Miracle-dz/UniFAR-FTUs huggingface dataset:
Carbon Nanostructures in Bone Tissue Engineering

Background: Recent advances in developing biocompatible materials for treating bone loss or defects have dramatically changed clinicians’ reconstructive armory. Current clinically available reconstructive options have certain advantages, but also several drawbacks that prevent them from gaining universal acceptance. A wide range of synthetic and natural biomaterials is being used to develop tissue-engineered bone. Many of these materials are currently in the clinical trial stage. Methods: A selective literature review was performed for carbon nanostructure composites in bone tissue engineering. Results: Incorporation of carbon nanostructures significantly improves the mechanical properties of various biomaterials to mimic that of natural bone. Recently, carbon-modified biomaterials for bone tissue engineering have been extensively investigated to potentially revolutionize biomaterials for bone regeneration. Conclusion: This review summarizes the chemical and biophysical properties of carbon nanostructures and discusses their functionality in bone tissue regeneration.
Quantum Virtual Machine: A Scalable Model to Optimize Energy Savings and Resource Management

This work presents a model for managing Virtual Application Servers (VAS) on cluster-based web servers. In addition to providing energy savings, our model has linear scalability and defines a default processing virtual web server, known as Quantum Virtual Machine (QVM). A set of QVM performs a Logical Web Server (LWS), which operates in a flexible manner, changing its performance and power consumption depending on the workload of the applications. Concepts of agile VAS clone, co-allocation of VAS in the same core, and Dynamic Voltage and Frequency Scaling (DVFS) are used in the model, enabling rapid configuration actions and a fine-grained QoS control. The experiments evaluate the effectiveness of the proposed model by means of power consumption reduction and QoS violation as compared to the Linux CPU governors and state-of-the-art approaches based on optimization. The results show our model conserves up to 51.8% of the energy required by a cluster designed for peak workload scenario, with a negligible impact on the applications performance.
Frequency dependence of CA3 spike phase response arising from h-current properties

The phase of firing of hippocampal neurons during theta oscillations encodes spatial information. Moreover, the spike phase response to synaptic inputs in individual cells depends on the expression of the hyperpolarization-activated mixed cation current (Ih), which differs between CA3 and CA1 pyramidal neurons. Here, we compared the phase response of these two cell types, as well as their intrinsic membrane properties. We found that both CA3 and CA1 pyramidal neurons show a voltage sag in response to negative current steps but that this voltage sag is significantly smaller in CA3 cells. Moreover, CA3 pyramidal neurons have less prominent resonance properties compared to CA1 pyramidal neurons. This is consistent with differential expression of Ih by the two cell types. Despite their distinct intrinsic membrane properties, both CA3 and CA1 pyramidal neurons displayed bidirectional spike phase control by excitatory conductance inputs during theta oscillations. In particular, excitatory inputs delivered at the descending phase of a dynamic clamp-induced membrane potential oscillation delayed the subsequent spike by nearly 50 mrad. The effect was shown to be mediated by Ih and was counteracted by increasing inhibitory conductance driving the membrane potential oscillation. Using our experimental data to feed a computational model, we showed that differences in Ih between CA3 and CA1 pyramidal neurons could predict frequency-dependent differences in phase response properties between these cell types. We confirmed experimentally such frequency-dependent spike phase control in CA3 neurons. Therefore, a decrease in theta frequency, which is observed in intact animals during novelty, might switch the CA3 spike phase response from unidirectional to bidirectional and thereby promote encoding of the new context.
Automatic adjustment system for optical interconnection transmitter using improved particle swarm optimization

One of the challenges to deploying optical interconnection systems, which use optical waveguides instead of metal lines, is the adjustment of the pre-emphasis parameters of the optical transmitter. We developed an automatic adjustment system for the transmitter that is based on particle swarm optimization (PSO). We added two methods to shorten the adjustment time. First, the eye pattern measurement is skipped when the solution is predicted to be a low evaluation value. Second, the quality of the initial solution is improved using regression models. This improved PSO successfully adjusted the waveform of a 25-Gb/s optical transmitter in only 150 s, which is approximately one-third the time taken by the conventional PSO.
Novel SPICE dynamic model of SiC merged PiN schottky diodes

