nils-herrmann/clean_scirepeval huggingface dataset:
Anomalous Hooke's law in disordered graphene

The discovery of graphene, a single monolayer of graphite, has closed the discussion on stability of 2D crystals. Although thermal fluctuations of such crystals tend to destroy the long range order in the system, the crystal can be stabilized by strong anharmonicity effects. This competition is the central issue of the crumpling transition, i.e. a transition between flat and crumpled phases. We show that anharmonicity controlled fluctuations of a graphene membrane around equilibrium flat phase lead to unusual elastic properties. In particular, we demonstrate that stretching \xi$ of a flake of graphene is a nonlinear function of the applied tension at small tension: \xi\propto\sigma^\eta/(2 \eta) and \xi\propto\sigma^\eta/(8 \eta) for clean and strongly disordered graphene, respectively. Conventional linear Hooke's law, \xi\propto\sigma} is realized at sufficiently large tensions: \sigma\gg\sigma_* where \sigma_* depends both on temperature and on the disorder strength.
Optimizing distributed generation parameters through economic feasibility assessment

To meet the fast growth of electricity demand, the traditional network solution tends to expand existing substations, build more new substations, and build transmission lines. Distributed Generation (DG) is posed as an alternative method for the network providers not only to accommodate the load increase and relieve network overload, but also to offer other additional technical and economic benefits. This paper addresses the issue of DG planning and has proposed a technique for optimizing the DG size and location to minimize the overall investment and operational cost of the system. The proposed optimization methodology assesses the compatibility of different generation schemes in terms of their cost factors that can be significantly contributed by a DG. The direct and indirect costs of power supply quality, reliability, energy loss, total power operation, and DG investment are used as key cost components of the DG siting and sizing strategy. The Particle Swarm Optimization (PSO) method is applied to obtain the optimal DG planning solutions. Finally, the proposed approach is tested on a distribution feeder of an Australian power network. Simulation results are presented to illustrate the feasibility and effectiveness of the proposed method.
Precise Correction of Disease Mutations in Induced Pluripotent Stem Cells Derived From Patients With Limb Girdle Muscular Dystrophy.
Venue: Molecular therapy the journal of the American Society of Gene Therapy

Limb girdle muscular dystrophies types 2B (LGMD2B) and 2D (LGMD2D) are degenerative muscle diseases caused by mutations in the dysferlin and alpha sarcoglycan genes, respectively. Using patient derived induced pluripotent stem cells (iPSC) we corrected the dysferlin nonsense mutation c.5713C>T; p.R1905X and the most common alpha sarcoglycan mutation, missense c.229C>T; p.R77C, by single stranded oligonucleotide mediated gene editing, using the CRISPR/Cas9 gene editing system to enhance the frequency of homology directed repair. We demonstrated seamless, allele specific correction at efficiencies of 0.7 1.5% As an alternative, we also carried out precise gene addition strategies for correction of the LGMD2B iPSC by integration of wild type dysferlin cDNA into the H11 safe harbor locus on chromosome 22, using dual integrase cassette exchange (DICE) or TALEN assisted homologous recombination for insertion precise (THRIP) These methods employed TALENs and homologous recombination, and DICE also utilized site specific recombinases. With DICE and THRIP, we obtained targeting efficiencies after selection of ~20% We purified iPSC corrected by all methods and verified rescue of appropriate levels of dysferlin and alpha sarcoglycan protein expression and correct localization, as shown by immunoblot and immunocytochemistry. In summary, we demonstrate for the first time precise correction of LGMD iPSC and validation of expression, opening the possibility of cell therapy utilizing these corrected iPSC.
Combining Single Strand Oligodeoxynucleotides and CRISPR/Cas9 to Correct Gene Mutations in b Thalassemia induced Pluripotent Stem Cells*
Venue: The Journal of Biological Chemistry

