nils-herrmann/clean_scirepeval huggingface dataset:
Advances in shrub willow crops for bioenergy, renewable products, and environmental benefits.

Short rotation coppice systems like shrub willow are projected to be an important source of biomass in the United States for the production of bioenergy, biofuels, and renewable bio based products, with the potential for auxiliary environmental benefits and multifunctional systems. Almost three decades of research has focused on the development of shrub willow crops for biomass and ecosystem services. The current expansion of willow in New York State (about 500 ha) for the production of renewable power and heat has been possible because of incentive programs offered by the federal government, commitments by end users, the development of reliable harvesting systems, and extension services offered to growers. Improvements in the economics of the system are expected as willow production expands further, which should help lower establishment costs, enhance crop management options and increase efficiencies in harvesting and logistics. As a result, deploying willow in multifunctional value added systems provides opportunities for both potential producers and end users to learn about the system and the quality of the biomass feedstock, which in turn will help overcome barriers to expansion.
Boundary flow on end grafted PEG brushes.
Venue: Soft matter

We investigated the boundary conditions for flow of a Newtonian liquid over soft interfaces by measuring hydrodynamic drainage forces with colloid probe atomic force microscopy in a viscous liquid. The investigated soft surfaces are end grafted brushes of thiolated poly(ethylene glycol) (PEG) of molecular weight 1k and 30k, grafted to gold. The conditions for brush preparation were optimized as to meet the stringent conditions required for surface force measurements, namely reproducible and uniform surface composition and roughness. The fit of a slip model to the experimental data returned a slip length of 16 nm on the PEG 1k brush and 25 nm on the PEG30k brush. The slip length can be interpreted as a penetration length, which accounts for flow within the top half of the brush for the PEG30k case, and within the brush and surface roughness for the PEG1k case. These findings confirm earlier simulation studies by our group on the flow of liquids within polymer brushes.
Enhanced attachment of human mesenchymal stem cells on nanograined titania surfaces

Surface nanostructures have shown potential as biomaterials, in tissue engineering and regenerative medicine devices since they have been shown to enhance cellular function by modulating cell surface interactions in a controlled manner. This work studies human stem cell behavior on titanium dioxide (TiO2) nanotubes that were fabricated on nano grained (NG) and coarse grained (CG) substrates. The NG substrates were derived by surface mechanical attrition treatment (SMAT) which has the advantage of being simple to implement. The TiO2 nanotube layer formed on the SMATed titanium (Ti) is thicker and has an inner diameter (70 nm) greater than a comparable layer observed on an untreated (40 nm) substrate. The results illustrate that a NG Ti layer favors the growth of TiO2 nanotubes; presumably due to the high density of grain boundaries and dislocations. An increase in adhesion of human mesenchymal stem cells (hMSCs) in short term culture was observed on the TiO2 nanotubes grown on the NG substrate compared to those grown on the CG substrate, which we attribute to the various roughness and hydrophilicity differences between the two surfaces. Additionally, higher specific strengths of the TiO2 nanotubes may also be achieved by taking advantage of the Ti grain changes on the substrate and the subsequent growth of the nanotubes. Furthermore, structural deformations at the nanoscale can be exploited to manufacture advanced biomaterial surfaces that are designed to enable improved stem cell attachment.
Fusing Deep Convolutional Networks for Large Scale Visual Concept Classification
Venue: 2016 IEEE Second International Conference on Multimedia Big Data (BigMM)

Deep learning architectures are showing great promise in various computer vision domains including image classification, object detection, event detection and action recognition. In this study, we investigate various aspects of convolutional neural networks (CNNs) from the big data perspective. We analyze recent studies and different network architectures both in terms of running time and accuracy. We present extensive empirical information along with best practices for big data practitioners. Using these best practices we propose efficient fusion mechanisms both for single and multiple network models. We present state of the art results on benchmark datasets while keeping computational costs at a lower level. Another contribution of our paper is that these state of the art results can be reached without using extensive data augmentation techniques.
Deep Contextual Networks for Neuronal Structure Segmentation
Venue: AAAI

