Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study on the Challenges and Prospects of PCM Based Main Memory Architectures

For several decades, computer's memory has been volatile. High speed memories such as DRAM and SRAM have been used as main memory and cache memory respectively. Magnetic disks are used as the persistent secondary storage devices. The present DRAM based main memory has reached its energy lits. Due to the advent of nonvolatile memories like PCM, MRAM, RRAM, FeRAM and Flash, there is growing interest in incorporating them into the computers as the main memory alternates. Introducing the non-volatile storage devices in memory hierarchy is considered to reduce the energy consumption since non- volatile memories have got no power leakage in memory cells. A major hurdle in this direction is the poor the endurance limit of most non-volatile memory technologies in comparison to the RAM technologies. Among the non- volatile memory technologies, PCM is the most attractive and the most investigated option due to it advantages over other memory types. But there are few issues related to PCM that need to be addressed in order to integrate it as a potential memory for computers. There have been intense researches being carried out to devise new memory architectures based on PCM. There are also methods identified to overcome the issues of PCM. This paper analyses the various challenges in integrating PCM into the system and the various PCM based main memory architectures that have been proposed so far.
Privacy-Preserving Methods for Sharing Financial Risk Exposures

Unlike other industries in which intellectual property is patentable, the financial industry relies on trade secrecy to protect its business processes and methods, which can obscure critical financial risk exposures from regulators and the public. We develop methods for sharing and aggregating such risk exposures that protect the privacy of all parties involved and without the need for a trusted third party. Our approach employs secure multi-party computation techniques from cryptography in which multiple parties are able to compute joint functions without revealing their individual inputs. In our framework, individual financial institutions evaluate a protocol on their proprietary data which cannot be inverted, leading to secure computations of real-valued statistics such a concentration indexes, pairwise correlations, and other single- and multi-point statistics. The proposed protocols are computationally tractable on realistic sample sizes. Potential financial applications include: the construction of privacy-preserving real-time indexes of bank capital and leverage ratios; the monitoring of delegated portfolio investments; financial audits; and the publication of new indexes of proprietary trading strategies.
Musician Children Detect Pitch Violations in Both Music and Language Better than Nonmusician Children: Behavioral and Electrophysiological Approaches

The idea that extensive musical training can influence processing in cognitive domains other than music has received considerable attention from the educational system and the media. Here we analyzed behavioral data and recorded event-related brain potentials (ERPs) from 8-year-old children to test the hypothesis that musical training facilitates pitch processing not only in music but also in language. We used a parametric manipulation of pitch so that the final notes or words of musical phrases or sentences were congruous, weakly incongruous, or strongly incongruous. Musician children outperformed nonmusician children in the detection of the weak incongruity in both music and language. Moreover, the greatest differences in the ERPs of musician and nonmusician children were also found for the weak incongruity: whereas for musician children, early negative components developed in music and late positive components in language, no such components were found for nonmusician children. Finally, comparison of these results with previous ones from adults suggests that some aspects of pitch processing are in effect earlier in music than in language. Thus, the present results reveal positive transfer effects between cognitive domains and shed light on the time course and neural basis of the development of prosodic and melodic processing.
Motor planning modulates sensory-motor control of collision avoidance behavior in the bullfrog, Rana catesbeiana

Summary In this study, we examined the collision avoidance behavior of the frog, Rana catesbeiana to an approaching object in the upper visual field. The angular velocity of the frog's escape turn showed a significant positive correlation with the turn angle (r2 = 0.5741, P<0.05). A similar mechanism of velocity control has been known in head movements of the owl and in human saccades. By analogy, this suggests that the frog planned its escape velocity in advance of executing the turn, to make the duration of the escape behavior relatively constant. For escape turns less than 60°, the positive correlation was very strong (r2 = 0.7097, P<0.05). Thus, the frog controlled the angular velocity of small escape turns very accurately and completed the behavior within a constant time. On the other hand, for escape turns greater than 60°, the same correlation was not significant (r2 = 0.065, P>0.05). Thus, the frog was not able to control the velocity of the large escape turns accurately and did not complete the behavior within a constant time. In the latter case, there was a small but significant positive correlation between the threshold angular size and the angular velocity (r2 = 0.1459, P<0.05). This suggests that the threshold is controlled to compensate for the insufficient escape velocity achieved during large turn angles, and could explain a significant negative correlation between the turn angle and the threshold angular size (r2 = 0.1145, P<0.05). Thus, it is likely that the threshold angular size is also controlled by the turn angle and is modulated by motor planning.
Myeloma bone disease