b Thalassemia (b Thal) is one of the most common genetic diseases in the world. The generation of patient specific b Thal induced pluripotent stem cells (iPSCs) correction of the disease causing mutations in those cells, and then differentiation into hematopoietic stem cells offers a new therapeutic strategy for this disease. Here, we designed a CRISPR/Cas9 to specifically target the Homo sapiens hemoglobin b (HBB) gene CD41/42( CTTT) mutation. We demonstrated that the combination of single strand oligodeoxynucleotides with CRISPR/Cas9 was capable of correcting the HBB gene CD41/42 mutation in b Thal iPSCs. After applying a correction specific PCR assay to purify the corrected clones followed by sequencing to confirm mutation correction, we verified that the purified clones retained full pluripotency and exhibited normal karyotyping. Additionally, whole exome sequencing showed that the mutation load to the exomes was minimal after CRISPR/Cas9 targeting. Furthermore, the corrected iPSCs were selected for erythroblast differentiation and restored the expression of HBB protein compared with the parental iPSCs. This method provides an efficient and safe strategy to correct the HBB gene mutation in b Thal iPSCs.
Complete Spectrum of CRISPR/Cas9 induced Mutations on HBV cccDNA
Venue: Molecular therapy the journal of the American Society of Gene Therapy

Hepatitis B virus (HBV) causes chronic infections that cannot yet be cured. The virus persists in infected hepatocytes, because covalently closed circular DNA (cccDNA) the template for the transcription of viral RNAs, is stable in nondividing cells. Antiviral therapies with nucleoside analogues inhibit HBV DNA synthesis in capsids in the cytoplasm of infected hepatocytes, but do not destroy nuclear cccDNA. Because over 200 million people are still infected, a cure for chronic hepatitis B (CHB) has become one of the major challenges in antiviral therapy. As a first step toward the development of curative therapies, we previously demonstrated that the CRISPR/Cas9 system can be used to functionally inactivate cccDNA derived from infectious HBV. Moreover, some evidence suggests that certain cytokines might induce an APOBEC mediated cascade leading to the destruction of cccDNA. In this report we investigated whether a combination of the two mechanisms could act synergistically to inactivate cccDNA. Using next generation sequencing (NGS) we determined the complete spectrum of mutations in cccDNA following Cas9 cleavage and repair by nonhomologous end joining (NHEJ) We found that over 90% of HBV DNA was cleaved by Cas9. In addition our results showed that editing of HBV DNA after Cas9 cleavage is at least 15,000 times more efficient that APOBEC mediated cytosine deamination following treatment of infected cells with interferon alpha (IFNa) We also found that a previously used method to detect cytosine deaminated DNA, termed 3D PCR, overestimates the amount and frequency of edited HBV DNA. Taken together, our results demonstrated that the CRISPR/Cas9 system is so far the best method to functionally inactivate HBV cccDNA and provide a cure for CHB.
Exploring the Process of Implementing Healthy Workplace Initiatives: Mapping to Kotter's Leading Change Model
Venue: Journal of occupational and environmental medicine

The aim of this study was to use Kotter's leading change model to explore the implementation of workplace health and wellbeing initiatives.  Qualitative interviews were conducted with 31 workplace representatives with a healthy workplace initiative.  None of the workplaces used a formal change management model when implementing their healthy workplace initiatives. Not all of the steps in Kotter model were considered necessary and the order of the steps was challenged. For example, interviewees perceived that communicating the vision, developing the vision, and creating a guiding coalition were integral parts of the process, although there was less emphasis on the importance of creating a sense of urgency and consolidating change.  Although none of the workplaces reported using a formal organizational change model when implementing their healthy workplace initiatives, there did appear to be perceived merit in using the steps in Kotter's model.
Securing embedded systems and their IPs with digital reconfigurable PUFs
Venue: 2016 26th International Workshop on Power and Timing Modeling, Optimization and Simulation (PATMOS)

