Miracle-dz/UniFAR-FTUs huggingface dataset:
Crystal Structures of the Dab Homology Domains of Mouse Disabled 1 and 2*

Disabled (Dab) 1 and 2 are mammalian homologues of Drosophila DAB. Dab1 is a key cytoplasmic mediator in Reelin signaling that controls cell positioning in the developing central nervous system, whereas Dab2 is an adapter protein that plays a role in endocytosis. DAB family proteins possess an amino-terminal DAB homology (DH) domain that is similar to the phosphotyrosine binding/phosphotyrosine interaction (PTB/PI) domain. We have solved the structures of the DH domains of Dab2 (Dab2-DH) and Dab1 (Dab1-DH) in three different ligand forms, ligand-free Dab2-DH, the binary complex of Dab2-DH with the Asn-Pro-X-Tyr (NPXY) peptide of amyloid precursor protein (APP), and the ternary complex of Dab1-DH with the APP peptide and inositol 1,4,5-trisphosphate (Ins-1,4,5-P3, the head group of phosphatidylinositol-4,5-diphosphate (PtdIns-4,5-P2)). The similarity of these structures suggests that the rigid Dab DH domain maintains two independent pockets for binding of the APP/lipoprotein receptors and phosphoinositides. Mutagenesis confirmed the structural determinants specific for the NPXY sequence and PtdIns-4,5-P2 binding. NMR spectroscopy confirmed that the DH domain binds to Ins-1,4,5-P3 independent of the NPXY peptides. These findings suggest that simultaneous interaction of the rigid DH domain with the NPXY sequence and PtdIns-4,5-P2 plays a role in the attachment of Dab proteins to the APP/lipoprotein receptors and phosphoinositide-rich membranes.
Using “Standardized Narratives” to Explore New Ways to Represent Faculty Opinions of Resident Performance

Purpose Most efforts to develop reliable evaluations of clinical competence have been oriented toward deconstructing the requisite competencies into separate scales. However, many are questioning the value of this approach on theoretical and empirical bases. This study uses “standardized narratives” to explore a different approach to assessing resident performance. Method In 2009, based on interviews with 19 experienced clinical faculty from two institutions, 16 narrative profiles were created to represent the range of resident competence that clinical faculty might encounter during supervision. Fourteen clinicians from three institutions independently grouped the profiles into as many categories as necessary to reflect various levels of performance, described their categories, then ranked the individual profiles within each category. Then, in groups of three or four, participants negotiated a final ranking and grouping of the 16 profiles. Results Despite interesting idiosyncracies in the factors some participants identified as guiding their rankings, there was strong consistency across the 14 clinicians regarding the rankings (single-rater intraclass correlation [ICC] = 0.86) and groupings (single-rater ICC = 0.81) of the profiles. Similarly, across institutions, the four groups were highly consistent in their final negotiated rankings (single-group ICC = 0.91) and groupings (single-group ICC = 0.87) of the profiles. Conclusions Faculty showed more consistency in their decisions of what constitutes excellent, competent, and problematic performance in residents than implied by current assessment techniques that require deconstruction of resident competencies. This use of standardized narratives points to interesting opportunities for more authentically codifying faculty opinions of residents.
Blind Nonnegative Source Separation Using Biological Neural Networks

Blind source separation—the extraction of independent sources from a mixture—is an important problem for both artificial and natural signal processing. Here, we address a special case of this problem when sources (but not the mixing matrix) are known to be nonnegative—for example, due to the physical nature of the sources. We search for the solution to this problem that can be implemented using biologically plausible neural networks. Specifically, we consider the online setting where the data set is streamed to a neural network. The novelty of our approach is that we formulate blind nonnegative source separation as a similarity matching problem and derive neural networks from the similarity matching objective. Importantly, synaptic weights in our networks are updated according to biologically plausible local learning rules.
A novel half-bridge LLC Resonant Converter for high power DC power supply

A novel half-bridge LLC DC-DC Resonant Converter for high power DC power supply is presented in this paper. The design consideration of resonant tank circuit paramerters are presented. The DC gain characteristics of the proposed converter is analyzed from its complex DC gain equation. First the performance of the converter is analyzed through simulation. The proposed converter operate with higher frequency of operation and from the light load to full load point in characteristics ZVS/ZCS (zero voltage switching/zero current switching) turn on and low current turn off is achieved in variable frequency open-loop control range. An experimental prototype of 2.1 kW has been built according to the parameters consideration and calculated tank circuit parameters. Variable frequency control is implemented through DSP for the regulation of output voltage in open-loop. The converter maintains ZVS in the entire range of open-loop control from 5 to 15 kHz.
The Direction of the Double Standard : Are Norms Stricter for Men or for Women ?