The goal of connectomics is to manifest the interconnections of neural system with the Electron Microscopy (EM) images. However, the formidable size of EM image data renders human annotation impractical, as it may take decades to fulfill the whole job. An alternative way to reconstruct the connectome can be attained with the computerized scheme that can automatically segment the neuronal structures. The segmentation of EM images is very challenging as the depicted structures can be very diverse. To address this difficult problem, a deep contextual network is proposed here by leveraging multi level contextual information from the deep hierarchical structure to achieve better segmentation performance. To further improve the robustness against the vanishing gradients and strengthen the capability of the back propagation of gradient flow, auxiliary classifiers are incorporated in the architecture of our deep neural network. It will be shown that our method can effectively parse the semantic meaning from the images with the underlying neural network and accurately delineate the structural boundaries with the reference of low level contextual cues. Experimental results on the benchmark dataset of 2012 ISBI segmentation challenge of neuronal structures suggest that the proposed method can outperform the state of the art methods by a large margin with respect to different evaluation measurements. Our method can potentially facilitate the automatic connectome analysis from EM images with less human intervention effort.
Crisis Management on the Basis of the Marketing Approach for Development of Innovative Potential of the Organization

This article describes the problem of efficiency of functioning of the organization in modern conditions of dynamic external environment. Modern external environment characterized by financial instability, lower incomes, economic constraints in relation to Russia, as well as constantly changing consumer preferences caused by other factors. In such circumstances, it becomes important domestic market. Close attention should be paid to the innovative capacity of organizations in the predominant direction of innovative development of the Russian economy as a whole to deal with these unstable conditions. Describes the factors the marketing environment the organization's operations and their impact on its activities. The authors propose a methodology of determining the stability of the organization based on the analysis of environmental factors. This method may be supplemented in the study and to identify other factors of importance in the organization. The authors also proposed the algorithm of marketing management organization based on the assessment of the stability of the organization at this point in time and compare it with the desired level of stability. If defined an unsustainable situation, it is necessary to take measures of administrative influence, which is based in particular on innovation management in organization in order to achieve the desired level of stability.
Perception of risk and communication among conventional and complementary health care providers involving cancer patients' use of complementary therapies: a literature review
Venue: BMC Complementary and Alternative Medicine

BackgroundCommunication between different health care providers (conventional and complementary) and cancer patients about their use of complementary therapies affects the health and safety of the patients. The aim of this study was to examine the qualitative research literature on the perception of and communication about the risk of complementary therapies between different health care providers and cancer patients.MethodsSystematic searches in six medical databases covering literature from 2000 to 2015 were performed. The studies were accessed according to the level of evidence and summarized into different risk situations. Qualitative content analysis was used to analyze the text data, and the codes were defined before and during the data analysis.ResultsTwenty nine papers were included in the primary analysis and five main themes were identified and discussed. The main risk situations identified were 1. Differences in treatment concepts and philosophical values among complementary and conventional health care providers. 2. Adverse effects from complementary products and herbs due to their contamination/toxicity and interactions with conventional cancer treatment. 3. Health care physicians and oncologists find it difficult to recommend many complementary modalities due to the lack of scientific evidence for their effect. 4. Lack of knowledge and information about complementary and conventional cancer treatments among different health care providers.ConclusionThe risk of consuming herbs and products containing high level of toxins is a considerable threat to patient safety (direct risk) At the same time, the lack of scientific evidence of effect for many complementary therapies and differences in treatment philosophy among complementary and conventional health care providers potentially hinder effective communication about these threats with mutual patients (indirect risk) As such, indirect risk may pose an additional risk to patients who want to combine complementary therapies with conventional treatment in cancer care. Health care providers who care for cancer patients should be aware of these risks.
Spatial modulation orthogonal frequency division multiplexing with subcarrier index modulation for V2X communications
Venue: 2016 International Conference on Computing, Networking and Communications (ICNC)

Spatial modulation orthogonal frequency division multiplexing (SM OFDM) is a novel OFDM technique which conveys additional information by active antenna indices of subcarriers, and thus achieves enhanced data rate and robustness against inter antenna interference within subcarriers. Index modulated OFDM (IM OFDM) applies the concept of index modulation to subcarrier domain and is shown to have reduced inter carrier interference (ICI) In this paper, we propose SM OFDM with subcarrier index modulation (ISM OFDM) for vehicle to vehicle and vehicle to infrastructure (V2X) to mitigate the ICI caused by Doppler effects. The idea is to to embed subcarrier index modulation to SM OFDM and conduct SM at the active subcarriers independently. It is shown via computer simulations that the proposed scheme achieves better bit error rate (BER) performance than classical SM OFDM systems under V2X channel models.
Orthogonal frequency division multiplexing linear frequency modulation signal design with optimised pulse compression property of spatial synthesised signals

