nils-herrmann/clean_scirepeval huggingface dataset:
Simulation of FBG temperature sensor array for oil identification via Random Forest Classification
Year: 2020

Water oil separation is important in the oil industry, as the incorrect classification of oil can lead to losses in the production and have an environmental impact. This paper proposes the use of fiber Bragg grating (FBG) temperature sensor array to identify the oil in water emulsion oil systems, using only the temperature responses for oil classification results in operational and economic benefits. To demonstrate the possibility of using the FBG temperature sensor to classify oil level, the temperature distribution of an oil storage tank, with 2 m height and 0.8 m in diameter, is simulated using thermal distribution models. Then, the temperature effect in a 2 m long FBG array with a different number and distribution of FBGs is simulated using the transfer matrix method. In each case, we extract the wavelength shift (Dl) total width at half the maximum (FWHM) and the location of the FBG in the fiber. For the oil classification, we dichotomized the fluids into oil and non oil (water and emulsion) Due to the low separability of the classes, the random forest algorithm was chosen for classification, starting with 200 FBG equidistant sensors and decreasing to 6, with different distributions along the fiber. As expected, the highest accuracy occurs with the 200 FBGs array (96% However, it was possible to classify the oil with an accuracy of 94.89% with only 8 FBGs, using tests for two proportions (with a significance of 5% the accuracy of 8 FBGs is the same as of 50 FBGs.
A Memetic Algorithm for the Multi Depot Vehicle Routing Problem with Limited Stocks
Year: 2018

The Vehicle Routing Problem (VRP) is one of important combinatorial problems, which holds a central place in logistics management. One of the most widely studied problems in the VRP family is the MultiDepot Vehicle Routing Problem (MDVRP) where more than one depot is considered. In this chapter, the authors focus on a new extension of the MDVRP in which goods loaded by the vehicle are restricted due to limited stocks available at warehouses. More specifically, this extension consists in determining a least cost routing plan that can satisfy all the customs demands by delivering available stocks. Indeed, this problem is often encountered when goods are shortage in some warehouses. To deal with the problem efficiently, a memetic algorithm is proposed in this chapter. The authors study this approach on a set of modified benchmark instances and compare its performance to a pure genetic algorithm.
A ventilator strategy combining low tidal volume ventilation, recruitment maneuvers, and high positive end expiratory pressure does not increase sedative, opioid, or neuromuscular blocker use in adults with acute respiratory distress syndrome and may improve patient comfort
Venue: Annals of Intensive Care
Year: 2014

BackgroundThe Lung Open Ventilation Study (LOV Study) compared a low tidal volume strategy with an experimental strategy combining low tidal volume, lung recruitment maneuvers, and higher plateau and positive end expiratory pressures (PEEP) in adults with acute respiratory distress syndrome (ARDS) Herein, we compared sedative, opioid, and neuromuscular blocker (NMB) use among patients managed with the intervention and control strategies and clinicians' assessment of comfort in both groups.MethodsThis was an observational substudy of the LOV Study, a randomized trial conducted in 30 intensive care units in Canada, Australia, and Saudi Arabia. In 16 centers, we recorded daily doses of sedatives, opioids, and NMBs and surveyed bedside clinicians about their own comfort with the assigned ventilator strategy and their perceptions of patient comfort. We compared characteristics and outcomes of patients who did and did not receive NMBs.ResultsStudy groups received similar sedative, opioid, and NMB dosing on days 1, 3, and 7. Patient comfort as assessed by clinicians was not different in the two groups: 93% perceived patients had no/minimal discomfort. In addition, 92% of clinicians were comfortable with the assigned ventilation strategy without significant differences between the two groups. When clinicians expressed discomfort, more expressed discomfort about PEEP levels in the intervention vs control group (2.9% vs 0.7% P <0.0001) and more perceived patient discomfort among controls (6.0% vs 4.3% P 0.049) On multivariable analysis, the strongest associations with NMB use were higher plateau pressure (hazard ratio (HR) 1.15; 95% confidence interval (CI) 1.07 to 1.23; P 0.0002) and higher daily sedative dose (HR 1.03; 95% CI 1.02 to 1.05; P <0.0001) Patients receiving NMBs had more barotrauma, longer durations of mechanical ventilation and hospital stay, and higher mortality.ConclusionsIn the LOV Study, high PEEP, low tidal volume ventilation did not increase sedative, opioid, or NMB doses in adults with ARDS, compared with a lower PEEP strategy, and appeared at least as comfortable for patients. NMB use may reflect worse lung injury, as these patients had more barotrauma, longer durations of ventilation, and higher mortality.
Caching hit probability and Compressive Sensing perspective for mobile cellular networks
Venue: Simul. Model. Pract. Theory
Year: 2018

