Miracle-dz/UniFAR-FTUs huggingface dataset:
Polypropylene nanocomposite for power equipment: a review

Polypropylene (PP), with high breakdown strength, low dissipation and good processibility, is one of the most widely used dielectric material for power equipment, especially in power capacitors and power cables. The improvement of PP-based dielectric material can benefit the properties enhancement of power capacitors and cables, and thus to meet with the rapid development of the power system. Nanocomposite provided a promising orientation to reach the target and recent research approaches of PP nanocomposite for power equipment were reviewed in this paper. In this paper, we linked the nanofillers to the improved properties of PP nanocomposite, and categorised the research works into nanoclay/PP composites, metal oxide/PP nanocomposite, conductive particles/PP nanocomposite, and PP core-shell nanocomposites chronologically, corresponding to the enhanced thermal and mechanical property, breakdown strength property and energy storage property, respectively. Based on the achieved approaches, prospective for future research was proposed, providing a worth-considering direction for the future work.
Toward an Evolved Concept of Landrace

The term “landrace” has generally been defined as a cultivated, genetically heterogeneous variety that has evolved in a certain ecogeographical area and is therefore adapted to the edaphic and climatic conditions and to its traditional management and uses. Despite being considered by many to be inalterable, landraces have been and are in a constant state of evolution as a result of natural and artificial selection. Many landraces have disappeared from cultivation but are preserved in gene banks. Using modern selection and breeding technology tools to shape these preserved landraces together with the ones that are still cultivated is a further step in their evolution in order to preserve their agricultural significance. Adapting historical landraces to present agricultural conditions using cutting-edge breeding technology represents a challenging opportunity to use them in a modern sustainable agriculture, as an immediate return on the investment is highly unlikely. Consequently, we propose a more inclusive definition of landraces, namely that they consist of cultivated varieties that have evolved and may continue evolving, using conventional or modern breeding techniques, in traditional or new agricultural environments within a defined ecogeographical area and under the influence of the local human culture. This includes adaptation of landraces to new management systems and the unconscious or conscious selection made by farmers or breeders using available technology. In this respect, a mixed selection system might be established in which farmers and other social agents develop evolved landraces from the variability generated by public entities.
Mechanical strength in hierarchically polycrystalline graphene with dislocation arrays-embedded grains

Nanotwinning lamellae within crystalline grains strengthens 3D polycrystalline solids due to inactive dislocation-slips by nanotwinning. 2D graphene with twin grain boundaries formed by pentagon-heptagon dislocation lines (PHDLs) exhibits high strength comparable to pristine lattice. However, the role of PHDLs embedded within 2D polycrystalline grains on the mechanical properties of graphene remains unknown yet. Here, hierarchically polycrystalline graphene comprising of a variety of PHDLs-embedded grains are constructed and their tensile properties are explored by atomistic simulations. Relaxed hierarchical polycrystals composed of PHDLs-contained grains are hierarchically wrinkled, with unique surface wrinkles of grains nested within irregularly global wrinkles, in contrast to the conventional counterparts. Tensile strengths of PHDLs-contained polycrystals are type of PHDLs dependent; those with robust PHDLs are as strong as the intragain PHDLs-free counterpart. All hierarchical polycrystals demonstrate inverse pseudo Hall-Petch-like strength relations to grain size, analogous to the counterpart yet in contrast to nanotwinned polycrystals. However, depending on the type of PHDLs, either monotonous or ‘flipped’ variation in the breaking strains with grain size is observed. Four distinct cracking behaviors are identified relying on the robustness of PHDLs. Particularly, tension-induced broken bonds shared by hexagon-heptagon near the PHDLs are recoverable. These findings shed new light in the optimal performance of 2D materials through dislocation engineering for practical applications in flexible systems.
Metric and topological entropy bounds on state estimation for stochastic non-linear systems

This paper studies state estimation over noisy channels for stochastic non-linear systems. We consider three estimation objectives, a strong and a weak form of almost sure stability of the estimation error as well as quadratic stability in expectation. For all three objectives, we derive lower bounds on the smallest channel capacity Co above which the objective can be achieved with an arbitrarily small error. Lower bounds are obtained via a dynamical systems (through a novel construction of a dynamical system), an information-theoretic and a random dynamical systems approach. The first two approaches show that for a large class of systems, such as additive noise systems, Co = ∞, i.e., the estimation objectives cannot be achieved via channels of finite capacity. The random dynamical systems approach is shown to be operationally non-adequate for the problem, since it yields finite lower bounds Co under mild assumptions. Finally, we prove that a memoryless noisy channel in general constitutes no obstruction to asymptotic almost sure state estimation with arbitrarily small errors, when there is no noise in the system.
Real-time multidimensional NMR follows RNA folding with second resolution