This paper presents a novel SPICE model for SiC merged PiN Schottky diodes applicable for both dynamic and static simulations of these devices. The model takes into account the temperature dependence of device characteristics combining in a single model the behavior typical for bipolar and unipolar devices. The presented dynamic simulations of diode switching process demonstrate that the proposed model produces accurate simulations results, consistent with the measurements, whereas, the model provided by the manufacturer fails to predict properly the device behavior.
Mining Program Workflow from Interleaved Logs

Successful software maintenance is becoming increasingly critical due to the increasing dependence of our society and economy on software systems. One key problem of software maintenance is the difficulty in understanding the evolving software systems. Program workflows can help system operators and administrators to understand system behaviors and verify system executions so as to greatly facilitate system maintenance. In this paper, we propose an algorithm to automatically discover program workflows from event traces that record system events during system execution. Different from existing workflow mining algorithms, our approach can construct concurrent workflows from traces of interleaved events. Our workflow mining approach is a three-step coarse-to-fine algorithm. At first, we mine temporal dependencies for each pair of events. Then, based on the mined pair-wise temporal dependencies, we construct a basic workflow model by a breadth-first path pruning algorithm. After that, we refine the workflow by verifying it with all training event traces. The refinement algorithm tries to find out a workflow that can interpret all event traces with minimal state transitions and threads. The results of both simulation data and real program data show that our algorithm is highly effective.
Age-Related Hearing Loss in Mn-SOD Heterozygous Knockout Mice

Age-related hearing loss (AHL) reduces the quality of life for many elderly individuals. Manganese superoxide dismutase (Mn-SOD), one of the antioxidant enzymes acting within the mitochondria, plays a crucial role in scavenging reactive oxygen species (ROS). To determine whether reduction in Mn-SOD accelerates AHL, we evaluated auditory function in Mn-SOD heterozygous knockout (HET) mice and their littermate wild-type (WT) C57BL/6 mice by means of auditory brainstem response (ABR). Mean ABR thresholds were significantly increased at 16 months when compared to those at 4 months in both WT and HET mice, but they did not significantly differ between them at either age. The extent of hair cell loss, spiral ganglion cell density, and thickness of the stria vascularis also did not differ between WT and HET mice at either age. At 16 months, immunoreactivity of 8-hydroxydeoxyguanosine was significantly greater in the SGC and SV in HET mice compared to WT mice, but that of 4-hydroxynonenal did not differ between them. These findings suggest that, although decrease of Mn-SOD by half may increase oxidative stress in the cochlea to some extent, it may not be sufficient to accelerate age-related cochlear damage under physiological aging process.
Sequence-Based Prediction of Protein Folding Rates Using Contacts, Secondary Structures and Support Vector Machines

Predicting protein folding rate is useful for understanding protein folding process and guiding protein design. Most previous methods of predicting folding rate require the tertiary structure of a protein as an input. And most methods do not distinguish the different kinetic natures (two-state folding and multi-state folding) of the proteins. Here we developed a method, SeqRate, to predict both protein folding kinetic type (two-state versus multi-state) and real-value folding rate using features extracted from only protein sequence with support vector machines. On a standard benchmark dataset, the accuracy of folding kinetic type classification is 80%. The Pearson correlation coefficient and the mean absolute difference between predicted and experimental folding rates (sec-1) in the base-10 logarithmic scale are 0.81 and 0.79 for two-state protein folders, and 0.80 and 0.68 for three-state protein folders. SeqRate is the first sequence-based method for protein folding type classification and its accuracy of fold rate prediction is improved over previous sequence-based methods. Both the web server and software of predicting folding rate are publicly available at http://casp.rnet. missouri.edu/fold_rate/index.html.
Enhancing the Resolution of the Spectrogram Based on a Simple Adaptation Procedure

This work is concerned with improving the quality of signal localization for the short-time Fourier transform by properly adjusting the size of its analysis window over time. The adaptation procedure involves the estimation of an area in the time-frequency plane which is more compact than the support of the fixed-window spectrogram. Then, at each time instant, the optimal window is selected such that the signal energy is maximized within the identified area. The proposed method achieves its objectives, and can compare favorably with alternative time-adaptive spectrograms as well as with advanced quadratic representations.
A Fast Disprover for X eriFun

