Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection from space of a reduction in anthropogenic emissions of nitrogen oxides during the Chinese economic downturn

Abstract. Rapid economic and industrial development in China and relatively weak emission controls have resulted in significant increases in emissions of nitrogen oxides (NO x ) in recent years, with the exception of late 2008 to mid 2009 when the economic downturn led to emission reductions detectable from space. Here vertical column densities (VCDs) of tropospheric NO 2 retrieved from satellite observations by SCIAMACHY, GOME-2 and OMI (both by KNMI and by NASA) are used to evaluate changes in emissions of NO x from October 2004 to February 2010 identifying impacts of the economic downturn. Data over polluted regions of Northern East China suggest an increase of 27–33 % in 12-month mean VCD of NO 2 prior to the downturn, consistent with an increase of 49 % in thermal power generation (TPG) reflecting the economic growth. More detailed analysis is used to quantify changes in emissions of NO x in January over the period 2005–2010 when the effect of the downturn was most evident. The GEOS-Chem model is employed to evaluate the effect of changes in chemistry and meteorology on VCD of NO 2 . This analysis indicates that emissions decreased by 20 % from January 2008 to January 2009, close to the reduction of 18 % in TPG that occurred over the same interval. A combination of three independent approaches indicates that the economic downturn was responsible for a reduction in emissions by 9–11 % in January 2009 with an additional decrease of 10 % attributed to the slow-down in industrial activity associated with the coincident celebration of the Chinese New Year; errors in the estimate are most likely less than 3.4 %.
Relation Guided Bootstrapping of Semantic Lexicons

State-of-the-art bootstrapping systems rely on expert-crafted semantic constraints such as negative categories to reduce semantic drift. Unfortunately, their use introduces a substantial amount of supervised knowledge. We present the Relation Guided Bootstrapping (RGB) algorithm, which simultaneously extracts lexicons and open relationships to guide lexicon growth and reduce semantic drift. This removes the necessity for manually crafting category and relationship constraints, and manually generating negative categories.
Properties of Sintered Mg Alloys for Biomedical Applications

In addition to the use as light weight construction material, magnesium alloys are also very suitable for future orthopaedic and traumatology applications. Common permanent implant materials such as titanium or stainless steel still suffer from stress shielding problems, causing bone resorption and implant loosening. In contrast, magnesium alloys provide elastic moduli and strengths matching those of cortical bone. In order to support osseointegration and vascularisation, an open porous surface structure of an Mg-implant is advantageous. The powder metallurgical processing route of Mg-alloys enables the generation of such parts. Powder blends with different sintering behaviour were produced via mixing pure Mg-powder with different Ca containing master alloy powders (MAP). As a result, sintering of these Mg alloy powders and blends became feasible. Sintered parts were investigated in view of shrinkage, porosity, grain size using SEM, EDX and XRD. In addition, compression tests were performed revealing ultimate compression strength up to 328 MPa, plastic compressibility of 22 % and compressive yield strength up to 90 MPa. Hence, the PM-route enables the production of parts with mechanical properties matching those of cortical bone.
Demonstration abstract: A lightweight, portable device with integrated USB-Host support for reprogramming wireless sensor nodes

Node reprogramming serves as an important service to support post-deployment code management and maintenance for unattended wireless sensor networks or autonomous robotics applications. We present a prototype of a design framework called SHAMPU, a Single chip Host for Autonomous Mote Programming over USB. A SHAMPU device is portable and can be paired with a sensor node for post-deployment reprogramming that is OS independent. Moreover, it is small, lightweight and energy efficient. In the demo, we will present two scenarios, in which SHAMPU-paired Telosbs are integrated with a mobile flying robot and locomotives for local autonomous reprogramming by the flying robot and for network reprogramming with code dissemination via the data links on the tracks, respectively.
4D offline PET-based treatment verification in scanned ion beam therapy: a phantom study