Abstract Bone destruction is a hallmark of multiple myeloma, and recent studies demonstrated a strong interdependence between tumor progression and bone resorption. Increased bone resorption as a major characteristic of multiple myeloma is caused by osteoclast activation and osteoblast inhibition (uncoupling). Myeloma cells alter the local regulation of bone metabolism by increasing the receptor activator of NF-κB ligand (RANKL) and decreasing osteoprotegerin (OPG) expression within the bone marrow microenvironment, thereby stimulating the central pathway for osteoclast formation and activation. In addition, they produce the chemokines MIP-1, MIP-1β and SDF-1, which also increase osteoclast activity. Furthermore, myeloma cells suppress osteoblast function by the secretion of osteoblast inhibiting factors, e.g. Dickkopf (DKK)-1. The resulting bone destruction releases several cytokines, which in turn promote myeloma cell growth. Therefore, the inhibition of bone resorption could stop this vicious circle and not only decrease myeloma bone disease, but also the tumor progression. Preclinical studies provided strong evidence that the suppression of the osteoclast activity using bisphosphonates, RANKL blockade or inhibition of MIP-1 or MIP-1β is effective both in reducing myeloma bone disease and tumor growth and therefore may offer an important treatment strategy in multiple myeloma.
A Comparison of the Classification of Disparate Malware Collected in Different Time Periods

It has been argued that an anti-virus strategy based on malware collected at a certain date, will not work at a later date because malware evolves rapidly and an anti- virus engine is then faced with a completely new type of executable not as amenable to detection as the first was. In this paper, we test this idea by collecting two sets of malware, the first from 2002 to 2007, the second from 2009 to 2010 to determine how well the anti-virus strategy we developed based on the earlier set (18) will do on the later set. This anti-virus strategy integrates dynamic and static features extracted from the executables to classify malware by distinguishing between families. We also perform another test, to investigate the same idea whereby we accumulate all the malware executables in the old and new dataset, separately, and apply a malware versus cleanware classification. The resulting classification accuracies are very close for both datasets, with a difference of approximately 5.4% for both experiments, the older malware being more accurately classified than the newer malware. This leads us to conjecture that current anti-virus strategies can indeed be modified to deal effectively with new malware.
Location of actin, myosin, and microtubular structures during directed locomotion of Dictyostelium amebae

During their life cycle, amebae of the cellular slime mould Dictyostelium discoideum aggregate to form multicellular structures in which differentiation takes place. Aggregation depends upon the release of chemotactic signals of 3',5'-cAMP from aggregation centers. In response to the signals, aggregating amebae elongate, actively more toward the attractive source, and may be easily identified from the other cells because of their polarized appearance. To examine the role of cytoskeletal components during ameboid locomotion, immunofluorescence microscopy with antibodies to actin, myosin, and to a microtubule-associated component was used. In addition, rhodamine- labeled phallotoxin was employed. Actin and myosin display a rather uniform distribution in rounded unstretched cells. In polarized locomoting cells, actin fluorescence (due to both labeled phallotoxin and specific antibody) is prevalently concentrated in the anterior pseudopod while myosin fluorescence appears to be excluded from the pseudopod. Similarly, microtubules in locomoting cells are excluded from the leading pseudopod. The cell nucleus is attached to the microtubule network by way of a nucleus-associated organelle serving as a microtubule-organizing center and seems to be maintained in a rather fixed position by the microtubules. These findings, together with available morphological and biochemical evidences, are consistent with a mechanism in which polymerized actin is moved into the pseudopod through its interaction with myosin at the base of the pseudopod. Microtubules, apparently, do not actively participate in movement but seem to behave as anchorage structures for the nucleus and possibly other cytoplasmic organelles.
Red Blood Cell Function and β2 Microglobulin Kinetics during Cuprophan Hemodialysis: A Hypothesis

The exact role of β2microglobulin (β2m) in dialysis amyloidosis is yet not known. Local release of β2m from the endothelial cells of the lung and other tissues as a consequence of acute-phase activation due to the contact of blood with membranes has still to be considered a possible pathogenetic factor in this syndrome. β2m kinetics and decrease of glutathione content in RBC were studied in 41 chronic hemodialysis patients during cuprophan dialysis. The latter test reflects the RBC scavenger function for free oxygen radicals. Only 30% of patients showed a clinically significant increase in β2m. The change in β2m in this group between the start and 180 minutes, corrected for plasma volume, was 23.1±3.6% and the change in gluthathione content between the start and 15 minutes was 4.5±3.4%. In these patients there was a significant correlation between β2m production and decrease of gluthathione (R= -0.61, p= 0.0299). It is possible that the production of free oxygen radicals during bioincompatible dialysis leads to cellular toxicity with release ofβ2m which may be prevented to some extent by the scavenger role of RBC.
Virtual Surfaces and Haptic Shape Perception

