SIRIS-Lab/unlabelled-sti-corpus huggingface dataset:
PIH3 A COSTING STUDY COMPARING MIDWIFERY GROUP PRACTICE WITH USUAL CARE IN AN AUSTRALIAN METROPOLITAN HOSPITAL

OBJECTIVES: To undertake an economic evaluation of the costs and outcomes of midwifery group practice care compared with usual care in an Australian metropolitan hospital. METHODS: In a cohort study, pregnant women at low risk of complications could select to receive midwifery group practice care or usual care early in theirpregnancy and were recruited when they were 35 weeks pregnant. Midwifery group practice provides care by the same two to three midwives and labor in a birth center. Usual care consists of women generally attending a GP or midwives antenatal clinic for antenatal care, followed by labor in the hospital. Costing data was collected from week 36 of pregnancy until 6 weeks postpartum. Costing for antenatal, labor, baby, and postnatal care were collected using the hospital accounting system. Women kept a diary with the number of antenatal and postnatal visits. Costing data on GP visits were calculated using the diaries and government reimbursement costs. RESULTS: The study included 102 women, with 52 women receiving midwifery group practice care and 50 women receiving usual care. Midwifery group practice care was associated with fewer antenatal visits, lower rate of induction and pharmacological pain relief, shorter stay in hospital and more postnatal visits. There were no statistical differences in clinical outcomes of the baby. The cost of antenatal care was similar between the groups; labor and baby costs were lower for midwifery group practice, while postnatal costs were higher in the midwifery group practice. Midwifery group practice was associated with a lower total cost per woman compared to usual care (A$4447 vs. A$5772, P = 0.047). CONCLUSIONS: For women at low risk of complications midwifery group practice is a cost-effective option, with better clinical outcomes and lower total costs.
Layout-Aware Mixture Preparation of Biochemical Fluids on Application-Specific Digital Microfluidic Biochips

The recent proliferation of digital microfluidic (DMF) biochips has enabled rapid on-chip implementation of many biochemical laboratory assays or protocols. Sample preprocessing, which includes dilution and mixing of reagents, plays an important role in the preparation of assays. The automation of sample preparation on a digital microfluidic platform often mandates the execution of a mixing algorithm, which determines a sequence of droplet mix-split steps (usually represented as a mixing graph). However, the overall cost and performance of on-chip mixture preparation not only depends on the mixing graph but also on the resource allocation and scheduling strategy, for instance, the placement of boundary reservoirs or dispensers, mixer modules, storage units, and physical design of droplet-routing pathways. In this article, we first present a new mixing algorithm based on a number-partitioning technique that determines a layout-aware mixing tree corresponding to a given target ratio of a number of fluids. The mixing graph produced by the proposed method can be implemented on a chip with a fewer number of crossovers among droplet-routing paths as well as with a reduced reservoir-to-mixer transportation distance. Second, we propose a routing-aware resource-allocation scheme that can be used to improve the performance of a given mixing algorithm on a chip layout. The design methodology is evaluated on various test cases to demonstrate its effectiveness in mixture preparation with the help of two representative mixing algorithms. Simulation results show that on average, the proposed scheme can reduce the number of crossovers among droplet-routing paths by 89.7% when used in conjunction with the new mixing algorithm, and by 75.4% when an earlier algorithm [Thies et al. 2008] is used.
Optical Simulation and Analysis of Iso-textured Silicon Solar Cells and Modules Including Light Trapping

Abstract Solar cells made from multicrystalline silicon (mc-Si) wafers play an important role in photovoltaics. Nevertheless, tools for the optical simulation of these devices are scarce. In the present work, the reflectance and charge carrier generation of mc-Si cells and modules are for the first time simulated successfully in the complete spectral range including light trapping and escape light, as the comparison with measured reflectance of the finished cells and mini-modules shows. The “spherical caps” geometry is used to model the front surface reflection of iso-textured silicon solar cells. The characteristic angles of the spherical caps are determined from the reflectance of iso-textured wafers for three different texture strengths. Based on this calibration, the reflectance and charge carrier generation rates of cells encapsulated with EVA and glass are simulated and analysed. Iso-textured cells with full-area aluminium back surface field (Al-BSF) and with passivated emitter and rear (PERC) are quantitatively compared regarding the photo-generated current density jPh. The simulations demonstrate that the direct cell-to-module loss of iso-textured mc-Si cells with Al-BSF (0.7 mA/cm2) is smaller than for PERC cells (1.2 mA/cm2).
Biological rhythms: do they cointegrate?