In the near future, firmware security will be imperative for the large number of smart embedded devices that are tightly integrated into one's daily lives. In this paper, we present a security scheme for these embedded systems that can provide protection from tempered binaries and the thefts of hardware and software Intellectual Properties (IPs) The key idea is to incorporate digital Physical Unclonable Functions (PUFs) in an authentication mechanism at the machine code level. Each copy of the binary is digitally locked by vendor using the signatures of the individual PUFs. At run time, the binaries are unlocked by the embedded digital PUFs at a low cost to performance and resource utilization. Each digital PUF is unique by initialization using analog PUFs, and at the same time it can be reconfigured with new seeds. The digital reconfigurable PUFs (drPUFs) have much lower risks of side channel attacks and much more combinations of challenge response pairs, while retaining the speed and ease of digital PUF implementation. We demonstrate how the digital PUF is implemented and incorporated into a processor design as well as a software production flow to generate unique firmware binaries that are paired with respective drPUF devices. As a proof of concept we will show the results of the implementation on a Xilinx Spartan 6 Field Programmable Gate Array (FPGA) device.
Novel Binary to Gray Code Converters in QCA with Power Dissipation Analysis
Venue: MUE 2016

Quantum dot cellular automata (QCA) are pledging nanotechnology which has been used widely in digital circuits and systems. Conventional lithography based VLSI model encounter acute challenges of tunneling, variation of doping and short channel issue. In a remarkably fast development of VLSI technology, it is the cardinal of the age to reach a stable model with area and low power consumption. QCA is a promising alternative to complementary metal oxide semiconductor (CMOS) technology with many enticing features such as high speed, low power consumption and higher switching frequency than transistor based technology. The code converters are the basic unit for transformation of data to execute arithmetic processes. In this paper, a novel QCA based 2 bit binary togray, 3 bit binary to gray, and 4 bit binary to gray code converter have been proposed. The proposed design reduces the number of cells, area, and raises switching speed. The energy dissipation by the proposed circuits are evaluated which certifies the prospect of QCA nano circuit presenting as a substitute level for the attainment of reversible circuits. The consistency of the proposed circuits is tested under thermal randomness that reveal the functioning effectiveness of the circuits. The proposed circuits are simulated using QCADesigner and Microwindlite tool which is widely used for simulation and verification.
Noise based spreading in code division multiple access systems for secure communications
Venue: Int. J. Commun. Syst.

Binary spreading sequences or chaotic nonbinary sequences are used in code division multiple access systems. In contrast to those sequences, this paper presents the theory, simulation, and implementation in digital signal processor technology of a code division multiple access system that uses random spreading sequences. The expressions for probability of bit error are derived for the cases when the additive white Gaussian noise and fading are present in the channel. Because the overall transmitted signal is a sum of random signals, the security of signal transmission in this communication system can be enormously increased and will depend on the goodness of the random sequence generator. The developed theory was confirmed by a prototype of the system that was designed in digital signal processor technology. The prototype used spreading sequences that had statistical characteristics very close to the characteristics of theoretical random sequences. The main problem in the system is how to synchronize the received spread sequence with the locally generated sequence. Hence, a mathematical model of the synchronization block for the system has been separately designed and developed. The synchronization procedure has been demonstrated on the basis of application of a periodically repeated pilot sequence.
Sense Effects about Wine Consumption by Means of Self Reports and Neuromarketing Methods

Functional features about wine products are mediating consumer evaluation in combination to brand related elements that taken all together provide a multisensory experience (Ding and Tseng, 2015) Sensory characteristics elicit cognitive and affective responses, which influence consumers evaluation of wine brands and products (Krishna, 2012) Wine is a special kind of product as it cannot be truly evaluated until the product has been tasted. Generally this kind of products are studied in the scientific literatures by means of selfquestionnaires that consumers fill in. However, due the complexity of the wine consumption experience, these kind of techniques are often not enough to enable to understand in a precise and systematic way consumer behavior. For this reason, as in the last decades the application of neuroscientific methods to consumer study showed an increasing trend (Plassmann et al. 2008) there is the need to develop empirical methods that allows to deeply understand consumers responds in order to derive a predictable model of consumer behavior.
Domain Separation Networks
Venue: NIPS

