Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Evaluation of LDA , CCA and AAM 1

Wouldn't we love to replace passwords access control to avoid theft, forgotten passwords? Wouldn't we like to enter the security areas just in seconds? Yes the answer is face recognition. In this study we explore and compare the performance of three algorithms namely LDA, CCA, AAM. LDA (an evolution of PCA is a dimensionality reduction technique where it solves the problem of illumination to some extent, maximizing the inter class separation and minimizing the intra class variations. CCA, a measure of linear relationship between two multidimensional variables where it takes the advantage of PCA and LDA for maximizing the correlation and better performance. AAM is a model based approach where it just picks the landmarks of the images for recognition therefore reducing the error rate and producing good performance rate.
Study on wettability and corrosivity of a new no-clean flux for lead-free solder paste in electronic packaging technology

Solder paste plays a critical role in SMT (surface mount technology) and reflow soldering. And flux is an important material in composition of solder paste. Due to the drive towards lead-free electronic packaging and no-clean soldering technology, a new no-clean flux contained composite activators was formulated specifically for lead-free paste. Spread test was carried out to evaluate the activity of the newly developed flux with Sn3.0Ag0. 5Cu lead-free solder. Influence of flux residues on corrosivity of cu substrate was also investigated. The results showed that the new no-clean flux contained composite activators exhibited better soldering performance. Corrosivity of flux residues related to activators in fluxes. The new no-clean flux contained composite activators had less residues and minor corrosivity than flux which contained simple activators of organic acids. Therefore, composite activators are promising no-clean flux ingredients for lead-free solder paste.
1 Frequency-Dependent Regulation of the Cardiac Na +-Ca 2 + Exchanger

The activity of the cardiac Na +-Ca 2+ exchanger (NCX1.1) undergoes continuous modulation during the contraction/relaxation cycle due to the accompanying changes in the electrochemical gradients for Na + and Ca 2+. In addition, NCX1.1 activity is also modulated via secondary, ionic regulatory mechanisms mediated by Na + and Ca 2+. In an effort to evaluate how ionic regulation influences exchange activity under pulsatile conditions, we studied the behaviour of the cloned NCX1.1 during frequency-controlled changes in Na + i and Ca 2+ i. Na +-Ca 2+ exchange activity was measured using the giant, excised patch clamp technique with conditions chosen to maximize the extent of Na +-and Ca 2+-dependent ionic regulation so that the effects of variables such as pulse frequency and duration could be optimally discerned. We demonstrate that increasing the frequency or duration of solution pulses leads to a progressive decline in pure outward, but not pure inward, Na +-Ca 2+ exchange current. However, when the exchanger is permitted to alternate between inward and outward transport modes, both current modes exhibit substantial levels of inactivation. Changes in regulatory Ca 2+ , or exposure of patches to limited proteolysis by α-chymotrypsin, reveal that this " coupling " is due to Na +-dependent inactivation originating from the outward current mode. Under physiological ionic conditions, however, evidence for modulation of exchange currents by Na + i-dependent inactivation was not apparent. The current approach provides a novel means for assessment of Na +-Ca 2+ exchange ionic regulation that may ultimately prove useful towards understanding its role under physiological and pathophysiological conditions.
Unique haplotypes in ant-attended aphids and widespread haplotypes in non-attended aphids

Aphid species within the genus Tuberculatus Mordvilko (Hemiptera: Aphididae) exhibit a variety of interactions with ants, ranging from close associations to non-attendance. A previous study indicated that despite wing possession, ant-attended Tuberculatus species exhibited low dispersal rates compared with non-attended species. This study examined if presence or absence of mutualistic interactions and habitat continuity of host plants affected intraspecific genetic diversity and genetic differentiation in mitochondrial DNA cytochrome oxidase I (COI) sequences. Sympatric ant-attended Tuberculatus quercicola (Matsumura) (Hemiptera: Aphididae) and non-attended Tuberculatus paiki Hille Ris Lambers (Hemiptera: Aphididae) were collected from the daimyo oak Quercus dentata Thunberg (Fagales: Fagaceae) in Japan and examined for haplotype variability. Seventeen haplotypes were identified in 568 T. quercicola individuals representing 23 populations and seven haplotypes in 425 T. paiki representing 19 populations. Haplotype diversity, which indicates the mean number of differences between all pairs of haplotypes in the sample, and nucleotide diversity were higher in T. quercicola than T. paiki. Analysis of molecular variance (AMOVA) showed higher genetic differentiation among populations within groups of T. quercicola (39.8%) than T. paiki (22.6%). The effects of attendant ant species on genetic differentiation in T. quercicola were not distinguishable from geographic factors. Despite low dispersal rates, host plant habitat continuity might facilitate widespread dispersal of a T. quercicola haplotype in Hokkaido. These results suggested that following T. quercicola colonization, gene flow among populations was limited, resulting in genetic drift within populations. However, frequent T. paiki dispersal is clearly evident by low genetic differentiation among populations within groups, resulting in lower haplotype diversity.
The Oxford Handbook of Cognitive and Behavioral Therapies