Many biological systems can be seen as networks of interconnected oscillating units. Unraveling how they interact, coordinate and influence each other in a random environment is essential for understanding systems such as the dynamic brain. The problem is that the current statistical methods are insufficient for solid data analysis. To solve this problem, I will elaborate the methodology of cointegration analysis, which has been applied mainly in econometrics, to provide a principled statistical framework for analyzing experimental data from neuronal systems. I will work on this project under the supervision of Professor Susanne Ditlevsen at the University of Copenhagen (UCPH).
On the asymptotic connectivity of random networks under the random connection model

Consider a network where all nodes are distributed on a unit square following a Poisson distribution with known density ρ and a pair of nodes separated by an Euclidean distance x are directly connected with probability g(x over r ρ ), where g : [0,∞) → [0,1] satisfies three conditions: rotational invariance, qnon-increasing monotonicity and integral boundedness, equation and b is a constant, independent of the event that another pair of nodes are directly connected. In this paper, we analyze the asymptotic distribution of the number of isolated nodes in the above network using the Chen-Stein technique and the impact of the boundary effect on the number of isolated nodes as ρ → ∞. On that basis we derive a necessary condition for the above network to be asymptotically almost surely connected. These results form an important link in expanding recent results on the connectivity of the random geometric graphs from the commonly used unit disk model to the more generic and more practical random connection model.
Supervised Learning with Complex-valued Neural Networks

Recent advancements in the field of telecommunications, medical imaging and signal processing deal with signals that are inherently time varying, nonlinear and complex-valued. The time varying, nonlinear characteristics of these signals can be effectively analyzed using artificial neural networks. Furthermore, to efficiently preserve the physical characteristics of these complex-valued signals, it is important to develop complex-valued neural networks and derive their learning algorithms to represent these signals at every step of the learning process. This monograph comprises a collection of new supervised learning algorithms along with novel architectures for complex-valued neural networks. The concepts of meta-cognition equipped with a self-regulated learning have been known to be the best human learning strategy. In this monograph, the principles of meta-cognition have been introduced for complex-valued neural networks in both the batch and sequential learning modes. For applications where the computation time of the training process is critical, a fast learning complex-valued neural network called as a fully complex-valued relaxation network along with its learning algorithm has been presented. The presence of orthogonal decision boundaries helps complex-valued neural networks to outperform real-valued networks in performing classification tasks. This aspect has been highlighted. The performances of various complex-valued neural networks are evaluated on a set of benchmark and real-world function approximation and real-valued classification problems.
Support towards the oapen initiative (2018-2019)

This project supports OAPEN to enlarge the quality controlled collection of open access books already hosted by the OAPEN Library, and to develop additional services for publishers, libraries and research funders in the areas of dissemination, quality assurance and digital preservation. 
The project specifically intends to enlarge the collection of OA books and chapters relating to research funded through ERC grants, by aggregating these publications and enabling publishers and authors to deposit these publications directly into the OAPEN Library. 
The project will develop new components to increase the visibility and usage of the ERC collection, to improve integration with OpenAIRE, and to increase the understanding of societal and scholarly impact of ERC publications through an Altmetrics service.
New components include:
- Collection view: a separate website providing a branded view of the ERC collection, thereby improving the overall visibility of the collection;
- Research grant information: adding standard information from ERCEA and other sources to provide additional information about the research connected to the publication, improving discoverability and usage of the ERC collection;
- Review linking: exploring whether it is possible to link to reviews of publications, to promote these publications and increase usage.
An innovative medical device for early diagnosis based on a disruptive body temperature monitoring and analysis scheme-t-clinic

