime permissions, 2) extending it to describe Cusper, and 3) formally showing that key security properties that can be violated in the current permission model are always satisfied in Cusper. To demonstrate Cusper’s practicality, we implemented it in the Android platform and showed that it is both effective and efficient.
LPS Increases 5-LO Expression on Monocytes via an Activation of Akt-Sp1/NF-κB Pathways

5-Lipoxygenase (5-LO) plays a pivotal role in the progression of atherosclerosis. Therefore, this study investigated the molecular mechanisms involved in 5-LO expression on monocytes induced by LPS. Stimulation of THP-1 monocytes with LPS (0~3 µg/ml) increased 5-LO promoter activity and 5-LO protein expression in a concentration-dependent manner. LPS-induced 5-LO expression was blocked by pharmacological inhibition of the Akt pathway, but not by inhibitors of MAPK pathways including the ERK, JNK, and p38 MAPK pathways. In line with these results, LPS increased the phosphorylation of Akt, suggesting a role for the Akt pathway in LPS-induced 5-LO expression. In a promoter activity assay conducted to identify transcription factors, both Sp1 and NF-κB were found to play central roles in 5-LO expression in LPS-treated monocytes. The LPS-enhanced activities of Sp1 and NF-κB were attenuated by an Akt inhibitor. Moreover, the LPS-enhanced phosphorylation of Akt was significantly attenuated in cells pretreated with an anti-TLR4 antibody. Taken together, 5-LO expression in LPS-stimulated monocytes is regulated at the transcriptional level via TLR4/Akt-mediated activations of Sp1 and NF-κB pathways in monocytes.
Ground penetrating radar for tunnel detection

Ground penetrating radar (GPR) systems have important civil and military applications and can be used for surveying subsurface structures such as bunkers, tunnels and buried pipes. However, GPR systems for detecting deep tunnels still face many challenges, and their performance often depends on soil types, specific targets and subsurface geological features. This paper discusses challenges in tunnel detection and provides a useful and efficient procedure to develop system requirements and predict detection performance.
How does clickthrough data reflect retrieval quality?

Automatically judging the quality of retrieval functions based on observable user behavior holds promise for making retrieval evaluation faster, cheaper, and more user centered. However, the relationship between observable user behavior and retrieval quality is not yet fully understood. We present a sequence of studies investigating this relationship for an operational search engine on the arXiv.org e-print archive. We find that none of the eight absolute usage metrics we explore (e.g., number of clicks, frequency of query reformulations, abandonment) reliably reflect retrieval quality for the sample sizes we consider. However, we find that paired experiment designs adapted from sensory analysis produce accurate and reliable statements about the relative quality of two retrieval functions. In particular, we investigate two paired comparison tests that analyze clickthrough data from an interleaved presentation of ranking pairs, and we find that both give accurate and consistent results. We conclude that both paired comparison tests give substantially more accurate and sensitive evaluation results than absolute usage metrics in our domain.
Agricultural waste Annona squamosa peel extract: biosynthesis of silver nanoparticles.

Development of reliable and eco-friendly process for the synthesis of metallic nanoparticles is an important step in the field of application of nanotechnology. We have developed modern method by using agriculture waste to synthesize silver nanoparticles by employing an aqueous peel extract of Annona squamosa in AgNO(3). Controlled growth of silver nanoparticles was formed in 4h at room temperature (25°C) and 60°C. AgNPs were irregular spherical in shape and the average particle size was about 35±5 nm and it is consistent with particle size obtained by XRD Scherer equation.
Cerebellar Changes in Guinea Pig Offspring Following Suppression of Neurosteroid Synthesis During Late Gestation

Elevated gestational concentrations of allopregnanolone are essential for the development and neuroprotection of the foetal brain. Preterm birth deprives the foetus of these high levels of allopregnanolone, which may contribute to the associated adverse effects on cerebellar development. Preterm birth alters expression of GABAA receptor subunit composition, which may further limit neurosteroid action. The objective of this study was to determine the effects of suppression of allopregnanolone levels on the markers of development and functional outcome. Pregnant guinea pigs were treated with finasteride at a dose (25 mg/kg maternal weight) shown to suppress allopregnanolone between 60 days of gestation until delivery (term ∼71 days). The cerebella from neonates, whose mothers were treated with finasteride or vehicle during pregnancy, were collected at postnatal age 8. Pups that received finasteride displayed significantly greater glial fibrillary acid protein area coverage and reduced GABAA receptor α6-subunit messenger RNA within the cerebellum than pups that were exposed to vehicle. These findings indicate that loss of neurosteroid action on the foetal brain in late gestation produces prolonged astrocyte activation and reductions in GABAA receptor α6-subunit expression. These changes may contribute to the long-term changes in function associated with preterm birth.
Increasing trend of wearables and multimodal interface for human activity monitoring: A review.