Ever since the advent of wireless communications, there has been a tremendous growth in data traffic and service demand. Both of the above quantities are expected to explosively dominate wireless communication networks, as we move on to the future 5G wireless communication systems. This paper involves the so called hit probability related to data caching, a technique that mainly alleviates backbone network congestion and reduces latency, by storing frequently accessed data in mobile users' cache (mobility aware caching) and leaves the least popular data for recovery from base stations. The hit probability is defined in the literature as the probability of specific file request by a user together with the successful delivery of the data packet to the user/network node that made the request. Considering three distributions, the uniform, the well established Zipf like distribution and the normal distribution, we allow a varying number of cached filles and observe the curves representing the hit probabilities and perform comparison. We provide interpretation of the related to optimality results i.e. greatest achievable hit probability. In a pico cell of a cellular network of minimum radius of 50 m and a maximum radius of 200 m, we derive the transmission power level and verify that it complies to the typical transmission power of a pico cell. A final remark involves the Compressed Sensing sparsity concept, where considering that the possibility that a file is cached with probability p, and not cached with probability 1 p, we examine the <sparsest> and <densest> scenario with respect to the number of cached files n opposed to the total N files in the aggregate users' cache, plotting the equivalent total probability. A final conclusion sets the issues of future work.
Polymicrobial Candida biofilms: friends and foe in the oral cavity.
Venue: FEMS yeast research
Year: 2015

The role of polymicrobial biofilm infections in medicine is becoming more apparent. Increasing number of microbiome studies and deep sequencing has enabled us to develop a greater understanding of how positive and negative microbial interactions influence disease outcomes. An environment where this is particularly pertinent is within the oral cavity, a rich and diverse ecosystem inhabited by both bacteria and yeasts, which collectively occupy and coexist within various niches as biofilm communities. Studies within this environment have however tended to be subject to extensive independent investigation, in the context of either polymicrobial bacterial communities or yeast biofilms, but rarely both together. It is clear however that they are not mutually exclusive. Therefore, this review aims to explore the influence of candidal populations on the composition of these complex aggregates and biofilm communities, to investigate their mechanistic interactions to understand how these impact clinical outcomes, and determine whether we can translate how this knowledge can be used to improve patient management.
Anonymous IBE From Quadratic Residue With Fast Encryption
Venue: IACR Cryptol. ePrint Arch.
Year: 2020

We develop two variants of Cocks' identity based encryption. One variant has faster encryption which is as efficient as RSA encryption. The other variant makes the first variant anonymous under suitable complexity assumptions, while its decryption efficiency is about twice lower than the first one. Both the variants have ciphertext expansion twice larger than the original Cocks' identity based encryption.
A parallel query processing system based on graph based database partitioning
Venue: Inf. Sci.
Year: 2019