We examined double standards in norms concerning voluntary childlessness. Whether the choice to remain childless is more accepted for men or women is not a priori clear; we formulated hypotheses in both directions. Parenthood might be considered as more central to women’s identity than to men’s, resulting in higher disapproval of childlessness for women. Yet, as the costs of parenthood are higher for women, people might also be more accepting of their choice to remain childless and disapprove more of childless men. Multilevel analyses were conducted, including individual and societal-level variables. Our sample consisted of N1⁄4 44,055 individuals nested in 25 European countries, obtained from the third round of the European Social Survey (2006). Subjective norms regarding voluntary childlessness were measured with a split-ballot design: half of the respondents were randomly assigned items regarding women choosing childlessness, and the other half was assigned items regarding men. Findings indicated that men were more disapproved of when choosing not to have children than women. Generally, this double standard was endorsed by women, not by men. Clear cross-national variation in the double standard existed, which was partly explained by the level of gender equality. We found that higher levels of gender equality were associated with larger double standards favouring women.
A Real-time Audio-to-audio Karaoke Generation System for Monaural Recordings Based on Singing Voice Suppression and Key Conversion Techniques

This paper describes an automatic karaoke generation system, which can suppress the singing voice in audio music signals, and can also change the pitch of the song. Furthermore, this system accepts the streaming input, and it works in real-time. To the best of our knowledge, there have been no real-time audio-to-audio karaoke system that has the two functions above. This paper particularly describes the two technical components, as well as some comments on the implementation. In this system, the authors employed two signal processing techniques: singing voice suppression that is based on two-stage HPSS, a vocal enhancement technique that the authors proposed previously, and a pitch shift technique that is based on the spectrogram stretch and phase vocoder. The attached video file shows that the system works in real-time, and the sound quality may be practically acceptable.
Multi-Objective Gene Expression Programming for Clustering

This paper proposes a multi-objective gene expression programming for clustering (MGEPC), which could automatically determine the number of clusters and the appropriate partitioning from the data set. The clustering algebraic operations of gene expression programming are extended first. Then based on the framework of the Non-dominated Sorting Genetic Algorithm-II, two enhancements are proposed in MGEPC. First, a multi-objective k-means clustering is proposed for local search, where the total symmetrical compactness and the cluster connectivity are used as two complementary objectives and the point symmetry based distance is adopted as the distance metric. Second, the power-law distribution based selection strategy is proposed for the parent population generation. In addition, the external archive and the archive truncation are used to keep a historical record of the non-dominated solutions found along the search process. Experiments are performed on five artificial and three real-life data sets. Results show that the proposed algorithm outperforms the PESA-II based clustering method (MOCK), the archived multiobjective simulated annealing based clustering technique with point symmetry based distance (VAMOSA) and the single-objective version of gene expression programming based clustering technique (GEP-Cluster). DOI: http://dx.doi. org/10.5755/j01.itc. 41.3. 1330
Changes in biomass carbon stocks in China's grasslands between 1982 and 1999

Terrestrial ecosystems in the northern latitudes are significant carbon sinks for atmospheric CO2; however, few studies come from grassland ecosystems. Using national grassland resource inventory data, NDVI (normalized difference vegetation index) time series data set, and a satellite‐based statistical model, this study identifies changes in the size and distribution of aboveground biomass carbon (C) stocks for China's grasslands between 1982 and 1999. Biomass C stocks averaged 145.4 Tg C for the study period for a total area of 334.1 × 104 km2, and have increased by 17.7 Tg C (1 Tg = 1012 g) from 136.3 Tg C in the early 1980s (average of 1982–1984) to 154.0 Tg C in the late 1990s (average of 1997–1999), with an annual increase of 0.7%. This suggests that the aboveground biomass of China's grasslands may have functioned as the C sinks in the past 2 decades. Assuming a constant ratio of aboveground to belowground biomass for each grassland type, we also estimated belowground biomass C and its change over time for each grassland type, generating an average estimate of 1051.1 Tg C for the total (aboveground and belowground) biomass C and an annual increase of 126.67 Tg C for China's grasslands over the 18 years. However, the accuracy of these estimates has limitations due primarily to uncertainties in estimates of belowground C, biomass inventories, and satellite time series data sets.
Automatic Heliothis zea classification using image analysis

We present the design and implementation of an image analysis system for the automatic analysis of Heliothis zea insect images. The Heliothis zea is a corn earworm eating corn crops. Biotech researchers are interested in developing insecticidal bio-toxins with the best performance to kill or stunt the growth of this insects. The automated analysis of Heliothis zea images is imperative for fast and efficient biotech experiments. The proposed system consists of three stages: (i) insect segmentation, (ii) region processing, and (iii) instar and life classification. A probabilistic model (PM) based on mixtures of Gaussians has shown better performance for segmenting the insect images. And a back-propagation neural network (NN) has shown better performance for classifying the insect instar stage. The proposed system has been evaluated on real data using a fivefold cross validation procedure.
Preventive Effect of Maternal Forced Exercise on Offspring Pain Perception and Intensity: The Role of 5-HT2 and D2 Receptors