In t-Clinic, a novel medical device will be validated as a new additional tool for early detection and prognosis of a number of pathologies: cancer, sepsis, stroke, diabetes, hypertension, infectious diseases, etc., and for different applications: epidemics, critical care, paediatrics, internal medicine, etc., that are based on subtle changes in the body temperature dynamics, not just in its absolute values (discover hidden information, bring to light undetected trends, find new diagnosis correlations).
Body temperature quantification systems are currently the primary choice for standard clinical practice. However, due to the low sensitivity and specificity of these methods, a limited field of action, and null dynamics perspective, patients are often referred for secondary procedures, such as blood cultures, for more detailed diagnosis information. These referrals pose a global challenge that postpone treatment, increase the patient risks, and entail higher costs to the healthcare system (materials, labour requirements). There is a worldwide need to reduce the temporal and economic diagnosis costs to enable faster treatment of conditions and more affordable and sustainable healthcare systems by introducing preventive screenings and monitorings for earlier interventions.
Innovatec has developed an advanced non-invasive body temperature monitor capable of long-term accurate thermoregulation assessment that can provide a low cost prompt diagnosis tool that will reduce the need for referrals, and will become an effective tool for body temperature dynamics correlation with disorder onset and progression. This is achieved by means of a precise multi-site body temperature monitoring scheme based on a portable wireless device, a set of clinical temperature probes (skin, tympanic, axillary, etc.), and a number of advanced signal entropy estimation algorithms developed by Innovatec's scientists in the last years, which are our most disruptive competitive advantage.
Improving loan quality and acceptance rates by predicting credit behavior through social mediadata.

The problem:  Credit Losses on Banks’ Loan Portfolios - Youngsters and 2nd generation immigrants still have difficulty in obtaining credit.

The solution: Our credit scoring model called Big Data Score assesses the credit quality of people and accurately predicts their payment behaviour based on data from social media (Facebook) and internet browsing behaviour. 

Objectives of the overall innovation project: 
1)	Bring the present Technology Readiness from level 7 to 9.
2)	Provide the system with complete access to real life data and Open Data made available from governments.
3)	Development of a marketing and sales strategy based on two key principle: vertical approach and distribution approach.

Value Proposition: To help lenders to save money on credit losses and to make more money on increased acceptance rate.

Business Model:  Business follows a simple and easily scalable model where lender pays for each score: 
0.99 EUR per Facebook score and  0.20 EUR per browser score.

Users/Clients: Our target client is anyone who is taking a short to medium term (1-36 months) credit risk.

Competition: Traditional credit bureaus and innovative credit score (Kreditech, Leendo, ZestFinance).

Revenue Streams: 36M€ revenues at the 3rd year after commercialization.

Team: Big Data Scoring AS, Aasa Global AS.

Required funding: 1,5M€
A personal perspective on concurrency

This talk will describe a view of concurrency, the author's own, as it has evolved since the late 1970s. Early notions of concurrency were intimately tied with physical hardware and speeding up of computations, which proved to be an impediment to the development of a logical theory of concurrency. In collaboration with K. Mani Chandy, the author developed a theory called UNITY that combined a programming notation with a verification logic to describe a large class of fundamental concurrent algorithms arising in operating systems, communication protocols and distributed systems. Several model checkers, including Murphi, developed by David Dill, are based on UNITY. A limitation of UNITY was a lack of adequate structuring mechanism. While this was not a major problem in low-level applications, the current wide-spread use of concurrency requires theories that go beyond managing infrastructure to the level of massive applications. Our current research, a programming model called Orc, introduces mechanisms to organize the communication, synchronization and coordination in programs that run on wide-area networks. Orc includes constructs to orchestrate the concurrent invocation of services to achieve a goal -- while managing time-outs, priorities, and failure of sites or communication.
Geodemographic analysis and estimation of early plug-in hybrid electric vehicle adoption