As parallel database systems have large amounts of data to process, it is important to utilize a scalable and efficient horizontal database partitioning method. The existing partitioning methods have major drawbacks that not only cause large amounts of data redundancy but also still require expensive shuffle operations for join queries in many cases despite their high data redundancy. We elucidate upon the drawbacks originating from the tree based partitioning schemes and propose a novel graph based database partitioning method called GPT that both improves the query performance and reduces data redundancy. We integrate the proposed GPT method into a parallel query processing system, Spark SQL, across all the relevant layers and modules, including the query plan generator and the scan operator. Through extensive experiments using three benchmarks, TPC DS, IMDB and BioWarehouse, we show that GPT significantly outperforms the state of the art method in terms of both storage overhead and query performance.
Arterial hypertension and work related risk factors: a literature review
Year: 2020

As pesquisas cientificas sobre a hipertensao arterial mostram que ainda ha muitas lacunas existentes quanto aos fatores de risco associados ao ambiente de trabalho. O estresse e um dos fatores capazes de elevar a pressao arterial, e um ambiente de trabalho estressante pode ser extremamente danoso ao trabalhador, acarretando a um estado em que ocorre desgaste do organismo humano e diminuicao da capacidade de trabalho. Parte se de uma abordagem qualitativa realizada por meio de pesquisa bibliografica embasados em varios autores. Para a construcao do corpo do estudo foi realizada uma busca na base eletronica: Portal Regional da BVS (Biblioteca Virtual em Saude) com selecao das bases de dados Medical Literature Analysis and Retrieval System Online (MEDLINE) Literatura Latino Americana e do Caribe em Ciencias da Saude (LILACS) com os descritores: hipertensao, trabalho e fatores de risco. Quando comparados, os estudos relacionados demonstraram que ha a necessidade de investigar a saude do trabalhador de maneira geral, quanto a questao da Hipertensao arterial relacionada aos fatores de risco do trabalho. Conclui se que o estresse ocupacional ta sendo uns dos problemas que mais afeta o trabalhador no ambiente de trabalho, estresse que quando e exagerado acaba afetando tanto saude fisica como mental levando a sociedade obter hipertensao arterial.
Panopticon: a scalable monitoring system
Venue: SAICSIT '10
Year: 2010

Monitoring systems are necessary for the management of anything beyond the smallest networks of computers. While specialised monitoring systems can be deployed to detect specific problems, more general systems are required to detect unexpected issues, and track performance trends. While large fleets of computers are becoming more common, few existing, general monitoring systems have the capability to scale to monitor these very large networks. There is also an absence of systems in the literature that cater for visualisation of monitoring information on a large scale. Scale is an issue in both the design and presentation of large scale monitoring systems. We discuss Panopticon, a monitoring system that we have developed, which can scale to monitor tens of thousands of nodes, using only commodity equipment. In addition, we propose a novel method for visualising monitoring information on a large scale, based on general techniques for visualising massive multi dimensional datasets. The monitoring system is shown to be able to collect information from up to 100 000 nodes. The storage system is able to record and output information from up to 25 000 nodes, and the visualisation is able to simultaneously display all this information for up to 20 000 nodes. Optimisations to our storage system could allow it to scale a little further, but a distributed storage approach combined with intelligent filtering algorithms would be necessary for significant improvements in scalability.
The IASP classification of chronic pain for ICD 11: chronic neuropathic pain
Venue: Pain
Year: 2019

The upcoming 11th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD) of the World Health Organization (WHO) offers a unique opportunity to improve the representation of painful disorders. For this purpose, the International Association for the Study of Pain (IASP) has convened an interdisciplinary task force of pain specialists. Here, we present the case for a reclassification of nervous system lesions or diseases associated with persistent or recurrent pain for =3 months. The new classification lists the most common conditions of peripheral neuropathic pain: trigeminal neuralgia, peripheral nerve injury, painful polyneuropathy, postherpetic neuralgia, and painful radiculopathy. Conditions of central neuropathic pain include pain caused by spinal cord or brain injury, poststroke pain, and pain associated with multiple sclerosis. Diseases not explicitly mentioned in the classification are captured in residual categories of ICD 11. Conditions of chronic neuropathic pain are either insufficiently defined or missing in the current version of the ICD, despite their prevalence and clinical importance. We provide the short definitions of diagnostic entities for which we submitted more detailed content models to the WHO. Definitions and content models were established in collaboration with the Classification Committee of the IASP's Neuropathic Pain Special Interest Group (NeuPSIG) Up to 10% of the general population experience neuropathic pain. The majority of these patients do not receive satisfactory relief with existing treatments. A precise classification of chronic neuropathic pain in ICD 11 is necessary to document this public health need and the therapeutic challenges related to chronic neuropathic pain.
DEVELOPMENT AND FUTURE TRENDS OF IFRS IN ACCOUNTING
Year: 2017