Background: Many previous studies showed that maternal forced exercise can reduce some central disorders in offsprings, but its clear mechanism remains unclear. In this study, the role of 5-HT2 and D2 receptors in neuroprotective effects of maternal forced exercise in offspring neurodevelopment and effect on some behaviors were evaluated. Materials and Methods: Forty-eight pregnant rats were trained by forced exercise, and some behavioral assays in their offspring were performed in the presence and absence of 5-HT2 and D2 receptor antagonists in various experimental groups. Results: Our data showed that maternal forced exercise caused increase in latency of pain perception in offsprings in hot plate test, writhing test (WT), and tail flick test. Furthermore, a decrease in intensity was shown by WT. On the other hand, treatment of mothers by forced exercise in combination with 5-HT2 and D2 receptor antagonists could inhibit these effects of forced exercise and cause disturbances in pain perception and intensity. Conclusion: Our data suggested that maternal forced exercise causes protective effects on offspring pain perception and intensity, and in this effect, 5-HT2 and D2 receptors are probably involved.
Sets of RNA Repeated Tags and Hybridization-Sensitive Fluorescent Probes for Distinct Images of RNA in a Living Cell

Background Imaging the behavior of RNA in a living cell is a powerful means for understanding RNA functions and acquiring spatiotemporal information in a single cell. For more distinct RNA imaging in a living cell, a more effective chemical method to fluorescently label RNA is now required. In addition, development of the technology labeling with different colors for different RNA would make it easier to analyze plural RNA strands expressing in a cell. Methodology/Principal Findings Tag technology for RNA imaging in a living cell has been developed based on the unique chemical functions of exciton-controlled hybridization-sensitive oligonucleotide (ECHO) probes. Repetitions of selected 18-nucleotide RNA tags were incorporated into the mRNA 3′-UTR. Pairs with complementary ECHO probes exhibited hybridization-sensitive fluorescence emission for the mRNA expressed in a living cell. The mRNA in a nucleus was detected clearly as fluorescent puncta, and the images of the expression of two mRNAs were obtained independently and simultaneously with two orthogonal tag–probe pairs. Conclusions/Significance A compact and repeated label has been developed for RNA imaging in a living cell, based on the photochemistry of ECHO probes. The pairs of an 18-nt RNA tag and the complementary ECHO probes are highly thermostable, sequence-specifically emissive, and orthogonal to each other. The nucleotide length necessary for one tag sequence is much shorter compared with conventional tag technologies, resulting in easy preparation of the tag sequences with a larger number of repeats for more distinct RNA imaging.
DIGITAL MEDIA AND THE GENERATION GAP

In many parts of the developed world, families engage with a wide range of communication media as a part of their daily lives. Parents often express mixed feelings about this engagement on the part of young people, however. Employing Baumberg's narrative-in-interaction analysis to interviews with 55 parents and 125 young people, this article explores both the discursive strategies parents employ when discussing their rules and regulations regarding digital technologies, and the strategies employed by their teenage young people in response. It considers how parents attempt to articulate authority in relation to digital media use among their teenage children, and how the ways in which teens interpret those parental attempts to express authority influence the strategies they themselves embrace regarding digital media. The article argues that although economically disadvantaged families experience the digital generation gap with particular intensity, their strategies reveal that they and their teenage children are able to deal with these challenges in creative and effective ways.
Visibility Versus Complexity in Business Groups: Evidence from Japanese Keiretsu

In this article, we examine the potential for external conflicts in large, diversified business groups. On the one hand, these highly visible groups facilitate the detection of opportunistic actions. Accordingly, reputational concerns should effectively constrain group behavior. On the other hand, these groups' complexities hinder outsiders from unveiling group strategies from among a myriad of transactions. This complexity limits the power of reputational concerns to constrain actions. Using data on initial public offer initial returns, we evaluate the trade-off between visibility and complexity. The evidence suggests that complexity dominates visibility, providing scope for opportunistic behavior against outside investors. Copyright 2001 by University of Chicago Press.
Response to Comment by Ayubi and Safiri. Insulin Resistance Predicts Cognitive Decline: An 11-Year Follow-up of a Nationally Representative Adult Population Sample. Diabetes Care 2017;40:751–758