Conformational transitions and structural rearrangements are central to the function of many RNAs yet remain poorly understood. We have used ultrafast multidimensional NMR techniques to monitor the adenine-induced folding of an adenine-sensing riboswitch in real time, with nucleotide-resolved resolution. By following changes in 2D spectra at rates of approximately 0.5 Hz, we identify distinct steps associated with the ligand-induced folding of the riboswitch. Following recognition of the ligand, long range loop-loop interactions form and are then progressively stabilized before the formation of a fully stable complex over approximately 2–3 minutes. The application of these ultrafast multidimensional NMR methods provides the opportunity to determine the structure of RNA folding intermediates and conformational trajectories.
Novel insights into the management of brain metastases.

PURPOSE OF REVIEW This review provides available clinical evidence regarding current therapies, discusses ongoing controversies, and introduces investigational approaches in the management of brain metastases. RECENT FINDINGS Novel approaches to estimating prognosis of patients with brain metastases highlight the importance of tailoring treatment to each particular patient. In the setting of unfavorable prognosis, either hospice care, symptom management, or short-course whole-brain radiotherapy (WBRT) is a critical component of palliation. In the setting of favorable or intermediate prognosis, treatment options can include a slightly more prolonged course of WBRT, surgery, stereotactic radiosurgery, systemic therapy, or a combination. Selection of the appropriate treatment is influenced by the number of brain metastases, overall patient performance status and residual life expectancy, as well as an understanding of the benefits and toxicities of each modality. Recent clinical studies have shed novel insight on the temporal sequence of memory changes following WBRT. Innovative approaches to mitigating these radiation-induced memory effects are currently being investigated. SUMMARY Evidence-based management of brain metastases represents an evolving field of active clinical research. Ongoing and future investigations focus on the preservation of cognition and quality of life, in addition to conventional outcomes such as intracranial tumor control and survival.
Nonlinear neural-network modeling of an induction machine

Presents an approach to identify the nonlinear model of an induction machine. The free acceleration test is performed on a 5-HP induction machine, and the resulting stator voltages, stator currents and rotor angular velocity are measured. Using the maximum likelihood (ML) algorithm, the parameter sets of the nonlinear model at various operating conditions are estimated. Then the nonlinear model parameters are represented by feedforward neural networks (FNNs). For validation, the simulated responses of the identified model using the measured and the simulated input patterns for the FNN models are performed. The identified model can be utilized for power system transient stability analysis and for online computer controlled electric drives.
Palmprint Identification by Fourier Transform

Palmprint identification refers to searching in a database for the palmprint template, which is from the same palm as a given palmprint input. The identification process involves preprocessing, feature extraction, feature matching and decision-making. As a key step in the process, in this paper, we propose a new feature extraction method by converting a palmprint image from a spatial domain to a frequency domain using Fourier Transform. The features extracted in the frequency domain are used as indexes to the palmprint templates in the database and the searching process for the best match is conducted by a layered fashion. The experimental results show that palmprint identification based on feature extraction in the frequency domain is effective in terms of accuracy and efficiency.
Natural technologies for knowledge work: information visualization and knowledge extraction

This paper ‘looks” into one of the most novel knowledge management technology products that has been brought to the market in the recent years. The authors describe two technologies, information visualization and knowledge extraction, for leveraging our natural abilities of vision, language and memory. They discuss a way for exploiting structure that is available in the information system in one case (traditionally called structured) and easily perceived by humans in the other (traditionally called unstructured). The two technologies focus on the two sides of this goal, respectively. They demonstrate the value of these technologies in supporting interaction with much larger amounts of information than was possible with previous graphical interfaces and in guiding access and use of the information and often for automating portions of the work.
Feedback linearization approach to distributed feedback manipulation

This report formulates the problem of a distributed planar manipulation realized by shaping a spatially continuous force field. It also suggests a control strategy based on feedback linearization. Force fields derived from potential fields are considered. The potentials are “shaped” by a set of spatially discrete “actuators“ such as electrodes in the case of dielectrophoresis, electromagnets in the case of planar magnetic manipulators, or linear piezoelectric actuators in the case of deformable flat surfaces. The actuators form arrays. Distinguished feature of such force fields is that the contribution from an individual actuator usually affects the situation in the neighboring zones too, but usually not in too remote zones. As an idealization, the spatial domain is considered unbounded, which enables examination of asymptotic behavior of the manipulation scheme.
Natural killer cells and hepatitis C: action and reaction