The cost of large scale data collection and annotation often makes the application of machine learning algorithms to new tasks or datasets prohibitively expensive. One approach circumventing this cost is training models on synthetic data where annotations are provided automatically. Despite their appeal, such models often fail to generalize from synthetic to real images, necessitating domain adaptation algorithms to manipulate these models before they can be successfully applied. Existing approaches focus either on mapping representations from one domain to the other, or on learning to extract features that are invariant to the domain from which they were extracted. However, by focusing only on creating a mapping or shared representation between the two domains, they ignore the individual characteristics of each domain. We hypothesize that explicitly modeling what is unique to each domain can improve a model's ability to extract domain invariant features. Inspired by work on private shared component analysis, we explicitly learn to extract image representations that are partitioned into two subspaces: one component which is private to each domain and one which is shared across domains. Our model is trained to not only perform the task we care about in the source domain, but also to use the partitioned representation to reconstruct the images from both domains. Our novel architecture results in a model that outperforms the state of the art on a range of unsupervised domain adaptation scenarios and additionally produces visualizations of the private and shared representations enabling interpretation of the domain adaptation process.
Optimum Hovering Locations with Angular Domain User Separation for Cooperative UAV Networks
Venue: 2016 IEEE Global Communications Conference (GLOBECOM)

Unmanned aerial vehicles (UAVs) can be used as aerial base stations (BSs) to deliver broadband wireless connectivity during temporary events, at hotspot areas, or after disasters that may destroy existing communication infrastructure. Since UAV BSs are low power nodes, their efficient placement is important to reap the maximum capacity and coverage benefits from their deployments. By making use of \emph{UAV mobility} and multi antenna arrays, it is possible to achieve angular domain user separation with lower feedback requirement. In this paper, we propose an approach to identify optimum hovering locations for UAV BSs equipped with multi antenna arrays. We formulate the problem as a signal to noise ratio (SNR) maximization at ground nodes subject to a constraint that interference leakage is lower than a threshold. We consider a scenario with two UAVs each with a single user attached and develop our proposed scheme to achieve: 1) angular domain user separation, and 2) SNR maximization at each user. The performance evaluation of the proposed scheme is carried out through simulations, which show that under interference limited conditions the proposed scheme provides capacity performance better than linear zero force beamforming (LZFBF) without the requirement of full channel state information of all the users.
Artificial neural networks for retrieving absorption and reduced scattering spectra from frequency domain diffuse reflectance spectroscopy at short source detector separation.
Venue: Biomedical optics express

Diffuse reflectance spectroscopy (DRS) based on the frequency domain (FD) technique has been employed to investigate the optical properties of deep tissues such as breast and brain using source to detector separation up to 40 mm. Due to the modeling and system limitations, efficient and precise determination of turbid sample optical properties from the FD diffuse reflectance acquired at a source detector separation (SDS) of around 1 mm has not been demonstrated. In this study, we revealed that at SDS of 1 mm, acquiring FD diffuse reflectance at multiple frequencies is necessary for alleviating the influence of inevitable measurement uncertainty on the optical property recovery accuracy. Furthermore, we developed artificial neural networks (ANNs) trained by Monte Carlo simulation generated databases that were capable of efficiently determining FD reflectance at multiple frequencies. The ANNs could work in conjunction with a least square optimization algorithm to rapidly (within 1 second) accurately (within 10% quantify the sample optical properties from FD reflectance measured at SDS of 1 mm. In addition, we demonstrated that incorporating the steady state apparatus into the FD DRS system with 1 mm SDS would enable obtaining broadband absorption and reduced scattering spectra of turbid samples in the wavelength range from 650 to 1000 nm.
Efecto de la utilizacion de harina de Lens culinaris como extensor en las caracteristicas fisicas y aceptabilidad de una salchicha