Lateral force fields (LFFs) have been used before to generate haptic textures [3]. We propose that LFFs can be used to study haptic shape perception. We present preliminary results of an experiment in which human subjects interact with realistic LFFs. The LFFs encode shape information in the magnitude of unidimensional force vectors. Subjects explore the LFFs and classify them into haptic categories. We found that subjects can consistently perform this classification. This and subjects’ qualitative judgments of the stimuli suggest that haptic interaction with LFFs resembles the experience of touching a real 3D object.
PROPERTY OF MIT PRESS: FOR PROOFREADING AND INDEXING PURPOSES ONLY

One can distinguish between traditional and evolutionary robotics (ER) by the way in which each community generates controllers: traditional roboticists hand-design or use learning methods to create control policies, while evolutionary roboticists employ evolutionary algorithms. What further distinguishes these two approaches is that evolutionary algorithms may also be used to optimize robot morphology as well as the control policy. This chapter traces the history of this practice and outlines how we as a community are transitioning from questions regarding how to evolve morphology to why one should do so. Here I outline seven such reasons: selecting or evolving an appropriate morphology can (1) simplify control, (2) make seemingly difficult tasks easier, (3) increase evolvability, (4) provide new behaviors, (5) facilitate the extraction of information from the environment, (6) generate new research questions, and (7) improve scalability
The Medium is the Message

In this paper we advocate exploiting channel descriptor information in packet data communication networks to gain transmission capacity. Besides the normal data transmission also the channel descriptor (or character of the channel) can be used to convey data. This novel access technique is suitable for wired as well as for wireless networks. By the example of a wireless spread spectrum system with pseudo-noise spreading sequences, we can report that a gain of nearly an order of magnitude in terms of capacity can be achieved compared to the standard spread spectrum transmission for a given scenario. Our approach is not limited to spread spectrum technologies, but applies to all systems with the property that the number of channel descriptors is larger than the actual number of simultaneously usable resources.
An interactive visualization of Genetic Algorithm on 2-D graph

The visualization of search space makes it easy to understand the behavior of the Genetic Algorithms (GAs). We proposed a novel way for representation of multidimensional search space of the GA on 2-D graph. This visualization is carried out based on the gene values of the current generation, and user interruption is only required after several generations. The main contribution of this research is to propose an approach to visualize the GA search data and to improve the searching process of the GA with user's intention in different generations. Besides the selection of best individual or parents for the next generation, interference of user is required to propose a new individual in the search space. Hence, the active user intervention leads to a faster searching, resulting in less user fatigue. The experiments were carried out by evolving the parameters to derive the rules for a Parametric L-System. These rules are then used to model the growth process of branching structures in 3-D space. The experiments were conducted to evaluate the ability of the proposed approach to converge to optimized solution as compared to the Simple Genetic Algorithm (SGA).
A Comparative Survey of Image Binarisation Algorithms for Optical Recognition on Degraded Musical Sources

Binarisation of greyscale images is a critical step in optical music recognition (OMR) preprocessing. Binarising music documents is particularly challenging because of the nature of music notation, even more so when the sources are degraded, e.g., with ink bleed-through from the other side of the page. This paper presents a comparative evaluation of 25 binarisation algorithms tested on a set of 100 music pages. A real-world OMR infrastructure for early music (Aruspix) was used to perform an objective, goaldirected evaluation of the algorithms’ performance. Our results differ significantly from the ones obtained in studies on non-music documents, which highlights the importance of developing tools specific to our community.
Role of n-3 Polyunsaturated Fatty Acids in Ameliorating the Obesity-Induced Metabolic Syndrome in Animal Models and Humans

The incidence of obesity and its comorbidities, such as insulin resistance and type II diabetes, are increasing dramatically, perhaps caused by the change in the fatty acid composition of common human diets. Adipose tissue plays a role as the major energy reservoir in the body. An excess of adipose mass accumulation caused by chronic positive energy balance results in obesity. The n-3 polyunsaturated fatty acids (n-3 PUFA), DHA (docosahexaenoic acid) and EPA (eicosapentaenoic acid) exert numerous beneficial effects to maintain physiological homeostasis. In the current review, the physiology of n-3 PUFA effects in the body is delineated from studies conducted in both human and animal experiments. Although mechanistic studies in human are limited, numerous studies conducted in animals and models in vitro provide potential molecular mechanisms of the effects of these fatty acids. Three aspects of n-3 PUFA in adipocyte regulation are discussed: (1) lipid metabolism, including adipocyte differentiation, lipolysis and lipogenesis; (2) energy expenditure, such as mitochondrial and peroxisomal fatty acid β-oxidation; and (3) inflammation, including adipokines and specialized pro-resolving lipid mediators. Additionally, the mechanisms by which n-3 PUFA regulate gene expression are highlighted. The beneficial effects of n-3 PUFA may help to reduce the incidence of obesity and its comorbidities.
Innovative biocapped CuO nano-photocatalysts: a rapid and green method for photocatalytic degradation of 4-nitrophenol