The objective of this research paper is to find out the development and changes in accounting practices across the world in recent times. We witnessed the first step in developing the national accounting and auditing in line with international standards and overcoming transitional economy by enacting legal enforcement, such as Law on accounting. Our Institute (ICAI) is awakening members, holding seminars, workshops for them. What was a trickle in 2007 08, is likely to become a flowing stream, but with a restricted speed. The revenue departments, the company law department and various industry associations, however, are still not enthusiastic supporters. The recent 'Satyam Episode' where the company claimed to be the first to be IFRS compliant, would also come in the way of proper studies because lot of defense mechanism will have to be used in damage control exercise. This paper also investigates whether there is a change in financial accounting system Today, it's apparent that these laws are not efficiently compliant with not only the rapidly growing economic and social requirement, but also sustaining future development focus. Looking back into the past, it's observed that we have gone the long way to shifting to the new accounting system and today we are facing with issue of starting the new phase of the accounting development. The new phase will comprise not only accounting, auditing, asset valuation, financial market regulation, finance, accounting of investment instruments, control issues in whole, but also issues on activity, responsibility, relationships, and legislative regulation of stakeholders.
Manajemen Asuhan Kebidanan Intranatal pada Ny "E" dengan Persalinan Sungsang di RSUD Syekh Yusuf Gowa Tanggal 04 September 2018
Year: 2018

Persalinan normal adalah proses pengeluaran hasil konsepsi dari dalam uterus pada umur kehamilan 37 42 minggu dengan ditandai adanya kontraksi uterus yang menyebabkan terjadinya penipisan dan dilatasi serviks. Terjadi persalinan normal bukan berarti tidak ada komplikasi, tetapi melainkan banyak kemungkinan hal yang bisa terjadi salah satu komplikasinya adalah persalinan sungsang.Penatalaksanaan Asuhan Persalinan Sungsang dengan bokong murni pada Ny "E" yaitu dilakukan dengan pemberiaan asuhan yang sesuai standar operasional prosedur serta melakukan upaya pencegahan komplikasi terutama terjadinya infeksi,perdarahan, robekan jalan lahir yang lebih besar, asfiksia pada bayi serta dilakukannya pemantauan dan Asuhan Manejemen Kebidanan dari kala I sampai kala IV. Kesimpulan dari kasus yaitu diantaranya pendokumentasian dalam bentuk SOAP yang digunakan untuk proses penyelesaian masalah kebidanan telah dilaksanakan pengkajian berupa pemantauan dan analisa data pada Ny "E" dengan persalinan sungsang di RSUD Syekh Yusud Gowa Tahun 2018 yakni dari kala I sampai kala IV, tidak ditemukannya komplikasi pada ibu dan bayi ditandai dengan tanda tanda vital dalam batas normal.
Initial Coin Offerings (ICOs) to Finance New Ventures
Year: 2018