1. Introduction Christine Maguth Nezu and Arthur M. Nezu Part One: Conceptual Foundations 2. Historical and Philosophical Dimensions of Contemporary Cognitive Behavior Therapy William T. O'Donohue, and Kyle Edward Ferguson 3. Core Competencies in Cognitive Behavioral Interventions Christine Maguth Nezu, Sarah Ricelli, and Arthur M. Nezu 4. Behavioral Assessment and the Functional Analysis William H. O'Brien, Stephen N. Haynes, and Joseph Keawe'aimoku Kaholokula 5. Case Formulation for the Cognitive and Behavioral Therapies: A Problem-Solving Approach Christine Maguth Nezu, Arthur M. Nezu, Sarah Ricelli, and Jessica B. Stern Part Two: Major Cognitive and Behavioral Therapy Approaches 6. Applied Behavior Analysis Raymond G. Miltenberger, Bryon G. Miller, and Heather M. Zerger 7. Exposure-based Interventions for Adult Anxiety Disorders, OCD, and PTSD Seth J. Gillihan and Edna B. Foa 8. Cognitive Restructuring/Cognitive Therapy Cory F. Newman 9. Rational Emotive Behavior Therapy Monica E. O'Kelly and James J. Collard 10. Contemporary Problem-solving Therapy: A Transdiagnostic Intervention Arthur M. Nezu, Alexandra P. Greenfield, and Christine Maguth Nezu 11. Mindfulness- and Acceptance-Based Cognitive and Behavioral Therapies Susan M. Orsillo, Sara B. Danitz, and Lizabeth Roemer 12. Dialectical Behavior Therapy: A Comprehensive Multi- and Trans-diagnostic Intervention Anita Lunga and Marsha M. Linehan 13. Relapse Prevention Katie Witkiewitz and Megan Kirouac 14. Behavioral Activation Derek R. Hopko, Marlene M. Ryba, Crystal McIndoo, and Audrey File 15. Cognitive-Behavioral Approaches to Stress Management Sarah L. Mann and Richard J. Contrada Part Three: Major Psychological Problems and Populations 16. Adult Anxiety and Related Disorders Jaqueline Bullis and Stefan G. Hofmann 17. Adult Mood Disorder: The Case of Major Depressive Disorder C. Steven Richards 18. Cognitive Behavioral Interventions in Psychosis Elizabeth Kuipers, Suzanne Jolley, and Juliana Onwumere 19. Cognitive Behavioral Therapies in Older Adult Populations Michele M. Braun, Bradley E. Karlin, and Antonette M. Zeiss 20. Treating Children and Adolescents Philip C. Kendall, Jeremy S. Peterman, Marianne A. Villabo, Matthew Mychailyszyn, and Kelley A. O'Neil Rodriguez 21. Couple Therapy Kristina Coop Gordon, Katie Wischkaemper, and Lee J. Dixon 22. Intellectual Disability James K. Luiselli 23. Delivery, Evaluation, and Future Directions for Cognitive Behavioral Treatments of Obesity Gareth R. Dutton and Michael G. Perri 24. Personality Disorders Mary McMurran and Mike J. Crawford Part Four: Special Topics 25. Multicultural Issues in Cognitive-Behavioral Therapy Gordon C. Nagayama Hall and Alicia Yee Ibaraki 26. Combination Treatment for Anxiety and Mood Disorders: Benefits and Issues for the Combination of CBT and Pharmacotherapy Michael W. Otto and Bridget A. Hearon
An Improvement of the PEG Algorithm for LDPC Codes in the Waterfall Region