At the Heidelberg Ion-Beam Therapy Center, patient irradiation with scanned proton and carbon ion beams is verified by offline positron emission tomography (PET) imaging: the β+ ? >-activity measured within the patient is compared to a prediction calculated on the basis of the treatment planning data in order to identify potential delivery errors. Currently, this monitoring technique is limited to the treatment of static target structures. However, intra-fractional organ motion imposes considerable additional challenges to scanned ion beam radiotherapy. In this work, the feasibility and potential of time-resolved (4D) offline PET-based treatment verification with a commercial full-ring PET/CT (x-ray computed tomography) device are investigated for the first time, based on an experimental campaign with moving phantoms. Motion was monitored during the gated beam delivery as well as the subsequent PET acquisition and was taken into account in the corresponding 4D Monte-Carlo simulations and data evaluation. Under the given experimental conditions, millimeter agreement between the prediction and measurement was found. Dosimetric consequences due to the phantom motion could be reliably identified. The agreement between PET measurement and prediction in the presence of motion was found to be similar as in static reference measurements, thus demonstrating the potential of 4D PET-based treatment verification for future clinical applications.
In Vitro Cytotoxicity Assessment of an Orthodontic Composite Containing Titanium-dioxide Nano-particles

Background and aims. Incorporation of nano-particles to orthodontic bonding systems has been considered to prevent enamel demineralization around appliances. This study investigated cytotoxicity of Transbond XT adhesive containing 1 wt% titanium dioxide (TiO2) nano-particles. Materials and methods. Ten composite disks were prepared from each of the conventional and TiO2-containg composites and aged for 1, 3, 5, 7 and 14 days in Dulbecco’s Modified Eagle’s Medium (DMEM). The extracts were obtained and exposed to culture media of human gingival fibroblasts (HGF) and mouse L929 fibroblasts. Cell viability was measured using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Results. Both adhesives were moderately toxic for HGF cells on the first day of the experiment, but the TiO2-containing adhesive produced significantly lower toxicity than the pure adhesive (P<0.05). No significant differences were found in cell viability percentages between the two groups on the other days (P>0.05). There was a significant reduction in cell toxicity with increasing pre-incubation time (P<0.001). L929 cells showed similar toxicity trends, but lower sensitivity to detect cytotoxicity of dental composites. Conclusion. The orthodontic adhesive containing TiO2 nano-particles indicated comparable or even lower toxicity than its nano-particle-free counterpart, indicating that incorporation of 1 wt% TiO2 nano-particles to the composite structure does not result in additional health hazards compared to that occurring with the pure adhesive.
A novel comprehensive wave-form MS data processing method

MOTIVATION Mass spectrometry (MS) can generate high-throughput protein profiles for biomedical research to discover biologically related protein patterns/biomarkers. The noisy functional MS data collected by current technologies, however, require consistent, sensitive and robust data-processing techniques for successful biomedical application. Therefore, it is important to detect features precisely for each spectrum, quantify them well and assign a unique label to features from the same protein/peptide across spectra. RESULTS In this article, we propose a new comprehensive MS data preprocessing package, Wave-spec, which includes several novel algorithms. It can overcome several conventional difficulties. Wave-spec can be applied to multiple types of MS data generated with different MS technologies. Results from this new package were evaluated and compared to several existing approaches based on a MALDI-TOF MS dataset. AVAILABILITY An example of MATLAB scripts used to implement the methods described in this article, along with Supplementary Figures, can be found at http://www.vicc. org/biostatistics/supp.php. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Impact of Residual Transmit RF Impairments on Training-Based MIMO Systems