Electric vehicles and hybrids are expected to become increasingly common in the coming years. The implications of growing adoption depend on its geographical extent. For instance, vehicles that are chargeable from the electrical grid, such as plug-in hybrids, can introduce problems for the distribution network especially if the vehicle adoption is spatially concentrated. In this paper, the adoption of hybrid electric vehicles is analysed in heterogeneous areas. The main purpose is to study the interrelationships between early hybrid electric vehicle adoption and different demographic and socio-economic characteristics of the areas. It is further discussed how the results can be applied to estimate the upcoming plug-in hybrid adoption. As there is a vast amount of information in the various registers of the society, slowly being opened for free usage but not fully utilised so far, it is also of interest to study and demonstrate the usability of public register data in this context. Our analysis suggests that certain characteristics of the areas strongly correlate with the hybrid electric vehicle adoption. The results of this study could be relevant, e.g., for electric distribution network planning, targeting policies to support cleaner vehicle adoption, marketing hybrid vehicles and locating charging stations.
Promotion of natural and cultural heritage to develop sustainable tourism in protected areas

PRONACUL emphasizes idea on promotion and preservation of natural and cultural heritage and support the development of transnational strategies for jointly promoting the ADRION area as a tourist destination. Partners and/or associated partners have heritage sights, protected by UNESCO or Natura 2000 or will become protected sights within PRONACUL&#39;s pilot areas. PRONACUL’s main overall objective is to achieve level of capacity for the stakeholders in the fields of improved management of natural and cultural heritage for sustainable tourism development in ADRION area. PRONACUL’s activities will make changes to the current situation by developing new tourist products, that will drive PRONACUL partners into position, where natural and cultural heritage will be perceived as new content. Changes will be made by increasing management for preservation of natural and cultural heritage for other purposes, which are appropriate for this period of time and estimated development. This will be achieved through development, application and promotion of a common methodology for management of natural and cultural heritage in Adrion area based on a participatory approach to stakeholders. Common methodology will be tested and later applied in 15 pilot areas, whose experiences will result in a joint proposal for identification of the Regional Route. Activity will be supported by the virtual chamber established for promotion of the common methodology and its transfer to other ADRION areas. The chamber will be a consulting body for tourism developers, where regions will exchange experiences and best practices in managing natural and cultural heritage. In order to improve policies for better management of natural and cultural heritage the common methodology will be disseminated to policy makers in a form of recommendations for concrete local, regional and national policy documents.
SSMART — SMC — COMPOSITE MATERIALS SRL

THE PROJECT ENVISAGED RELATES TO THE ACTIVITIES OF RESEARCH, DEVELOPMENT AND DESIGN OF A CRAFT WITH A ZERO EMISSION ENGINE, WHICH IS CHARACTERISED BY A HIGH DEGREE OF SUSTAINABILITY AND A VERY LOW ENVIRONMENTAL IMPACT, SUITABLE FOR THE TRANSPORT OF PERSONS AND THE LOGISTICAL SUPPORT IN MARINE AREAS AND THE LOGISTICAL SUPPORT OF PROTECTED INLAND WATERS AND INLAND WATERS SUPPLIED EXCLUSIVELY WITH SOLAR ENERGY. PLEASE NOTE THAT A MARK SHOULD BE ADDED TO THE REGISTRATION OF A BRAND IDENTIFYING A BRAND OF VESSELS THAT ARE POWERED ONLY AT ZERO EMISSION, AUTONOMOUS IN ENERGY TERMS POWERED ONLY BY SOLAR ENERGY PRODUCED BY PHOTOVOLTAIC PLANTS ON BOARD AND IN THE MOORING OF THE BERTH. The * individual * ÃIR VERIFIED A MEZZO WITH THE CHARACTERISTICS OF THE DEMTTE, MA ALLO STESTE TEMPO COMPATIIBLE WITH A EFFECTS TO A VERSION TO A VELOCITER PEOPLE A VELOCITUTO THE IMPACT OF NATURAL NATURE ON AM
Theoretical and observational consequences of the geometrical destabilization of inflation