En esta investigacion se utilizo harina de Lens culinaris variedad verdina como extensor carnico y se analizo su efecto en las caracteristicas fisicas y aceptabilidad de una salchicha.  Se obtuvo la harina, analizaron las caracteristicas bromatologicas, el indice de absorcion de lipidos (IAL) y la capacidad de retencion de agua (CRA) Se elaboraron las salchichas y anadiendole un 5% de la harina, posteriormente al producto terminado se le evaluaron los parametros bromatologicos, microbiologicos, texturales y sensoriales por triplicado. Analisis estadistico: Se empleo un diseno experimental completamente al azar, realizando tres replicas de la formulacion con harina de L. culinaris y se efectaron analisis de varianza para hallar las diferencias estadisticas.  El contenido de proteina de la harina fue 35,89% mientras que el de fibra 11,82% La capacidad de retencion de agua y el indice de absorcion de lipidos para la harina fueron de 3,87 mL agua/g muestra y 2,01 mL de aceite/g muestra. El producto final presento recuentos microbianos que estuvieron dentro de lo establecido por las Normas Tecnicas Colombianas. La harina influyo positivamente en la aceptabilidad de las salchichas y fue favorable en todos los parametros de textura, lo cual fue similar a lo obtenido en salchichas comerciales.  La harina de L. culinaris representa una alternativa como materia prima no carnica en la elaboracion de productos con interesantes valores proteicos. Estos resultados pueden incentivar la utilizacion de la harina de lenteja de la variedad verdina en productos alimenticios de consumo masivo.
Comparing the Effect of Acupressure and Cryotherapy on the Pain Caused by Removal of Chest Drain Tube in the Elderly Patients Undergoing Open Heart Surgery

Aging has a growing trend in the world. The elderly experience a high incidence of hospitalization and coronary bypass surgery compared with other age groups, and pain is the most common complaint in these patients. This research was conducted to compare the effect of acupressure and cryotherapy on the pain of removing drain tube from the chest of the elderly who have undergone open heart surgery.
Unsupervised learning for robust Bitcoin fraud detection
Venue: 2016 Information Security for South Africa (ISSA)

The rampant absorption of Bitcoin as a cryptographic currency, along with rising cybercrime activities, warrants utilization of anomaly detection to identify potential fraud. Anomaly detection plays a pivotal role in data mining since most outlying points contain crucial information for further investigation. In the financial world which the Bitcoin network is part of by default, anomaly detection amounts to fraud detection. This paper investigates the use of trimmed k means, that is capable of simultaneous clustering of objects and fraud detection in a multivariate setup, to detect fraudulent activity in Bitcoin transactions. The proposed approach detects more fraudulent transactions than similar studies or reports on the same dataset.
A survey on the state of healthcare upcoding fraud analysis and detection
Venue: Health Services and Outcomes Research Methodology

From its infancy in the 1910s, healthcare group insurance continues to increase, creating a consistently rising burden on the government and taxpayers. The growing number of people enrolled in healthcare programs such as Medicare, along with the enormous volume of money in the healthcare industry, increases the appeal for and risk of fraudulent activities. One such fraud, known as upcoding, is a means by which a provider can obtain additional reimbursement by coding a certain provided service as a more expensive service than what was actually performed. With the proliferation of data mining techniques and the recent and continued availability of public healthcare data, the application of these techniques towards fraud detection, using this increasing cache of data, has the potential to greatly reduce healthcare costs through a more robust detection of upcoding fraud. Presently, there is a sizable body of healthcare fraud detection research available but upcoding fraud studies are limited. Audit data can be difficult to obtain, limiting the usefulness of supervised learning; therefore, other data mining techniques, such as unsupervised learning, must be explored using mostly unlabeled records in order to detect upcoding fraud. This paper is specific to reviewing upcoding fraud analysis and detection research providing an overview of healthcare, upcoding, and a review of the current data mining techniques used therein.