In an initial coin offering (ICO) new ventures raise capital by selling tokens to a crowd of investors. Often, this token is a cryptocurrency, a digital medium of value exchange based on the distributed ledger technology. Both the number of ICOs and the amount of capital raised have exploded since 2017. Despite attracting significant attention from ventures, investors, and policy makers, little is known about the dynamics of ICOs. This initial study therefore assesses the determinants of the amount raised in 423 ICOs. Drawing on signaling theory, the study explores the role of signaling ventures' technological capabilities in ICOs. The results show that technical white papers and high quality source codes increase the amount raised, while patents are not associated with increased amounts of funding. Exploring further determinants of the amount raised, the results indicate that some of the underlying mechanisms in ICOs resemble those found in prior research into entrepreneurial finance, while others are unique to the ICO context. The study's implications are multifold and discussed in detail. Importantly, the results enable investors to more accurately understand crucial determinants of the amount raised (e.g. technical white papers, source code quality, token supply, Ethereum standard) This reduces the considerable uncertainty that investors face when investing in ICOs and enables more informed decision making.
A Mobile Robot for Automated Civil Infrastructure Inspection and Evaluation
Venue: 2018 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)
Year: 2018

Ahstract The objective of civil infrastructure inspection is to evaluate and periodically perform maintenance. This involves properly collecting data on structures, documenting the data, and analyzing the quantitative inspection data over an extended period of operating time, all in order to maintain the structures properly. Recent research on civil infrastructure inspection is mainly based on manual visual inspections, which are often influenced and limited by a professional inspector's knowledge and experience. Thus, the accuracy and reliability of their results are affected. These inspection processes require significant individual labor, which can become quite costly as the inspection areas often require traffic to be limited or evacuation of certain business parking areas while the inspections are performed. In this paper, we present a new development of the autonomous mobile robotic system for automated data collection and inspection. A 4 degree of freedom (DoF) arm is designed and developed then integrated with the robot for efficient image capture using both visual and thermal cameras. The robotic system performs crack detection on the collected data using a state of the art method involving convolutional neural networks (CNN) which is validated on a variety of test images. As inspection results, the robot can output several condition maps of the inspected infrastructure including crack map, thermal map and deterioration map to provide the overall picture of the structure health condition. Our robotic system reduces the overall inspection time compared to the current robotic inspection methods. We further validate our data collection process through showing the correlation between the data collected by each sensor in the system.
A New Strategy for Rotating Machinery Fault Diagnosis Under Varying Speed Conditions Based on Deep Neural Networks and Order Tracking
Venue: 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA)
Year: 2018

Rotating machines are widely used in industry and often work under harsh and varying speed conditions. Fault diagnosis under varying speed conditions is needed to prevent major shutdowns. This paper aims to develop an intelligent rotating machinery fault diagnosis strategy based on deep neural networks (DNNs) and order tracking (OT) The developed strategy can automatically conduct rotating machinery fault diagnosis under both constant and varying speed conditions. Case studies on a rolling element bearing dataset and a fixed shaft gearbox dataset show the superiority in diagnosis accuracy of the proposed strategy over reported approaches.
Simulated Mechanical Properties of Finite Size Graphene Nanoribbons.
Venue: Nanotechnology
Year: 2020

There are many simulation studies of mechanical properties of graphene nanoribbons (GNR) but there is a lack of agreement regarding elastic and plastic behavior. In this paper we aim to analyze mechanical properties of finite size GNR, including elastic modulus and fracture, as a function of ribbon size. We present classical molecular dynamics (MD) simulations for three different empirical potentials which are often used for graphene simulations: AIREBO, REBO scr and REAXFF. Ribbons with and without H passivation at the borders are considered, and the effects of strain rate and different boundaries are also explored. We focus on zig zag GNR, but also include some armchair GNR examples. Results are strongly dependent on the empirical potential employed. Elastic modulus under uniaxial tension can depend on ribbon size, unlike predictions from continuum scale models and from some atomistic simulations, and fracture strain and progress vary significantly amongst the simulated potentials. Because of that, we have also carried out quasi static ab initio simulations for a selected size, and find that the fracture process is not sudden, instead the wave function changes from Bloch states to a strong interaction between localized waves, which decreases continuously with distance. All potentials show good agreement with DFT in the linear elastic regime, but only the REBO scr potential shows reasonable agreement with DFT both in the non linear elastic and fracture regimes. This would allow more reliable simulations of GNRs and GNR based nanostructures, to help interpreting experimental results and for future technological applications.