The GEODESI project aims at interpreting current and forthcoming cosmological observations in a renewed theoretical framework about cosmological inflation and its ending. The simplest toy models of inflation economically explain all current data, leaving no observational clue to guide theorists towards a finer physical understanding. In this context, I very recently unveiled an hitherto unnoticed instability at play in the primordial universe that potentially affects all inflationary models and drastically modifies the interpretation of cosmological observations in terms of fundamental physics. The so-called Geometrical Destabilization of inflation reshuffles our understanding of the origin of structures in the universe, offers a new mechanism to end inflation, and promises unrivaled constraints on high-energy physics. It is crucial to develop this fresh look before a host of high-quality data from large-scale structure surveys and cosmic microwave background observations become available within the 5 year timescale of the project.

With the ERC grant I plan to build a group at the Institute of Astrophysics of Paris (IAP-CNRS) with the objective of determining the full theoretical and observational consequences of the geometrical destabilization of inflation. We will combine insights from non-standard cosmological perturbation theory and lattice simulations to constrain realistic models of inflation in high-energy physics, producing accurate theoretical predictions for a wide variety of observables, including the spectra and the non-Gaussianities of primordial fluctuations and stochastic backgrounds of gravitational waves.
Structure prediction and functional characterization of secondary metabolite proteins of Ocimum

Various species of Ocimum have acquired special attention due to their medicinal properties. Different parts of the plant (root, stem, flower, leaves) are used in the treatment of a wide range of disorders from centuries. Experimental structures (X-ray and NMR) of proteins from different Ocimum species, are not yet available in the Protein Databank (PDB). These proteins play a key role in various metabolic pathways in Ocimum. 3D structures of the proteins are essential to determine most of their functions. Homology modeling approach was employed in order to derive structures for these proteins. A program meant for comparative modeling- Modeller 9v7 was utilized for the purpose. The modeled proteins were further validated by Prochek and Verify-3d and Errat servers. Amino acid composition and polarity of these proteins was determined by CLC-Protein Workbench tool. Expasy's Prot-param server and Cys_rec tool were used for physico-chemical and functional characterization of these proteins. Studies of secondary structure of these proteins were carried out by computational program, Profunc. Swiss-pdb viewer was used to visualize and analyze these homology derived structures. The structures are finally submitted in Protein Model Database, PMDB so that they become accessible to other users for further studies.
Pregnancy outcome following gestational exposure to TNF-alpha-inhibitors: A prospective, comparative, observational study

To evaluate pregnancy safety of anti-TNF-α medications.Prospective, comparative, observational study done at the Israeli Teratology Information Service between 2002 and 2011.83 anti-TNF-α-exposed-pregnancies (97.6% in the first trimester, T1) were followed-up and compared with 86 disease-matched (DM) and 341 non-teratogenic-exposed (NTE) pregnancies. The anti-TNF-α group consisted of 35 infliximab-, 25 etanercept-, and 23 adalimumab-exposed pregnancies. The rate of major congenital anomalies did not significantly differ between the three groups [3/65 (4.6%) (anti-TNF-α, T1), 5/79 (6.3%) (DM), 8/336 (2.4%) (NTE)], even after excluding genetic or cytogenetic anomalies [3/65 (4.6%) (anti-TNF-α, T1), 4/79 (5.1%) (DM), 6/336 (1.8%) (NTE)]. There were no cases of VATER/VACTERL association.The present study suggests that anti-TNF-α treatment does not pose a major teratogenic risk in humans. This conclusion is based on relatively small numbers of exposed pregnancies and should be interpreted with caution. Larger studies are needed to establish anti-TNF-α pregnancy safety.