Radio-frequency (RF) impairments, which intimately exist in wireless communication systems, can severely limit the performance of multiple-input-multiple-output (MIMO) systems. Although we can resort to compensation schemes to mitigate some of these impairments, a certain amount of residual impairments always persists. In this paper, we consider a training-based point-to-point MIMO system with residual transmit RF impairments (RTRI) using spatial multiplexing transmission. Specifically, we derive a new linear channel estimator for the proposed model, and show that RTRI create an estimation error floor in the high signal-to-noise ratio (SNR) regime. Moreover, we derive closed-form expressions for the signal-to-noise-plus-interference ratio (SINR) distributions, along with analytical expressions for the ergodic achievable rates of zero-forcing, maximum ratio combining, and minimum mean-squared error receivers, respectively. In addition, we optimize the ergodic achievable rates with respect to the training sequence length and demonstrate that finite dimensional systems with RTRI generally require more training at high SNRs than those with ideal hardware. Finally, we extend our analysis to large-scale MIMO configurations, and derive deterministic equivalents of the ergodic achievable rates. It is shown that, by deploying large receive antenna arrays, the extra training requirements due to RTRI can be eliminated. In fact, with a sufficiently large number of receive antennas, systems with RTRI may even need less training than systems with ideal hardware.
A virtual class calculus

Virtual classes are class-valued attributes of objects. Like virtual methods, virtual classes are defined in an object's class and may be redefined within subclasses. They resemble inner classes, which are also defined within a class, but virtual classes are accessed through object instances, not as static components of a class. When used as types, virtual classes depend upon object identity -- each object instance introduces a new family of virtual class types. Virtual classes support large-scale program composition techniques, including higher-order hierarchies and family polymorphism. The original definition of virtual classes in BETA left open the question of static type safety, since some type errors were not caught until runtime. Later the languages Caesar and gbeta have used a more strict static analysis in order to ensure static type safety. However, the existence of a sound, statically typed model for virtual classes has been a long-standing open question. This paper presents a virtual class calculus, VC, that captures the essence of virtual classes in these full-fledged programming languages. The key contributions of the paper are a formalization of the dynamic and static semantics of VC and a proof of the soundness of VC.
Fecal glucocorticoid metabolite analysis as an indicator of stress during translocation and acclimation in an endangered large mammal, the Grevy's zebra

Fecal glucocorticoid metabolite (FGM) analysis provides a non‐invasive method for studying the physiological response of wildlife to a variety of stressors and is a ground‐breaking monitoring technique in wildlife management and conservation. The conservation benefits of successful wildlife translocation restocking efforts are significant but understandably stressful for the animals being captured, removed from familiar habitat, held in captivity in many cases and subsequently released into an unfamiliar environment. It is imperative that we identify non‐invasive methods for evaluating stress in translocated animals, especially in endangered species. Twenty Grevy's zebra Equus grevyi were translocated to Meru National Park as part of a Kenya Wildlife Service re‐population initiative. FGMs were monitored from the time of capture, during captivity and post‐release as an indicator of the stress of translocation and acclimation to the new environment. FGMs from representative non‐translocated zebra were used as a further control. When held in pens at Meru Park 3–4 and 5–6 weeks after capture, the zebra had higher FGMs (25.1±1.2 and 23.4±1.3 ng g−1) than either at the time of capture (14.6±2.1 ng g−1) or non‐translocated controls (16.2±1.2 ng g−1). This suggests that the stress of captivity elevated FGMs. FGM concentrations returned to pre‐capture concentrations c. 11–18 weeks after the zebra were released into Meru Park. The return of FGM concentrations to baseline suggests successful acclimation to the new environment. This study supports the use of FGM analysis as an assessment technique in wildlife management projects involving the movement of endangered large mammals with application for monitoring stress in a wide array of conservation projects involving translocation, reintroduction and rehabilitation.
Modelling of transport phenomena in crystal growth

Introduction to crystal growth processes from the melt Back-diffusion phenomenon during the crystal growth by the Bridgman method Numerical stimulation of crystal growth by the vertical Bridgman method Numerical modelling of crystal growth of binary compound semiconductors Crystal growth by travelling heater method in microgravity Convective instability in Czochralski crystal growth system Effect of magnetic field in Czochralski silicon crystal growth Modelling of Czochralski crystal growth in turbulent flow regime Transport phenomena during growth of superconducting materials by Czochralski method Modeling of high pressure liquid-encapsulated Czochralski crystal growth processes.
Recurrent Polynomial Network for Dialogue State Tracking with Mismatched Semantic Parsers