Abstract In this work, the rapid extracellular biofabrication of CuO nanoparticles (CONPs) was performed through microwave irradiation (MI) using rosehip extract. Not any hazardous reagents were employed during the fabrication period. The as-synthesized CONPs were characterized using XRD, SEM, EDS, antioxidant activity and FT-IR. The CONPs were crystalline and had average sizes about to 20–40 nm according to SEM. This methodology has the advantages of elimination of any chemical surfactants, simple rout and easy work up. The formation mechanism of CONPs was detected, for the first time, by marginal decrease in pH, potentiometric data, XRD and FTIR techniques. Moreover, CONPs as nano-photocatalyst could effectively photodegrade 4-nitrophenol as an environmental pollutant. The degradation rate is about 88% (for 20 ppm of catalyst) in 120 min under Vis irradiation. It demonstrated that the bio-capping had not any retarding effect during photodegradation. This fabrication protocol opens the windows for a large-scale and green approach for generating other metal oxide that are useful as nano-photocatalyst.
How to improve fuzzy-neural system modeling by means of qualitative simulation

The main problem in efficiently building robust fuzzy-neural models of nonlinear systems lies in the difficulty to define a "meaningful" fuzzy rule-base. Our approach to the solution of such a problem is based on a hybrid method which integrates fuzzy systems with qualitative models. We introduce qualitative models to exploit the available, although incomplete, a priori physical knowledge on the system with the goal to infer, through qualitative simulation, all of its possible behaviors.We show here that a rule-base, which captures all of the distinctions in the system states, is automatically generated by encoding the knowledge of the system dynamics described by the outcomes of its qualitative simulation. Such a rule-base properly initializes a fuzzy identifier, which is then tuned to a set of experimental data. Our method has shown good performance when applied both as a predictor and as a simulator.
Nontuberculous Mycobacteria Among Patients Who are Suspected for Multidrug-Resistant Tuberculosis—Need for Earlier Identification of Nontuberculosis Mycobacteria

Background:In this study, we intended to find the prevalence of nontuberculosis mycobacteria (NTM) among patients who are referred as suspected multidrug-resistant tuberculosis (MDR-TB) cases to the only referral center in Iran. Methods:All patients referred to our center in 2002–2006 as MDR-TB with histories of treatment with standard and CAT II World Health Organization regimens were included in the study. Sputum smear and culture for acid-fast bacilli were performed for all patients 3 times. Sputum polymerase chain reaction was also performed for all patients. Mycobacterial identification was performed via polymerase chain reaction and routine identification tests for all culture-positive cases. Results:Of the 105 patients in the study, 12 (11.43%) were identified to have NTM infection. The identified mycobacteria were classified in order of prevalence as Chelonae (8 cases), Simiae (2 cases), Aloei (1 case), and Farcinogen (1 case). Based on radiologic findings, most of the cases demonstrated bilateral nodularity (83.3%) and also multifocal bronchiectasis (75%). Notably, cavitary lesions were present in 41.7% of the cases. Conclusion:Based on the findings of this study, it is essential that such cases be identified before commencing MDR-TB treatment.
A Fast Technique for White Blood Cells Nuclei Automatic Segmentation Based on Gram-Schmidt Orthogonalization

Blood testing is one of the most important clinical examinations. Counting different blood cells is a significant process in a clinical laboratory. Manual microscopic evaluation is compulsory in case there is suspicious abnormality in the blood sample. Yet, the manual inspection is time-consuming and requires adequate technical knowledge. Therefore, automatic medical diagnosis systems are necessary to help physicians to diagnose diseases in a fast and nonetheless competent way. Cell automatic classification has wider interest especially for clinics and laboratories. Segmentation is the most important step for automatic classification success. This paper represents an efficient technique for automatic blood cell nuclei segmentation. This technique is relying on enhancing the color of the target object, nucleus, and filtering the image. Small objects are eliminated employing morphological operations. A set of 365 blood images was used to quantitatively evaluate this segmentation technique. Assessment of the proposed technique on the blood image set gives 85.4% accuracy. In comparison to other published technique that was implemented and executed on the same dataset, the proposed segmentation technique performance was found to be superior. A differential segmentation performance evaluation was performed on the five normal white blood cell types to compare isolated performance. Eosin Phil was found to have the highest segmentation accuracy with 90.1%. Lymphocyte and Basophil have the lowest accuracy with 78.3% and 78.6% respectively. The blood images dataset and the source code are published on MATLAB file exchange website for comparison and re-production.