We thank Drs. Ayubi and Safiri for their comments (1) on our article (2). First, they pointed out that because baseline measurements, instead of repeated measurements, of insulin resistance (IR), insulin, and glucose were used to evaluate associations between these risk factors and cognitive decline, the results might not be accurate because of regression dilution bias and collinearity. It is true that we did not have access to repeated measurements of IR, insulin, and glucose during the follow-up time, which is why we could not account for within-person variability in our analyses nor answer the question asked by Ayubi and Safiri (1): “Is there an …
Evolutionary sequences of irrotational binary neutron stars

We present results of numerical computations of quasiequilibrium sequences of binary neutron stars with zero vorticity, in the general relativistic framework. The Einstein equations are solved under the assumption of a conformally flat spatial 3-metric (Wilson-Mathews approximation). The evolution of the central density of each star is monitored as the orbit shrinks in response to gravitational wave emission. For a compactification ratio M/R=0.14, the central density remains rather constant (with a slight increase, below 0.1%) before decreasing. For a higher compactification ratio M/R=0.17 (i.e. stars closer to the maximum mass configuration), a very small density increase (at most 0.3%) is observed before the decrease. This effect remains within the error induced by the conformally flat approximation. It can be thus concluded that no substantial compression of the stars is found, which would have indicated a tendency to individually collapse to black hole prior to merger. Moreover, no turning point has been found in the binding energy or angular momentum along evolutionary sequences, which may indicate that these systems do not have any innermost stable circular orbit (ISCO).
Backdoor Detection System Using Artificial Neural Network and Genetic Algorithm

In this paper, we consider the issue of detecting a missing member of malicious codes named backdoors. We developed a novel approach for revealing them based on two clustered, system behavior and network traffic. Backdoors can easily be installed on the victim system aiming its exploit, detecting them requires considerable policies. Using Artificial Intelligence (AI) has revolutionized all security providing systems. Hence, our proposed method acquired a tunable idea using Artificial Neural Network (ANN) for classifying system features and predicting the percentage of backdoor existing probability and Genetic Algorithm (GA) in order to give a deterministic answer to the issue. Using ANN incorporation with the GA guarantees how precise our approach could be.
Multiparameter Respiratory Rate Estimation From the Photoplethysmogram

We present a novel method for estimating respiratory rate in real time from the photoplethysmogram (PPG) obtained from pulse oximetry. Three respiratory-induced variations (frequency, intensity, and amplitude) are extracted from the PPG using the Incremental-Merge Segmentation algorithm. Frequency content of each respiratory-induced variation is analyzed using fast Fourier transforms. The proposed Smart Fusion method then combines the results of the three respiratory-induced variations using a transparent mean calculation. It automatically eliminates estimations considered to be unreliable because of detected presence of artifacts in the PPG or disagreement between the different individual respiratory rate estimations. The algorithm has been tested on data obtained from 29 children and 13 adults. Results show that it is important to combine the three respiratory-induced variations for robust estimation of respiratory rate. The Smart Fusion showed trends of improved estimation (mean root mean square error 3.0 breaths/min) compared to the individual estimation methods (5.8, 6.2, and 3.9 breaths/min). The Smart Fusion algorithm is being implemented in a mobile phone pulse oximeter device to facilitate the diagnosis of severe childhood pneumonia in remote areas.
Predicting the Audience Size of a Tweet

We study information dissemination in Twitter. We present an analysis of two important characteristics of so called retweet cascades: retweet count and show count, i.e., number of users that receive the tweet in their feed. We show that these two measures behave differently. We describe three models that are aimed to predict the audience size of a tweet: first one utilizes only the data available at the moment of the initial tweet, the second one utilizes the spread of the cascade up to some moment while the third one is an online prediction.
Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion

Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error).
A Composition Methodology for Designing Proactive Distributed Protocols

The development of methodologies for the design of distributed protocols is essential to reducing the complexity and difficulty of creating distributed systems, as well as for maturing the field. This paper presents a composition methodology for designing a range of proactive distributed protocols, with applicability to large-scale distributed systems in both the Internet (e.g., peer to peer systems) and wireless sensor networks. The methodology consists of several basic building blocks and different composition techniques which can be used to combine the blocks into solutions for distributed computing problems. The compositions preserve properties of the original components (reliability, scalability, liveness). Next, we describe a simple specification language called “Proactive Protocol Composition Language (PPCL)” which can be used to specify and compose existing source (C language) code of building block implementations in order to automate the above design methodology. We discuss how the methodology and the toolkit generated by PPCL are (i) retroactive, i.e., can generate protocols already existing in literature, and (ii) progressive, i.e., can generate new protocols. For an important distributed computing problem (membership management in large groups), we give experimental data to compare (i) a generated protocols with a hand-written protocol, and (ii) an existing protocol with an augmentation realized through PPCL.