We present a disprover for universal formulas stating conjectures about functional programs. The quantiﬁed variables range over freely generated polymorphic data types, thus the domains of discourse are inﬁnite in general. The objective in the development was to quickly ﬁnd counter-examples for as many false conjectures as possible without wasting too much time on true statements. We present the reasoning method underlying the disprover and illustrate its practical value in several applications in an experimental version of the veriﬁcation tool X eriFun .
Refining search queries using WordNet glosses

This paper describes one of the approaches how to overcome some major limitations of current fulltext search engines. It tries to discover semantic categories for proper nouns from WordNet glosses and verify them with Yahoo and Google. It relies on lexical patterns present in large repositories and it is inspired by Pankow [2]. It follows the paper from student workshop in April 2006 [6]. Some limitations were solved and new results and plans are presented here.
Time and power allocation for the Gaussian wiretap channel with feedback of secret keys

This paper solves the time and power allocation problem for the simplest feedback scheme for the Gaussian wiretap channel, which is based on the transmission of random secret keys to be used in a one time pad manner. Specifically, the optimal transmission powers at Alice and Bob, as well as the time sharing factor between the feedback and feedforward channels, are given by the solution of a non-convex optimization problem, which is found by means of the golden section algorithm and the sequential solution of several convex optimization problems. Additionally, an specific and highly efficient procedure for the solution of the inner convex optimization problems is provided, which avoids the need for general purpose optimization packages. Finally, several simulation results illustrate the potential secrecy gains achievable with a feedback scheme as simple as the one considered in this paper.
Jahn − Teller Assisted Na Di ﬀ usion for High Performance Na Ion Batteries

: Na energy storage technology is strategically attractive for large scale applications such as grid energy storage. We show in this paper that there is a clear relation between the Jahn − Teller activity of a transition metal ion at the end of charge and the mobility of Na in a cathode material. This is particularly important as mobility at the end of charge limits the capacity of current materials. Hence, by using this classical piece of physics in the battery world, it is possible to create higher capacity Na-cathode materials. Even more exciting is that the ideal element to impart this e ﬀ ect on cathodes is Fe, which is the least expensive of the transition metal oxides and can therefore enable low cost cathode materials.
MANAGER : A Multicore Shared Cache Energy Saving Technique for QoS Systems

Last level caches (LLCs) contribute significantly to processor power consumption. Saving LLC energy in multicore QoS systems is especially challenging, since aggressive energy saving techniques may lead to failure in providing QoS. We present MANAGER, a multicore shared cache energy saving technique for quality-of-service systems. Using dynamic profiling, MANAGER periodically predicts cache access activity for different configurations. Then, cache is partitioned among running programs to fulfill the QoS requirement while saving memory subsystem (LLC+DRAM) energy. Out-of-order simulations performed using dual-core workloads from SPEC2006 suite show that for 4MB LLC, MANAGER saves 13.5% memory subsystem energy, over a statically, equally-partitioned baseline cache.
Localize heavily occluded human faces via deep segmentation

Localizing heavily occluded human faces is a challenging problem in facial detection. Previous methods mainly employ sliding windows by determining whether windows include human faces. In this paper, we provide a novel segmentation-based perspective for heavily occluded face localization with deep convolutional neural networks (CNN). Our model takes an image as input without complicated pre-processing. After several convolutional layers, fully-connected layers and a softmax classifier, we can predict the labels of all pixels in an image, which is the key to localize heavily occluded human faces. Finally, we search a minimal rectangle to localize the human face. Our detector needs neither complex pre-processing nor the time-consuming sliding window. Besides, we use a single model to localize faces to further alleviate computational complexity. Experimental results show that our proposed method is a very effective way to localize heavily occluded human face.
Automatic Marker Field Calibration

In many augmented reality applications a marker field (set of markers) is used to define the 3Dcoordinate transformation between the camera and the virtual objects. In most systems, the physical positions and pose of each marker relative to each others need to be measured in advance. This calibration process is often time consuming and inaccurate if done by hand. We present an automatic calibration process for a set of markers creating a marker field. Our automatic calibration can be used without any preparations and the markers may be placed in any 3D arrangement including even arbitrary angles and slanting planes. The calibration is a real time process and it does not need separate calibration phase. The user may lay markers randomly on suitable places and start tracking immediately. The accuracy of the system improves on the run as the transformation matrices are updated dynamically. The calibration can also be done as a separate calibration stage, and the results can be saved and used later with another application. In our implementation we used ARToolKit and its marker field implementation. However, the algorithms to create a marker field can be applied to create any type of feature/marker field mapping, not only ARToolKit compatible.
Journalism studies still needs to fix Western bias