In 1989, hepatitis C virus (HCV) was first identified as the infectious agent responsible for human non-A, non-B hepatitis.1 Two decades later, HCV remains a global public health problem with a suboptimal response rate to treatment and the absence of a protective vaccine. Recent work has highlighted the influence of the innate immune system, and in particular natural killer cells, on the outcome and pathology of HCV infection. These cells are considerably more complex than was originally thought and their role in viral infections is currently being unravelled. This review summarises our emerging understanding of natural killer cells in HCV infection.
Optimization of a Deep-Learning Method Based on the Classification of Images Generated by Parameterized Deep Snap a Novel Molecular-Image-Input Technique for Quantitative Structure–Activity Relationship (QSAR) Analysis

Numerous chemical compounds are distributed around the world and may affect the homeostasis of the endocrine system by disrupting the normal functions of hormone receptors. Although the risks associated with these compounds have been evaluated by acute toxicity testing in mammalian models, the chronic toxicity of many chemicals remains due to high cost of the compounds and the testing, etc. However, computational approaches may be promising alternatives and reduce these evaluations. Recently, deep learning (DL) has been shown to be promising prediction models with high accuracy for recognition of images, speech, signals, and videos since it greatly benefits from large datasets. Recently, a novel DL-based technique called DeepSnap was developed to conduct QSAR analysis using three-dimensional images of chemical structures. It can be used to predict the potential toxicity of many different chemicals to various receptors without extraction of descriptors. DeepSnap has been shown to have a very high capacity in tests using Tox21 quantitative qHTP datasets. Numerous parameters must be adjusted to use the DeepSnap method but they have not been optimized. In this study, the effects of these parameters on the performance of the DL prediction model were evaluated in terms of the loss in validation as an indicator for evaluating the performance of the DL using the toxicity information in the Tox21 qHTP database. The relations of the parameters of DeepSnap such as (1) number of molecules per SDF split into (2) zoom factor percentage, (3) atom size for van der waals percentage, (4) bond radius, (5) minimum bond distance, and (6) bond tolerance, with the validation loss following quadratic function curves, which suggests that optimal thresholds exist to attain the best performance with these prediction models. Using the parameter values set with the best performance, the prediction model of chemical compounds for CAR agonist was built using 64 images, at 105° angle, with AUC of 0.791. Thus, based on these parameters, the proposed DeepSnap-DL approach will be highly reliable and beneficial to establish models to assess the risk associated with various chemicals.
Does adiponectin benefit steatotic liver transplantation?

Strategies for improving the viability of steatotic donor livers could increase the number of organs suitable for transplantation. There is evidence that adiponectin, the most abundant adipose‐specific adipokine, acts as an anti‐obesity and anti‐inflammatory hormone. Here we review the signaling pathways of adiponectin and the possible therapies based on adiponectin regulation that have been examined or applied clinically. Recent studies on the role of adiponectin in steatotic livers subjected to ischemia/reperfusion are discussed. The data suggest that further investigations are required to determine whether adiponectin is a potential therapeutic target in liver transplantation. Liver Transpl 17:993–1004, 2011. © 2011 AASLD.
Applying ethnography to the study of context in healthcare quality and safety

Background Translating and scaling healthcare quality improvement (QI) and patient safety interventions remains a significant challenge. Context has been identified as a major factor in this. QI and patient safety research have begun to focus on context, with ethnography seen as a promising methodology for understanding the professional, organisational and cultural aspects of context. While ethnography is used to investigate the context of a variety of QI and safety interventions, the challenges inherent in effectively importing a qualitative methodology and its social science practitioners into this work have been largely unexamined. Method and results We explain ethnography as a research practice grounded in theory and dependent on observations gathered and interpreted in particular ways. We then review the approach of health services literature to evaluating this sort of qualitative research. Although the study of context is an interest shared by both social scientists and healthcare QI and safety researchers, we identify three key points at which those ‘exporting’ ethnography as a methodology and those ‘importing’ it to deal with QI and safety challenges may diverge. We describe perspectival divergences on the methodology's mission, form and scale. At the level of mission we demonstrate how ethnography has been adapted to a ‘describe and feed back’ role in the service of QI. At the level of form, we show how the long-term embedded observation at the heart of ethnography can be adapted only so far to accommodate QI interests if both data quality and ethical standards are to be upheld. Finally, at the level of scale, we demonstrate one ethnographic study design that balances breadth of exposure with depth of experience in its observations and so generates a particular type of scalable findings. Summary The effective export of ethnography into QI and safety research requires discussion and negotiation between social scientific and health services research perspectives, as well as creative approaches to producing self-reflexive data that will allow clinicians to understand their own context and so improve their own processes.
A New Method for Determination of Postmortem Interval: Citrate Content of Bone *

