Miracle-dz/UniFAR-FTUs huggingface dataset:
Robustness of Face Recognition to Image Manipulations

We can often recognize pictures of people we know even if the image has low resolution or obscures part of the face, if the camera angle resulted in a distorted image of the subject’s face, or if the subject has aged or put on makeup since we last saw them. Although this is a simple recognition task for a human, when we think about how we accomplish this task, it seems non-trivial for computer algorithms to recognize faces despite visual changes. Computer facial recognition is relied upon for many application where accuracy is important. Facial recognition systems have applications ranging from airport security and suspect identification to personal device authentication and face tagging [7]. In these real-world applications, the system must continue to recognize images of a person who looks slightly different due to the passage of time, a change in environment, or a difference in clothing. Therefore, we are interested in investigating face recognition algorithms and their robustness to image changes resulting from realistically plausible manipulations. Furthermore, we are curious about whether the impact of image manipulations on computer algorithms’ face recognition ability mirrors related insights from neuroscience about humans’ face recognition abilities.
Low-temperature expanded graphite for preparation of graphene sheets by liquid-phase method

A facile and scalable preparation of aqueous solutions of isolated, sparingly graphene sheets from low-temperature expanded graphite by liquid-phase method is reported. And the influence of expansion temperature on the property of graphene sheets in expanded graphite is discussed by several characterization methods. The TEM scans also indicate that graphene sheets exfoliated from expanded graphite has been restored to an extended conjugated sp2 network.
Mevalonate Metabolism in Immuno-Oncology

Immuno-oncology not only refers to the multifaceted relationship between our immune system and a developing cancer but also includes therapeutic approaches that harness the body’s immune system to fight cancer. The recognition that metabolic reprogramming governs immunity was a key finding with important implications for immuno-oncology. In this review, we want to explore how activation and differentiation-induced metabolic reprogramming affects the mevalonate pathway for cholesterol biosynthesis in immune and cancer cells. Glycolysis-fueled mevalonate metabolism is a critical pathway in immune effector cells, which may, however, be shared by cancer stem cells, complicating the development of therapeutic strategies. Additional engagement of fatty acidy oxidation, as it occurs in regulatory immune cells as well as in certain tumor types, may influence mevalonate pathway activity. Transcellular mevalonate metabolism may play an as yet unanticipated role in the crosstalk between the various cell types and may add another level of complexity. In humans, a subset of γδ T cells is specifically adapted to perform surveillance of mevalonate pathway dysregulation. While the mevalonate pathway remains an important target in immuno-oncology, in terms of personalized medicine, it may be the type or stage of a malignant disease that determines whether mevalonate metabolism requires training or attenuation.
Hybrid adders for high-speed arithmetic circuits: A comparison

In this paper the most interesting topologies of one-bit hybrid full adders, are analyzed and compared for speed, power consumption, and power-delay product. The investigation has been carried out with properly defined simulation set up and input pattern on a Mentor Graphics environment using a TSMC 180 nm CMOS process. Performance has been also compared for different supply voltage values. The simulation results show that the Chang adder is the best in terms of PDP figure of merit; however the Aguirre adder is the best in terms of driving capability even at low power supply.
Population structure of Hypochaeris salzmanniana DC. (Asteraceae), an endemic species to the Atlantic coast on both sides of the Strait of Gibraltar, in relation to Quaternary sea level changes

To detect potential Pleistocene refugia and colonization routes along the Atlantic coast, we analysed amplified fragment length polymorphisms (AFLPs) in 140 individuals from 14 populations of Hypochaeris salzmanniana (Asteraceae), an annual species endemic to the southwestern European and northwestern African coastal areas. Samples covered the total distributional range of the species, with eight populations in southwestern Spain and six populations in northwestern Morocco. Using nine primer combinations, we obtained 546 fragments in H. salzmanniana and its sister species H. arachnoidea of which 487 (89.2%) were polymorphic. The neighbour‐joining tree shows that the populations south of the Loukos river in Morocco are clearly differentiated, having more polymorphic, private, and rare fragments, and higher genetic diversity, than all the other populations. The southernmost populations in Morocco, south of the river Sebou, form a large panmictic population. They are probably the oldest populations that have been relatively unaffected by stochastic processes resulting from Pleistocene glaciations. Northward migration of populations during this period may have resulted in loss of genetic diversity in specific regions, perhaps due to bottlenecks caused by rise in sea level during interglacial periods, and, in some cases, by changes in the breeding system.
Development of a LDIE Prediction Theory in the Condition of Magnetite Formation on Secondary Side Piping in Nuclear Power Plants