Granted, studying journalism without any sort of ethnocentric bias is an epistemological impossibility. Just like all human beings, researchers bring their own selves to bear on the object of study. As scholars, we tend to calibrate our understanding of journalism to a convenient set of familiar concepts and cultural experience. This does not necessarily need to be a problem. In an ideal scholarly world, all voices compete in academic discourse regardless of geographic and linguistic origin, ultimately leading to a truly cosmopolitan vision of journalism and news production. Unfortunately, this is not the world we live in. In this short essay, I argue that, despite successful efforts to internationalize the field in terms of quantity, journalism studies is still struggling with the consequences of a continued Western hegemony in the way we approach and understand journalism on a global scale. This hegemony, understandable its reasons are, is doing the field a disservice. Most of what we know and take for granted in the Western world, but also elsewhere, about ‘journalism’ rests on concepts and evidence generated from within Western concepts and experience. Despite globalization, Western countries are still the dominant sites of both the production and subject of research in the field. In part, this Western dominance has resulted from, and is reinforcing, a concentration of academic and textbook publishers in the Anglo-Saxon world using English as the default language. Furthermore, the culturally asymmetric recognition of academic research and intellectual authority in global knowledge production give scholars from the Global North a considerable advantage. Western researchers often take it for granted that their work is relevant to readers around the world, while researchers from non-Western contexts often have to defend their choice of countries and country-specific literatures. Western publications, particularly journal articles, have a structure, format, and academic writing style as well as a quantitative methods bias that non-Western researchers may not always be trained in or be acquainted with, making it difficult for them to publish in journals that offer their work greater visibility.
Neuronal Categorization and Discrimination of Social Behaviors in Primate Prefrontal Cortex

It has been implied that primates have an ability to categorize social behaviors between other individuals for the execution of adequate social-interactions. Since the lateral prefrontal cortex (LPFC) is involved in both the categorization and the processing of social information, the primate LPFC may be involved in the categorization of social behaviors. To test this hypothesis, we examined neuronal activity in the LPFC of monkeys during presentations of two types of movies of social behaviors (grooming, mounting) and movies of plural monkeys without any eye- or body-contacts between them (no-contacts movies). Although the monkeys were not required to categorize and discriminate the movies in this task, a subset of neurons sampled from the LPFC showed a significantly different activity during the presentation of a specific type of social behaviors in comparison with the others. These neurons categorized social behaviors at the population level and, at the individual neuron level, the majority of the neurons discriminated each movie within the same category of social behaviors. Our findings suggest that a fraction of LPFC neurons process categorical and discriminative information of social behaviors, thereby contributing to the adaptation to social environments.
Iterative structure of the = 4 SYM spin chain

We develop algebraic methods for finding loop corrections to the = 4 SYM dilatation generator, within the noncompact (1, 1|2) sector. This sector gives a 't Hooft coupling λ-dependent representation of (1, 1|2) × (1|1)2. At first working independently of the representation, we present an all-order algebraic ansatz for the λ-dependence of this Lie algebra's generators. The ansatz solves the symmetry constraints if an auxiliary generator, , satisfies certain simple commutation relations with the Lie algebra generators. Applying this to the (1, 1|2) sector leads to an iterative solution for the planar three-loop dilatation generator in terms of leading order symmetry generators and , which passes a thorough set of spectral tests. We argue also that this algebraic ansatz may be applicable to the nonplanar theory as well.
A 40nm/65nm process adaptive low jitter phase-locked loop

As the chip performance improved, low jitter PLL is getting more attention. The migration of process requires more stability of PLL among different processes. In this paper, by depressing the non-ideality of charge-pump and setting the two-stage control voltage of VCO, the noise performance of PLL is improved. The self-adaptive bandwidth technology is used to decrease the dependency between process and performance. The simulation proves that this PLL can adapt to both 40nm and 65nm process. The chip is taped out under 40nm CMOS process, the phase-noise performance of this PLL is -130dBc/Hz@3MHz at 1GHz, the maximum VCO output is up to 3.2GHz, the lowest resolution is 0.048Hz, which guarantees the high versatility and high performance of this PLL.