Abstract: Few accurate methods exist currently to determine the time since death (postmortem interval, PMI) of skeletonized human remains found at crime scenes. Citrate is present as a constituent of living human and animal cortical bone at very uniform initial concentration (2.0 ± 0.1 wt %). In skeletal remains found in open landscape settings (whether buried or not), the concentration of citrate remains constant for a period of about 4 weeks, after which it decreases linearly as a function of log(time). The upper limit of the dating range is about 100 years. The precision of determination decreases slightly with age. The rate of decrease appears to be independent of temperature or rainfall but drops to zero for storage temperature <0°C.
Rough Terrain Visual Odometry

We present an integrated system to localize a mobile robot in rough outdoor terrain using visual odometry. Our previous work [1] presented a visual odometry solution that estimates frame-to-frame motion from stereo cameras and integrated this incremental motion with a low cost GPS. We extend that work through the use of bundle adjustment over multiple frames. Bundle adjustment helps to reduce the error significantly, thereby making our system more robust and accurate while still operating in real-time. Our new system can keep the robot well localized over several hundreds of meters to within 1% error. We present experimental results for our system over a 300 meters run in a challenging environment and compare it with ground truth Real Time Kinematic (RTK) GPS.
Spotting out the Cancerous Cells with Magnetic Nanoparticles using Microwave Imaging

The research in biomedical nanotechnology includes various applications using nanoparticles. The magnetic nanoparticle plays a vital role in medical diagnosis and treatment of cancer. This nanoparticles act as a biomarker for labeling the structures of cells, viruses and protein. One of the most noted medical applications using nanotechnology is Magnetic Drug Targeting (MDT). The MDT has the combination of chemotherapeutic drug and Magnetic Nanoparticles (MNPs), which are bounded together and surrounded near the tumor area by means of an external static magnetic field. The Microwave Imaging (MI) has been proposed as a corresponding diagnostic imaging technique mainly for cancer detection. This paper presents the approaches for spotting out the cancerous cells using the MDT and MI techniques. Keywords— Nanotechnology, nanoparticles, magnetic drug targeting, microwave imaging, biomarker.
How Neurons Know That It's C-c-c-c-cold Outside

NEUROSCIENCEA spate of papers published this month offers two answers to the question of how nerve cells transmit cold sensations. Sometimes specialized sensors for menthol, the active ingredient in mint, do the job; other times neurons choreograph the movement of ions in response to cold in the absence of a specific receptor. Researchers suspect that the two mechanisms operate in concert, either in separate populations of cells or together in the same neurons.
Calneurons provide a calcium threshold for trans-Golgi network to plasma membrane trafficking

Phosphatidylinositol 4-OH kinase IIIβ (PI-4Kβ) is involved in the regulated local synthesis of phospholipids that are crucial for trans-Golgi network (TGN)-to-plasma membrane trafficking. In this study, we show that the calcium sensor proteins calneuron-1 and calneuron-2 physically associate with PI-4Kβ, inhibit the enzyme profoundly at resting and low calcium levels, and negatively interfere with Golgi-to-plasma membrane trafficking. At high calcium levels this inhibition is released and PI-4Kβ is activated via a preferential association with neuronal calcium sensor-1 (NCS-1). In accord to its supposed function as a filter for subthreshold Golgi calcium transients, neuronal overexpression of calneuron-1 enlarges the size of the TGN caused by a build-up of vesicle proteins and reduces the number of axonal Piccolo-Bassoon transport vesicles, large dense core vesicles that carry a set of essential proteins for the formation of the presynaptic active zone during development. A corresponding protein knockdown has the opposite effect. The opposing roles of calneurons and NCS-1 provide a molecular switch to decode local calcium transients at the Golgi and impose a calcium threshold for PI-4Kβ activity and vesicle trafficking.
Analysis of the Pathogenic Factors and Management of Dry Eye in Ocular Surface Disorders

The tear film represents the interface between the eye and the environment. The alteration of the delicate balance that regulates the secretion and distribution of the tear film determines the dry eye (DE) syndrome. Despite having a multifactorial origin, the main risk factors are female gender and advanced age. Likewise, morphological changes in several glands and in the chemical composition of their secretions, such as proteins, mucins, lipidics, aqueous tears, and salinity, are highly relevant factors that maintain a steady ocular surface. Another key factor of recurrence and onset of the disease is the presence of local and/or systemic inflammation that involves the ocular surface. DE syndrome is one of the most commonly encountered diseases in clinical practice, and many other causes related to daily life and the increase in average life expectancy will contribute to its onset. This review will consider the disorders of the ocular surface that give rise to such a widespread pathology. At the end, the most recent therapeutic options for the management of DE will be briefly discussed according to the specific underlying pathology.