Orthogonal frequency division multiplexing (OFDM) linear frequency modulation (LFM) waveform is widely studied due to its application potentials in multiple input multiple output (MIMO) radar, but its effective design is still a challenge. Considering the critical role, the pulse compression property of spatial synthesised signals plays in MIMO radar, a detailed analysis is made using OFDM LFM signals, resulting in the radical reasons for the high grating sidelobes. Then, a joint optimisation method for OFDM LFM signal design based on genetic algorithm and sequential quadratic programming is proposed to degrade the sidelobe level dramatically. Furthermore, to nullify the grating sidelobes thoroughly, a modification is performed through optimising the relaxed frequency steps of the OFDM LFM waveform, which involves a balance between sidelobe property and orthogonality. Numerical results validate the theoretic analysis and show the superior performance of the designed OFDM LFM waveforms in pulse compression properties of spatial synthesised signals.
Experimental and numerical analysis of drop weight low velocity impact tests on hybrid titanium composite laminates

An experimental and numerical study on low velocity impact responses on [Ti/0/90] s hybrid titanium composite laminates (HTCLs) is presented. Different energy levels from 10 to 40 J are investigated using a drop weight instrument and post impact inspection. An explicit finite element implementation provides a detailed analysis of impact response in composite and titanium layers, respectively. It accounts for interfacial debonding, progressive failure in composite plies and elastic plastic deformation in titanium. The main failure modes are experimentally and numerically found to be debonding between titanium and composite, matrix cracking and interlaminar delamination. The principal energy absorbing mechanism is plastic dissipation of the two titanium sheets. The low cost numerical model is able to effectively predict the overall impact response and major failure modes with good accuracy.
Drilling of Hybrid Titanium Composite Laminate (HTCL) with Electrical Discharge Machining
Venue: Materials

An experimental investigation was conducted to determine the application of die sinker electrical discharge machining (EDM) as it applies to a hybrid titanium thermoplastic composite laminate material. Holes were drilled using a die sinker EDM. The effects of peak current, pulse time, and percent on time on machinability of hybrid titanium composite material were evaluated in terms of material removal rate (MRR) tool wear rate, and cut quality. Experimental models relating each process response to the input parameters were developed and optimum operating conditions with a short cutting time, achieving the highest workpiece MRR, with very little tool wear were determined to occur at a peak current value of 8.60 A, a percent on time of 36.12% and a pulse time of 258 microseconds. After observing data acquired from experimentation, it was determined that while use of EDM is possible, for desirable quality it is not fast enough for industrial application.
A computational investigation of failure modes in hybrid titanium composite laminates

High strength, low weight Fibre Metal Laminates (FMLs) are increasingly finding use in military and commercial aircraft applications by combining benefits of both fibre reinforced composite and metal components such as fracture toughness and fatigue resistance. Glass fibre reinforced composite laminates combined with aluminium (GLARE) was recently selected for the upper fuselage skin structure of Airbus A380 aircraft. Hybrid Titanium Composite Laminates (HTCLs) made from thin titanium sheets and carbon Fibre Reinforced Polymer (FRP) are more suitable in high strength environments at elevated temperatures and may therefore be used in future aerospace applications. Currently, the combination of titanium and FRP is mainly applied to surgical implants or biomedical devices. In order to improve design and performance of FMLs, it is essential to understand their failure mechanisms under various loading conditions. Major failure modes in composite laminates are delamination, matrix cracking and fibre fracture. Delamination can be initiated by stress concentrations at free edges, interfacial voids or transverse matrix cracks. The latter is referred to as Matrix Cracking Induced Delamination (MCID) An additional critical failure mode in FMLs is debonding between composite and metal sheets. These failure modes cause stress redistribution and can lead to complete loss of load carrying capability resulting in structural collapse. Virtual testing of FMLs can not only reduce physical testing, it also offers cost effective design flexibility and certification. FML structures can be virtually optimised to suit specific applications before time consuming and expensive manufacturing. Therefore, effective and accurate models are required to describe failure mechanisms and their interaction. The Phantom Node Method (PNM) is a numerical concept to simulate failure initiation and evolution in heterogeneous materials such as FMLs within the Finite Element Method (FEM) It includes the well established Cohesive Zone Method (CZM) to approximate nonlinear fracture processes in interfaces or cracks. Elemental locality and the use of standard shape functions make PNM conceptually simpler and hence easier to implement and modify compared to similar enrichment methods such as X FEM. This research project aims to develop, validate and use computational methods within FEM in order to investigate failure modes in composite laminates and HTCLs. Thereby, standard simulation tools as well as novel conceptual methods such as PNM are to be applied. Experimental investigations provide important modelling properties as well as data to validate numerical results. A novel Top Surface Analysis (TSA) technique using Digital Image Correlation in a
3D U Net: Learning Dense Volumetric Segmentation from Sparse Annotation
Venue: MICCAI