There exist many different algorithms to construct good low-density parity-check (LDPC) codes. To maximize the girth of the bipartite graph, which represents the LDPC code, the progressive edge-growth (PEG) algorithm was introduced. This construction methods leads for irregular LDPC codes to a lower error floor, but also to a performance loss in the waterfall region compared with randomly constructed LDPC codes. In this paper, we describe a modification of the PEG algorithm that improves the performance in the waterfall region. Furthermore, this modified PEG algorithm yields codes with lower error floors and a slightly better performance in the waterfall region than randomly constructed LDPC codes
Localization of an unmanned ground vehicle using 3D registration of laser range data and DSM

Localization of an unmanned ground vehicle (UGV) is a very important task for autonomous vehicle navigation. In this paper, we propose a computer vision technique to identify the location of an outdoor UGV. The proposed technique is based on 3D registration of 360 degree laser range data to a digital surface model (DSM). A long sequence of range frames is obtained from a rotating range sensor which is mounted on the top of the vehicle. Two novel approaches are proposed for accurate 3D registration of range data and the DSM. First, registration is done between range frames in a pair-wise manner followed by a refinement with the DSM. Second, we divide the DSM to several layers and find correspondences near the current vehicle elevation. This reduces the number of outliers and facilitates fast localization. Experimental results show that the proposed approaches yield better performance in 3D localization compared to conventional 3D registration techniques. Error analysis on four outdoor paths is presented with respect to ground truth.
Jak-TGFβ cross-talk links transient adipose tissue inflammation to beige adipogenesis

Transient inflammation in adipose tissue triggers Jak-TGFβ signaling to promote beige adipocyte differentiation. Committing progenitors to adipogenesis Promoting the “browning” of white fat has been proposed as a strategy to combat obesity. Beige adipocytes, which are intermediate between fat-storing white adipocytes and thermogenic brown adipocytes, can emerge from the differentiation of adipocyte progenitors in adipose tissue in response to β3-adrenergic stimulation. Using primary human and mouse cells and ex vivo mouse models, Babaei et al. (see also the Focus by Sun et al.) found that the Jak family of kinases promoted the commitment of adipocyte progenitors to beige adipogenesis. Through the downstream transcription factor Stat3, Jak inhibited TGFβ signaling and prevented adipocyte progenitors from differentiating into smooth muscle cells. β3-Adrenergic stimulation of lipolysis, which transiently triggers inflammation, induced the production of the cytokines IL-6 and IL-11, which activated the Jak/Stat3 pathway. These results delineate a pathway that is activated by transient inflammation in adipose tissue that steers adipocyte progenitors toward differentiation into a thermogenically active form of fat. The transient activation of inflammatory networks is required for adipose tissue remodeling including the “browning” of white fat in response to stimuli such as β3-adrenergic receptor activation. In this process, white adipose tissue acquires thermogenic characteristics through the recruitment of so-called beige adipocytes. We investigated the downstream signaling pathways impinging on adipocyte progenitors that promote de novo formation of adipocytes. We showed that the Jak family of kinases controlled TGFβ signaling in the adipose tissue microenvironment through Stat3 and thereby adipogenic commitment, a function that was required for beige adipocyte differentiation of murine and human progenitors. Jak/Stat3 inhibited TGFβ signaling to the transcription factors Srf and Smad3 by repressing local Tgfb3 and Tgfb1 expression before the core transcriptional adipogenic cascade was activated. This pathway cross-talk was triggered in stromal cells by ATGL-dependent adipocyte lipolysis and a transient wave of IL-6 family cytokines at the onset of adipose tissue remodeling induced by β3-adrenergic receptor stimulation. Our results provide insight into the activation of adipocyte progenitors and are relevant for the therapeutic targeting of adipose tissue inflammatory pathways.
Microfabricated mechanical biosensor with inherently differential readout