Recently, constrained Markov Bayesian polynomial (CMBP) has been proposed as a data-driven rule-based model for dialog state tracking (DST). CMBP is an approach to bridge rule-based models and statistical models. Recurrent Polynomial Network (RPN) is a recent statistical framework taking advantages of rulebased models and can achieve state-ofthe-art performance on the data corpora of DSTC-3, outperforming all submitted trackers in DSTC-3 including RNN. It is widely acknowledged that SLU’s reliability influences tracker’s performance greatly, especially in cases where the training SLU is poorly matched to the testing SLU. In this paper, this effect is analyzed in detail for RPN. Experiments show that RPN’s tracking result is consistently the best compared to rule-based and statistical models investigated on different SLUs including mismatched ones and demonstrate RPN’s is very robust to mismatched semantic parsers.
The Divided Software Life Cycle of ERP Packages

The traditional information system life cycle (SLC) focuses on the activities performed by a company developing, implementing and maintaining software for its own internal use. Enterprise resource planning (ERP) software packages change the SLC in several important ways. This paper presents an extension of the SLC model for ERP packages. The ‘divided software life cycle’ (DSLC) model features an equal emphasis on the activities performed by the ERP adopting company and the ERP vendor.
The influence of disorder on deformations in semiflexible networks

We present a model that assesses the different elastic responses of a semiflexible network, which either (i) is constrained to deform in an affine way or (ii) is permitted to thermally fluctuate and deviate from affine response. The thermal, non-affine response of the network is achieved using a Metropolis Monte Carlo algorithm with dynamic step size. We find that non-affine deformations soften the network dramatically at low strains and make the eventual nonlinear strain stiffening far more pronounced. We show that the effect of these non-affine deformations are very sensitive to the degree variation in the lengths of filaments connecting cross-links. Where there is high variation, non-affine deformations allow internal stresses to relax, giving rise to a smaller range of tensile forces in filaments and a dramatic reduction of network stiffness. This highlights that non-affine deformations are crucial in small strain response of stiff polymer networks.
Studies on subjects design in equipment virtual maintenance training system

Firstly, the importance of subjects design in virtual maintenance training system is emphasized, and then the main factors that affect the design for subjects in virtual maintenance training are analyzed. Secondly, the detailed design process of virtual maintenance training subjects is illustrated based on the analysis of training requirements. Finally, this process is applied in the design of a concrete virtual training subject which validated the reasonability and feasibility of the process.
Nested Images

A nested image is a form of artistic expression in which one or more secondary figures are embedded within a primary figure one by one. Contours of the primary figure, especially the contours of its inner holes, are used to portray a secondary figure. The secondary figure is totally inside the primary figure, and it would use some inner holes of primary figure as part of itself, which would produce an artistic effect. Here, we present a system for creating such images. It relies on the experience of human perception to minimize the difference between embedded inner figure and primary outer figure. Our system detects the enclosed outer contour of the figure to be nested, and then finds a place in the outer figure to embed it, together with a suitable transformation for doing so, by optimizing an energy based on the distance of contours. Morphing is done by an iterative approach, which warps the corresponding contours of the inner figure and the holes of the outer figure to an appropriate position. We show various nested images generated by our
Peri-operative platelet function testing: The potential for reducing ischaemic and bleeding risks