It has been thought that wall thinning on the secondary side piping in nu-clear power plants is mostly caused by Flow-Accelerated Corrosion (FAC). Recently, it has been seen that wall thinning on the secondary side piping carrying two-phase flow is caused by not only FAC but also Liquid Droplet Impingement Erosion (LDIE). Moreover, it turns out that LDIE in nuclear power plants does not result from a single degradation mechanism but also from the simultaneous happenings of LDIE and FAC. This paper presents a comparison of the mass loss rate of the tested materials between carbon steel (A106 B) and low alloy steel (A335 P22) resulting from degradation effect. An experimental facility was set up to develop a prediction model for clarifying multiple degradation mechanisms that occur together. The experimental facility allows examining liquid droplet impingement erosion in the same conditions as the secondary side piping in nuclear power plants by generating the magnetite on the surface of the test materials. The magnetite is formed by controlling the water chemistry and the temperature of fluid inside the facility. In the initial stage of the experiments, the mass loss rate of A106 B was greater than that of A335 P22. However, after a certain period of time, the mass loss rate of A335 P22 became greater than that of A106 B. It is presumed that the results are caused by the different yield strengths of the test materials and the different degrees of buffer action of the magnetite deposited on their surfaces. The layer of magnetite on the surface of A106 is thicker than that of A335 P22, due to the different amount of chrome content. In nuclear power plants, carbon steel piping having experienced wall thinning degradation is generally replaced with low-alloy steel piping. However, the materials of pipes carrying two-phase flow should be selected considering their susceptibility to LDIE.
Validity and reliability of the Spineangel® lumbo-pelvic postural monitor

Objective: to determine the reliability and the concurrent validity of the Spineangel® lumbo-pelvic postural monitoring device. Methods: the dynamic lumbo-pelvic posture of 25 participants was simultaneously monitored by the Spineangel® and FastrakTM devices. Participants performed six different functional tasks in random order. Within-task, within-session and between-day intraclass correlation coefficients (ICC(3,1), ICC(3,5), ICC(2,5), respectively) reliability were calculated for Spineangel® measurements. Concurrent validity of the Spineangel® was assessed by means of a Bland and Altman plot and by means of Pearson's correlation coefficient and paired t-test. Results: within-task, within-session and between-day ICC for the Spineangel® were found to be excellent (>0.93). The Spineangel® and FastrakTM pelvic measurements were found to have a good correlation (R = 0.77). Conclusion: the Spineangel® is a reliable and valid device for monitoring general lumbo-pelvic movements when clipped on the belt or waistband of workers' clothing during various occupational activities. Practitioner summary: The Spineangel® can be used for assessing lumbo-pelvic posture during work or daily-life activities. This device was found to provide reliable and valid measurements for lumbo-pelvic movements. Further research is required to determine whether the use of this device is clinically relevant for patients presenting with low back pain.
A Unified Posterior Regularized Topic Model with Maximum Margin for Learning-to-Rank

While most methods for learning-to-rank documents only consider relevance scores as features, better results can often be obtained by taking into account the latent topic structure of the document collection. Existing approaches that consider latent topics follow a two-stage approach, in which topics are discovered in an unsupervised way, as usual, and then used as features for the learning-to-rank task. In contrast, we propose a learning-to-rank framework which integrates the supervised learning of a maximum margin classifier with the discovery of a suitable probabilistic topic model. In this way, the labelled data that is available for the learning-to-rank task can be exploited to identify the most appropriate topics. To this end, we use a unified constrained optimization framework, which can dynamically compute the latent topic similarity score between the query and the document. Our experimental results show a consistent improvement over the state-of-the-art learning-to-rank models.
An Embodied Conversational Agent with Asperger Syndrome

We discuss the development of an embodied conversational agent with Asperger-like communi- cation skills. The agent was developed for use in educational software in a virtual environment specically aimed at autism spectrum disorder software. We describe the design and implementa- tion of the agent, and pay particular attention to the interaction between emotion, personality and social context. A 3D demonstration shows the typical output to conform to Asperger-like answers, with corresponding emotional responses.
Gap junction structures after experimental alteration of junctional channel conductance

Gap junctions are known to present a variety of different morphologies in electron micrographs and x-ray diffraction patterns. This variation in structure is not only seen between gap junctions in different tissues and organisms, but also within a given tissue. In an attempt to understand the physiological meaning of some aspects of this variability, gap junction structure was studied following experimental manipulation of junctional channel conductance. Both physiological and morphological experiments were performed on gap junctions joining stage 20-23 chick embryo lens epithelial cells. Channel conductance was experimentally altered by using five different experimental manipulations, and assayed for conductance changes by observing the intercellular diffusion of Lucifer Yellow CH. All structural measurements were made on electron micrographs of freeze-fracture replicas after quick-freezing of specimens from the living state; for comparison, aldehyde-fixed specimens were measured as well. Analysis of the data generated as a result of this study revealed no common statistically significant changes in the intrajunctional packing of connexons in the membrane plane as a result of experimental alteration of junctional channel conductance, although some of the experimental manipulations used to alter junctional conductance did produce significant structural changes. Aldehyde fixation caused a dramatic condensation of connexon packing, a result not observed with any of the five experimental uncoupling conditions over the 40-min time course of the experiments.
Ultrafast imaging of cell elasticity with optical microelastography