We report measurements with a micromachined mechanical biosensor that inherently suppresses background effects by producing a differential signal with respect to a reference. The sensor comprises two adjacent cantilevers with interdigitated fingers between them that allow interferometric detection of the differential, i.e., relative bending. We demonstrate that differential detection can efficiently suppress unspecific chemical effects that result in cantilever bending. We show that the differential deflection noise is up to an order of magnitude lower than the absolute deflection noise in the low-frequency range of 0.0003–1 Hz, where many types of biologically relevant reactions occur. We also demonstrate the sensor’s applicability to biological receptor–ligand systems by reporting experimental results on direct differential detection of biotin–streptavidin binding.
Source contributions to Northern Hemisphere CO and black carbon during spring and summer 2008 from POLARCAT and START08/preHIPPO observations and MOZART-4

Anthropogenic pollution and wildfires are main producers of carbon monoxide (CO) and black carbon (BC) in the Northern Hemisphere. High concentrations of these compounds are transported into the Arctic troposphere, influencing the ecosystem in high northern latitudes and the global climate. The global chemical transport model MOZART-4 is used to quantify the seasonal evolution of the contribution of CO and BC from different source regions in spring and summer 2008 by tagging their emissions. Aircraft observations from the POLARCAT experiments, in particular NASA ARCTAS, NOAA ARCPAC, POLARCAT-France, DLR GRACE and YAK-AEROSIB, as well as the NSF START08/preHIPPO experiments during Spring-Summer 2008 are combined to quantify the representation of simulated tracer characteristics in anthropogenic and fire plumes. In general, the model reproduces CO and BC well. Based on aircraft measurements and FLEXPART back-trajectories, the altitude contribution of emissions coming from different source regions is well captured in the model. Uncertainties of the MOZART-4 model are identified by comparing the data with model results on the flight tracks and using MOPITT satellite observations. Anthropogenic emissions are underestimated by about 10% in high northern latitudes in spring, and shortcomings exist in simulating fire plumes. The remote impact of East-Siberian fire emissions is underestimated for spring, whereas the impact of Southeast Asian fire emissions to mid-latitude CO values is overestimated by the model. In summer, mid-latitude CO values agree well between model and observations, whereas summer high latitude East-Siberian fire emissions in the model are overestimated by 20% in comparison to observations in the region. On the other hand, CO concentrations are underestimated by about 30% over Alaska and Canada at altitudes above 4 km. BC values are overestimated by the model at altitudes above 4 km in summer. Based on MOZART-4, with tagged CO and BC tracers, anthropogenic emissions of Asia, Europe and the US have the largest contribution to the CO and BC in mid- and high latitudes in spring and summer. Southeast Asian, Chinese and Indian fires have a large impact on CO pollution in spring in low latitudes with a maximum between 20° and 30°, whereas Siberian fires contribute largely to the pollution in high latitudes, up to 10% in spring and up to 30% in summer. The largest contributions to BC values in high latitudes are from anthropogenic emissions (about 70%). CO and BC have larger mass loadings in April than in July, as a result of photochemistry and dynamics.
Hessian based image structure adaptive gradient vector flow for parametric active contours

Active contours have been one of the most successful methods for image segmentation during the last two decades, but one of the shortcomings of being unable to converge to concavity is a handicap to its effectiveness. In order to address this issue, the gradient vector flow (GVF) was put forth. Although there have been a great number of works on GVF, the image structure has seldom been incorporated into GVF algorithm. In this work, the image structure characterized by the Hessian matrix is incorporated into the GVF algorithm by reformulating the smoothness constraint of GVF into matrix form. In this way, the associated diffusion PDEs are anisotropic and the modified GVF snake can converge to very long concavity and preserve weak edge simultaneously. Experiments and comparisons are presented to demonstrate the properties of the proposed strategies.
Community detection in social network with pairwisely constrained symmetric non-negative matrix factorization

Non-negative Matrix Factorization (NMF) aims to find two non-negative matrices whose product approximates the original matrix well, and is widely used in clustering condition with good physical interpretability and universal applicability. Detecting communities with NMF can keep non-negative network physical definition and effectively capture communities-based structure in the low dimensional data space. However some NMF methods in community detection did not concern with more network inner structures or existing ground-truth community information. In this paper, we propose a novel pairwisely constrained non-negative symmetric matrix factorization (PCSNMF) method, which not only consider symmetric community structures of undirected network, but also takes into consideration the pairwise constraints generated from some ground-truth group information to enhance the community detection. We compare our approaches with other NMF-based methods in three social networks, and experimental results for community detection show that our approaches are all feasible and achieve better community detection results.
Region annotations in hashing based image retrieval