This paper introduces a network for volumetric segmentation that learns from sparsely annotated volumetric images. We outline two attractive use cases of this method: (1) In a semi automated setup, the user annotates some slices in the volume to be segmented. The network learns from these sparse annotations and provides a dense 3D segmentation. (2) In a fully automated setup, we assume that a representative, sparsely annotated training set exists. Trained on this data set, the network densely segments new volumetric images. The proposed network extends the previous u net architecture from Ronneberger et al. by replacing all 2D operations with their 3D counterparts. The implementation performs on the fly elastic deformations for efficient data augmentation during training. It is trained end to end from scratch, i.e. no pre trained network is required. We test the performance of the proposed method on a complex, highly variable 3D structure, the Xenopus kidney, and achieve good results for both use cases.
Disruption of adolescents' circadian clock: The vicious circle of media use, exposure to light at night, sleep loss and risk behaviors
Venue: Journal of Physiology Paris

Although sleep is a key element in adolescent development, teens are spending increasing amounts of time online with health risks related to excessive use of electronic media (computers, smartphones, tablets, consoles. negatively associated with daytime functioning and sleep outcomes. Adolescent sleep becomes irregular, shortened and delayed in relation with later sleep onset and early waking time due to early school starting times on weekdays which results in rhythm desynchronization and sleep loss. In addition, exposure of adolescents to the numerous electronic devices prior to bedtime has become a great concern because LEDs emit much more blue light than white incandescent bulbs and compact fluorescent bulbs and have therefore a greater impact on the biological clock. A large number of adolescents move to evening chronotype and experience a misalignment between biological and social rhythms which, added to sleep loss, results in e.g. fatigue, daytime sleepiness, behavioral problems and poor academic achievement. This paper on adolescent circadian disruption will review the sensitivity of adolescents to light including LEDs with the effects on the circadian system, the crosstalk between the clock and the pineal gland, the role of melatonin, and the behavior of some adolescents(media use, alcohol consumption, binge drinking, smoking habits, stimulant use. Lastly, some practical recommendations and perspectives are put forward. The permanent social jet lag resulting in clock misalignment experienced by a number of adolescents should be considered as a matter of public health.
Stable actions and central extensions

A probability measure preserving action of a countable group is called stable if its transformation groupoid absorbs the ergodic hyperfinite equivalence relation of type \text {II}}_1$$II1 under direct product. We show that for a countable group G and its central subgroup C, if G C has a stable action, then so does G. Combining a previous result of the author, we obtain a characterization of a central extension having a stable action.
Effect of increasing levels of glycerin on growth rate, carcass traits and liver gluconeogenesis in young bulls

This study aimed to evaluate performance, carcass traits, glycerol kinase 1 (GK1) and cytoplasmatic phosphoenolpyruvate carboxykinase (PCK1) gene expression, and glycerol kinase activity in liver of young bulls receiving different levels of crude glycerin. Forty four crossbred young bulls (initial body weight of 368 4.2 kg) were used in a completely randomized design, with four treatments and 11 replicates. The experiment period lasted 84 days, preceded by an adaptation period of 28 days. The basal diet was composed of corn silage (300 g/kg) and concentrate (700 g/kg) containing corn and soybean. The experimental treatments were as follows: without glycerin or including 60, 120 or 180 g/kg of crude glycerin in the diet. Blood samples were collected on the last day of the experiment period to evaluate biochemical parameters. After slaughter, carcass traits were measured and liver samples were collected to analyze gene expression and glycerol kinase activity. There was no effect (P 0.21) of glycerin on glucose blood concentrations. However, liver glycerol kinase activity was greater (P 0.17) performance and most of the carcass traits. However, there was a greater (P 0.02) marbling score in the carcass of animals fed 120 and 180 g/kg of crude glycerin. In conclusion, the use of glycerin at a level of up to 180 g/kg is recommended in diets of feedlot beef cattle, and it increases liver glycerol kinase activity, feed efficiency and beef marbling.