Significance In wave physics, and especially seismology, uncorrelated vibrations could be exploited using “noise correlation” tools to reconstruct images of a medium. By using a high-frequency vibration, a high-speed tracking device, and a reconstruction technique based on temporal correlations of travelling waves we conceptualized an optical microelastography technique to map elasticity of internal cellular structures. This technique, unlike other methods, can provide an elasticity image in less than a millisecond, thus opening the possibility of studying dynamic cellular processes and elucidating new mechanocellular properties. We call this proposed technique “cell quake elastography. ” Elasticity is a fundamental cellular property that is related to the anatomy, functionality, and pathological state of cells and tissues. However, current techniques based on cell deformation, atomic force microscopy, or Brillouin scattering are rather slow and do not always accurately represent cell elasticity. Here, we have developed an alternative technique by applying shear wave elastography to the micrometer scale. Elastic waves were mechanically induced in live mammalian oocytes using a vibrating micropipette. These audible frequency waves were observed optically at 200,000 frames per second and tracked with an optical flow algorithm. Whole-cell elasticity was then mapped using an elastography method inspired by the seismology field. Using this approach we show that the elasticity of mouse oocytes is decreased when the oocyte cytoskeleton is disrupted with cytochalasin B. The technique is fast (less than 1 ms for data acquisition), precise (spatial resolution of a few micrometers), able to map internal cell structures, and robust and thus represents a tractable option for interrogating biomechanical properties of diverse cell types.
The Lucas paradox and the quality of institutions

In the first era of financial globalization (1880-1914), global capital market integration led to substantial net capital movements from rich to poor economies. The historical experience stands in contrast to the contemporary globalization where gross capital mobility is equally high, but did not incite a substantial transfer of savings from rich to poor economies. Using data for the historical and modern periods we extend Lucas' (1990) original model and show that differences in institutional quality between rich and poor countries can account for the sharply divergent patterns of international capital movements. for sharing data or thoughts. All remaining mistakes are our own.
Extended search space pruning in LVCSR

We compare the most important pruning methods which are common in different LVCSR decoding architectures and lead them back to a theoretical motivation. Based on this motivation, we propose a new pruning method which fades the word end pruning over a large part of the search network. We analyze the methods regarding their relationship between search-space and word error rate, and regarding their mutual dependence. We show that the different pruning methods are mutually dependent and difficult to combine, and that our new pruning method is the most effective method regarding both the search space and runtime efficiency.
Selective In Vivo Visualization of Immune-Cell Infiltration in a Mouse Model of Autoimmune Myocarditis by Fluorine-19 Cardiac Magnetic Resonance

Background— The goal of this study was to characterize the performance of fluorine-19 (19F) cardiac magnetic resonance (CMR) for the specific detection of inflammatory cells in a mouse model of myocarditis. Intravenously administered perfluorocarbons are taken up by infiltrating inflammatory cells and can be detected by 19F-CMR. 19F-labeled cells should, therefore, generate an exclusive signal at the inflamed regions within the myocardium. Methods and Results— Experimental autoimmune myocarditis was induced in BALB/c mice. After intravenous injection of 2×200 µL of a perfluorocarbon on day 19 and 20 (n=9) after immunization, in vivo 19F-CMR was performed at the peak of myocardial inflammation (day 21). In 5 additional animals, perfluorocarbon combined with FITC (fluorescein isothiocyanate) was administered for postmortem immunofluorescence and flow-cytometry analyses. Control experiments were performed in 9 animals. In vivo 19F-CMR detected myocardial inflammation in all experimental autoimmune myocarditis-positive animals. Its resolution was sufficient to identify even small inflammatory foci, that is, at the surface of the right ventricle. Postmortem immunohistochemistry and flow cytometry confirmed the presence of perfluorocarbon in macrophages, dendritic cells, and granulocytes, but not in lymphocytes. The myocardial volume of elevated 19F signal (r s=0.96; P<0.001), the 19F signal-to-noise ratio (r s=0.92; P<0.001), and the 19F signal integral (r s=0.96; P<0.001) at day 21 correlated with the histological myocarditis severity score. Conclusions— In vivo 19F-CMR was successfully used to visualize the inflammation specifically and robustly in experimental autoimmune myocarditis, and thus allowed for an unprecedented insight into the involvement of inflammatory cells in the disease process.
Explore maximal frequent itemsets for big data pre-processing based on small sample in cloud computing