Summary The pivotal role of platelet activation and reactivity during atherothrombotic event occurrence associated with acute coronary syndromes (ACS) or percutaneous coronary interventions (PCI) is well established. Numerous translational research studies have established a threshold level of platelet reactivity during dual antiplatelet therapy above which a higher risk for ischaemic event occurrence has been observed. The clinical validity of these threshold values in reducing ischemic event occurrence with modified P2Y12 receptor therapy is currently under investigation in large-scale clinical trials. The association between on-treatment platelet reactivity measured by an ex vivo assay and the occurrence of bleeding events is less established. Currently, there is limited evidence of an association between platelet inhibition and coronary artery bypass grafting (CABG)- related bleeding in patients on clopidogrel therapy indicating that preoperative platelet function monitoring may guide both the timing of elective CABG and the administration of blood products in patients needing surgery. However, in the absence of a large-scale prospective clinical trial, routine platelet function monitoring and modification of timing of surgery based on platelet function monitoring are currently not recommended.
A fisheye distortion correction algorithm optimized for hardware implementations

This paper presents a universal algorithm for correcting distortion in images obtained with fisheye lenses. We analyze and optimize the algorithm for implementation on hardware platforms such as Field Programmable Gate Arrays (FPGAs). A fully pipelined architecture, implemented in an FPGA, is capable of processing full HD images at 30 frames per second. Furthermore the proposed algorithmic modifications introduce very little error in fixed point arithmetic pixel coordinate computations. When compared to double precision results, most coordinates have an error of less than 0.5 pixel.
Test-Pattern Selection for Screening Small-Delay Defects in Very-Deep Submicrometer Integrated Circuits

Timing-related defects are major contributors to test escapes and in-field reliability problems for very-deep submicrometer integrated circuits. Small delay variations induced by crosstalk, process variations, power-supply noise, as well as resistive opens and shorts can potentially cause timing failures in a design, thereby leading to quality and reliability concerns. We present a test-grading technique that uses the method of output deviations for screening small-delay defects (SDDs). A new gate-delay defect probability measure is defined to model delay variations for nanometer technologies. The proposed technique intelligently selects the best set of patterns for SDD detection from an n-detect pattern set generated using timing-unaware automatic test-pattern generation (ATPG). It offers significantly lower computational complexity and excites a larger number of long paths compared to a current generation commercial timing-aware ATPG tool. Our results also show that, for the same pattern count, the selected patterns provide more effective coverage ramp-up than timing-aware ATPG and a recent pattern-selection method for random SDDs potentially caused by resistive shorts, resistive opens, and process variations.
Biology of Industrial Bast Fibers with Reference to Quality

Lignocellulosic bast fibers (e.g., jute, kenaf, hemp, and ramie) are one of the most important renewable carbon-neutral natural resources for various industrial applications. This review gives an outline of bast fiber biogenesis with special emphasis on the cell wall and wall polymers. Role of these molecules in influencing the quality of the bast fiber has been discussed.
Transient Heat Transfer of a Hollow Cylinder Subjected to Periodic Boundary Conditions

The purpose of this paper is to study the transient temperature responses of a hollow cylinder subjected to periodic boundary conditions, which comprises with a short heating period (a few milliseconds) and a relative long cooling period (a few seconds). During the heating process, the inner surface is under complex convection heat transfer condition, which is not so easy to approximate. This paper first calculated the gas temperature history and the convective heat transfer coefficient history between the gas flow and the inner surface and then they were applied to the inner surface as boundary conditions. Finite element analysis was used to solve the transient heat transfer equations of the hollow cylinder. Results show that the inner surface is under strong thermal impact and large temperature gradient occurs in the region adjacent to the inner surface. Sometimes chromium plating and water cooling are used to relief the thermal shock of a tube under such thermal conditions. The effects of these methods are analyzed, and it indicates that the chromium plating can reduce the maximum temperature of the inner surface for the first cycle during periodic heating and the water cooling method can reduce the growth trend of the maximum temperature for sustained conditions. We also investigate the effects of different parameters on the maximum temperature of the inner surface, like chromium thickness, water velocity, channel diameter, and number of cooling channels. [DOI: 10.1115/1.4029757]