Activity recognition technology is one of the most important technologies for life-logging and for the care of elderly persons. Elderly people prefer to live in their own houses, within their own locality. If, they are capable to do so, several benefits can follow in terms of society and economy. However, living alone may have high risks. Wearable sensors have been developed to overcome these risks and these sensors are supposed to be ready for medical uses. It can help in monitoring the wellness of elderly persons living alone by unobtrusively monitoring their daily activities. The study aims to review the increasing trends of wearable devices and need of multimodal recognition for continuous or discontinuous monitoring of human activity, biological signals such as Electroencephalogram (EEG), Electrooculogram (EOG), Electromyogram (EMG), Electrocardiogram (ECG) and parameters along with other symptoms. This can provide necessary assistance in times of ominous need, which is crucial for the advancement of disease-diagnosis and treatment. Shared control architecture with multimodal interface can be used for application in more complex environment where more number of commands is to be used to control with better results in terms of controlling.
A Multi-User Game-Theoretical Multipath Routing Protocol to Send Video-Warning Messages over Mobile Ad Hoc Networks

The prevention of accidents is one of the most important goals of ad hoc networks in smart cities. When an accident happens, dynamic sensors (e.g., citizens with smart phones or tablets, smart vehicles and buses, etc.) could shoot a video clip of the accident and send it through the ad hoc network. With a video message, the level of seriousness of the accident could be much better evaluated by the authorities (e.g., health care units, police and ambulance drivers) rather than with just a simple text message. Besides, other citizens would be rapidly aware of the incident. In this way, smart dynamic sensors could participate in reporting a situation in the city using the ad hoc network so it would be possible to have a quick reaction warning citizens and emergency units. The deployment of an efficient routing protocol to manage video-warning messages in mobile Ad hoc Networks (MANETs) has important benefits by allowing a fast warning of the incident, which potentially can save lives. To contribute with this goal, we propose a multipath routing protocol to provide video-warning messages in MANETs using a novel game-theoretical approach. As a base for our work, we start from our previous work, where a 2-players game-theoretical routing protocol was proposed to provide video-streaming services over MANETs. In this article, we further generalize the analysis made for a general number of N players in the MANET. Simulations have been carried out to show the benefits of our proposal, taking into account the mobility of the nodes and the presence of interfering traffic. Finally, we also have tested our approach in a vehicular ad hoc network as an incipient start point to develop a novel proposal specifically designed for VANETs.
Deep Deterministic Policy Gradient for Urban Traffic Light Control

Traffic light timing optimization is still an active line of research despite the wealth of scientific literature on the topic, and the problem remains unsolved for any non-toy scenario. One of the key issues with traffic light optimization is the large scale of the input information that is available for the controlling agent, namely all the traffic data that is continually sampled by the traffic detectors that cover the urban network. This issue has in the past forced researchers to focus on agents that work on localized parts of the traffic network, typically on individual intersections, and to coordinate every individual agent in a multi-agent setup. In order to overcome the large scale of the available state information, we propose to rely on the ability of deep Learning approaches to handle large input spaces, in the form of Deep Deterministic Policy Gradient (DDPG) algorithm. We performed several experiments with a range of models, from the very simple one (one intersection) to the more complex one (a big city section).
Nurse managers' preferred and perceived leadership styles: a study at an Italian hospital.

The aim of this cross-sectional descriptive study was to compare the different leadership styles based on perceptions of nurse managers and their staff.



Nurse managers' styles are fundamental to improving subordinates' performance and achieving goals at health-care institutions.



This was a cross-sectional study. A questionnaire developed by Ekvall & Arvonen, considering three leadership domains (Change, Production and Employee relations), was administered to all nurse managers and to their subordinates at a city hospital in north-east Italy.



The comparison between the leadership styles actually adopted and those preferred by the nurse managers showed that the preferred style always scored higher than the style adopted, the difference reaching statistical significance for Change and Production. The leadership styles preferred by subordinates always scored higher than the styles their nurse managers actually adopted; in the subordinates' opinion, the differences being statistically significant in all three leadership domains.



The study showed that nurse managers' expectations in relation to their leadership differ from those of their subordinates. These findings should be borne in mind when selecting and training nurse managers and other personnel, and they should influence the hospital's strategic management of nurses.
Full LR(1) parser generator Hyacc and study on the performance of LR(1) algorithms

Despite the popularity of LALR(1) parser generators such as Yacc/Bison and LL parser generators such as ANTLR, robust and effective LR(1) parser generators are rare due to expensive performance and implementation difficulty. This work employed relevant algorithms, including the Knuth canonical algorithm, Pager's practical general method, lane-tracing algorithm, unit production elimination algorithm and its extension, and the edge-pushing algorithm, implemented an efficient, practical and Yacc/Bison-compatible open-source parser generator Hyacc, which supports full LR(0)/LALR(1)/LR(1) and partial LR(k). Based on the implementation, an empirical study was conducted comparing different LR(1) parser generation algorithms and LALR(1) algorithms. The result shows that LR(1) parser generation based upon improved algorithms and carefully selected data structures can be sufficiently efficient to be of practical use with modern computing facilities.