During recent years, large-scale data has become more and more present in our daily life, requiring better, faster, and more effective ways to discriminate between unrelated content and what we are truly interested in. In particular, retrieving similar images is a fundamental problem in both image processing and computer vision. Since finding similar images high-dimensional image features is not feasible in practice, approximate hashing techniques have been proved very effective due to their great efficiency and reasonably accuracy. Current hashing methods focus on image as a whole. However, sometimes the relevant content might be just bounded to a region of interest while the background part seems to be needless for users. In this paper, we propose to exploit region-level annotations, whenever they are available, for both training supervised hashing methods and also in the query image. Our objective is to evaluate whether region-level features can be helpful in a supervised hashing scenario. Experimental results confirm that region-level annotations in both the query and training images increase the accuracy.
Overlapping Clustering Method Using Local and Global Importance of Feature Terms at NTCIR-4 WEB Task

In NTCIR-4 Web Task D (Topical Classification Task), we present an overlapping clustering method for a Japanese meta search engine as an alternative to a list of ranked retrieval results which most search engines adopt to present the retrieval results. The proposed method clusters the retrieval results dynamically according to the following two steps: (1) cluster labels consisting of the most important feature terms extracted from the retrieval results are generated first; then (2) each document is classified into one or more (i.e., overlapping) generated clusters based on its relevance to the feature term. The evaluation results showed that the proposed method in formal run achieved better retrieval effectiveness compared to the average of all the participants in Task D.
Facilitating Memory for Novel Characters by Reducing Neural Repetition Suppression in the Left Fusiform Cortex

Background The left midfusiform and adjacent regions have been implicated in processing and memorizing familiar words, yet its role in memorizing novel characters has not been well understood. Methodology/Principal Findings Using functional MRI, the present study examined the hypothesis that the left midfusiform is also involved in memorizing novel characters and spaced learning could enhance the memory by enhancing the left midfusiform activity during learning. Nineteen native Chinese readers were scanned while memorizing the visual form of 120 Korean characters that were novel to the subjects. Each character was repeated four times during learning. Repetition suppression was manipulated by using two different repetition schedules: massed learning and spaced learning, pseudo-randomly mixed within the same scanning session. Under the massed learning condition, the four repetitions were consecutive (with a jittered inter-repetition interval to improve the design efficiency). Under the spaced learning condition, the four repetitions were interleaved with a minimal inter-repetition lag of 6 stimuli. Spaced learning significantly improved participants' performance during the recognition memory test administered one hour after the scan. Stronger left midfusiform and inferior temporal gyrus activities during learning (summed across four repetitions) were associated with better memory of the characters, based on both within- and cross-subjects analyses. Compared to massed learning, spaced learning significantly reduced neural repetition suppression and increased the overall activities in these regions, which were associated with better memory for novel characters. Conclusions/Significance These results demonstrated a strong link between cortical activity in the left midfusiform and memory for novel characters, and thus challenge the visual word form area (VWFA) hypothesis. Our results also shed light on the neural mechanisms of the spacing effect in memorizing novel characters.
Framework for Evaluating Clustering Algorithms in Duplicate Detection

The presence of duplicate records is a major data quality concern in large databases. To detect duplicates, entity resolution also known as duplication detection or record linkage is used as a part of the data cleaning process to identify records that potentially refer to the same real-world entity. We present the Stringer system that provides an evaluation framework for understanding what barriers remain towards the goal of truly scalable and general purpose duplication detection algorithms. In this paper, we use Stringer to evaluate the quality of the clusters (groups of potential duplicates) obtained from several unconstrained clustering algorithms used in concert with approximate join techniques. Our work is motivated by the recent significant advancements that have made approximate join algorithms highly scalable. Our extensive evaluation reveals that some clustering algorithms that have never been considered for duplicate detection, perform extremely well in terms of both accuracy and scalability.