The data mining issue in big data processing which is based on cloud computing has become a hot research topic. Generally, most of the previous work directly analyzes the data through the existing mining approaches, which may cause problems such as redundant computation, high time complexity, and large storage space. Based on this argument, a novel heuristic approach called PASS (Pre-processing based on Small Sample) has been proposed for finding a small sample composed of the most frequent transactions in big data pre-processing. Taking advantage of the cloud computing which can solve the bottleneck of data mining in distributed environment, PASS directly operates on the transaction database and groups all transactions according to different dimensions. By using the Bitmap-Sort, the most frequent transactions can be screened from each transaction set. Finally, the best-transaction-set is obtained through aggregating all the transaction-elects of each transaction set. The experimental results have shown that PASS significantly avoids producing plenty of candidate sets resulting from join operation, accelerates the maximal frequent itemsets mining, economizes the storage space, and improves the utilization rate of resources simultaneously.
Performance-improved computation of very large word-length LNS addition/subtraction using signed-digit arithmetic

Pipelined computation of very large word-length LNS addition/subtraction requires a significant amount of hardware and long pipeline latency. We propose a base-e exponential algorithm to simplify the exponential computation and to replace half of the pipeline stages by multiplication-and-accumulate operations. By using this approach, the circuit cost of the previously proposed 64 bit pipelined LNS addition/subtraction unit can be reduced by more than fifty percent. We also developed signed-digit (SD) algorithms to further enhance the performance of the LNS computation. From our analysis, the throughput of the 64 bit LNS unit can be increased by a factor of 4.62, and the pipeline latency can be reduced by a factor of seven. Furthermore, this SD approach can still save more than 50% of the table size and 27.6% of the circuit of the previously proposed LNS unit. The proposed approaches and algorithms have been verified by comprehensive simulations on the designed 32 bit SD hardware-reduced LNS unit. We have concluded that the proposed approaches can significantly improve the performance of very large word-length LNS addition/subtraction computation.
Characterizing TDP-43 interaction with its RNA targets

One of the most important functional features of nuclear factor TDP-43 is its ability to bind UG-repeats with high efficiency. Several cross-linking and immunoprecipitation (CLIP) and RNA immunoprecipitation-sequencing (RIP-seq) analyses have indicated that TDP-43 in vivo can also specifically bind loosely conserved UG/GU-rich repeats interspersed by other nucleotides. These sequences are predominantly localized within long introns and in the 3′UTR of various genes. Most importantly, some of these sequences have been found to exist in the 3′UTR region of TDP-43 itself. In the TDP-43 3′UTR context, the presence of these UG-like sequences is essential for TDP-43 to autoregulate its own levels through a negative feedback loop. In this work, we have compared the binding of TDP-43 with these types of sequences as opposed to perfect UG-stretches. We show that the binding affinity to the UG-like sequences has a dissociation constant (Kd) of ∼110 nM compared with a Kd of 8 nM for straight UGs, and have mapped the region of contact between protein and RNA. In addition, our results indicate that the local concentration of UG dinucleotides in the CLIP sequences is one of the major factors influencing the interaction of these RNA sequences with TDP-43.
Using audio and video features to classify the most dominant person in a group meeting

The automated extraction of semantically meaningful information from multi-modal data is becoming increasingly necessary due to the escalation of captured data for archival. A novel area of multi-modal data labelling, which has received relatively little attention, is the automatic estimation of the most dominant person in a group meeting. In this paper, we provide a framework for detecting dominance in group meetings using different audio and video cues. We show that by using a simple model for dominance estimation we can obtain promising results.
Effects of Response-Driven Feedback in Computer Science Learning

This paper presents the results of a project on generating diagnostic feedback for guided learning in a first-year course on programming and a Master's course on software quality. An online multiple-choice questions (MCQs) system is integrated with neural network-based data analysis. Findings about how students use the system suggest that the feedback is effective in addressing the level of knowledge of the individual and guiding him/her toward a greater understanding of particular concepts. In contrast, there is no evidence that learning required in programming problems, where students develop higher-level thinking according to Bloom's taxonomy, was exercised by using MCQs.
Outlier Analysis and Top Scoring Pair for Integrated Data Analysis and Biomarker Discovery

Pathway deregulation has been identified as a key driver of carcinogenesis, with proteins in signaling pathways serving as primary targets for drug development. Deregulation can be driven by a number of molecular events, including gene mutation, epigenetic changes in gene promoters, overexpression, and gene amplifications or deletions. We demonstrate a novel approach that identifies pathways of interest by integrating outlier analysis within and across molecular data types with gene set analysis. We use the results to seed the top-scoring pair algorithm to identify robust biomarkers associated with pathway deregulation. We demonstrate this methodology on pediatric acute myeloid leukemia (AML) data. We develop a biomarker in primary AML tumors, demonstrate robustness with an independent primary tumor data set, and show that the identified biomarkers also function well in relapsed pediatric AML tumors.