Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast transient frequency control voltage regulator using push-pull dynamic leaker circuit

A novel technique of fast transient response for frequency control voltage regulator is presented in this paper. For an embedded switched capacitor based DC-DC converter, poor transient response of frequency control voltage regulator is improved with the help of a push-pull dynamic leaker circuit. Push-pull dynamic leaker paths have been used to reduce both peak and dip at the output during load transient or line transient. Introduction of push pull dynamic leaker path in parallel with existing frequency control regulator also helps to reduce settling time drastically with marginal increment of static power loss. The proposed scheme is most suitable for digital applications, where load changes from minimum to maximum or vice-versa in few nanoseconds. The proposed dynamic leaker circuit is implemented with the frequency control voltage regulator in 0. 18μm CMOS process for 3.3V to 1.35V conversion. 10% settling time of the regulator is less than 10ns whereas peaks and dips are within 17% of regulated output for Ins load transient time.
Clustered pixels analysis for functional MRI activation studies of the human brain

Conventional t‐statistics and cross‐correlation coefficients are commonly used for analysis of functional magnetic resonance images. The sensitivity of these statistics is usually low because severe Bonferroni‐type corrections are required for multiple statistical comparisons to minimize the false‐positive error. In the human brain, most functional areas are larger in size than a single image pixel, and coactivation of numerous contiguous pixels is expected. The probability of occurrence of clusters due to random noise is small and can be modeled. Cluster size and intensity thresholding can be used to assess statistical significance. Previous cluster analysis strategies used Gaussian models, working best with low spatial resolution images (e.g., positron emission tomography). We present a new cluster analysis model applicable to data with little or even no covariance between adjacent pixels. Computer simulations and phantom experiments were used to verify this strategy. Our new method is substantially more sensitive than both the conventional intensity‐only thresholding (IOT) method and the previous cluster method for signal change less than 6%, with maximum significant enhancement in sensitivity of 12.8 and 3.8 times, respectively. The results obtained from normal volunteers with visual stimulation further confirm the effectiveness of our new approach and show an average increase in detected activation area of 3.1 times over the IOT method and of 1.6 times over the previous cluster method using the new approach. ©1996 Wiley‐Liss, Inc.
CAPACITY CONSIDERATIONS IN MIMO SYSTEMS AND IMPACT OF TRANSMIT-SIDE SPACIAL FADING CORRELATION ON THE PERFORMANCE OF NON-ORTHOGONAL SPACE _ TIME CODES

High data rates are a primary concern for wireless system designers today. It is likely that future breakthroughs in wireless communications will be driven mainly by the demand for high data rate applications. Streaming video for example, requires two to three orders of magnitude higher data rates than speech. A simple solution for increasing data rate is to increase channel bandwidth. This however is not usually considered, as it is very costly. Use of multiple element arrays (MEA) at both transmitter & receiver on the other hand can result in the realization of these higher data rates. So far, only partial consideration has been given to the analysis of space-time coding in the practical case of correlated fading. In this work, we will expand newly published results on the performance of space-time codes in the presence of spatial fading correlation, by quantifying the impact of the fading on different classes of spacetime codes. Explicitly, we show that in the case of two and above receive antenna, transmit-side correlation has a more brutal impact on the performance of non-orthogonal space-time codes. Orthogonal spacetime codes offer maximum potency against transmit correlation.
The Science of Guessing: Analyzing an Anonymized Corpus of 70 Million Passwords

We report on the largest corpus of user-chosen passwords ever studied, consisting of anonymized password histograms representing almost 70 million Yahoo! users, mitigating privacy concerns while enabling analysis of dozens of subpopulations based on demographic factors and site usage characteristics. This large data set motivates a thorough statistical treatment of estimating guessing difficulty by sampling from a secret distribution. In place of previously used metrics such as Shannon entropy and guessing entropy, which cannot be estimated with any realistically sized sample, we develop partial guessing metrics including a new variant of guesswork parameterized by an attacker's desired success rate. Our new metric is comparatively easy to approximate and directly relevant for security engineering. By comparing password distributions with a uniform distribution which would provide equivalent security against different forms of guessing attack, we estimate that passwords provide fewer than 10 bits of security against an online, trawling attack, and only about 20 bits of security against an optimal offline dictionary attack. We find surprisingly little variation in guessing difficulty; every identifiable group of users generated a comparably weak password distribution. Security motivations such as the registration of a payment card have no greater impact than demographic factors such as age and nationality. Even proactive efforts to nudge users towards better password choices with graphical feedback make little difference. More surprisingly, even seemingly distant language communities choose the same weak passwords and an attacker never gains more than a factor of 2 efficiency gain by switching from the globally optimal dictionary to a population-specific lists.
Algorithm 915, SuiteSparseQR: Multifrontal multithreaded rank-revealing sparse QR factorization

SuiteSparseQR is a sparse QR factorization package based on the multifrontal method. Within each frontal matrix, LAPACK and the multithreaded BLAS enable the method to obtain high performance on multicore architectures. Parallelism across different frontal matrices is handled with Intel's Threading Building Blocks library. The symbolic analysis and ordering phase pre-eliminates singletons by permuting the input matrix A into the form [R11 R12; 0 A22] where R11 is upper triangular with diagonal entries above a given tolerance. Next, the fill-reducing ordering, column elimination tree, and frontal matrix structures are found without requiring the formation of the pattern of ATA. Approximate rank-detection is performed within each frontal matrix using Heath's method. While Heath's method is not always exact, it has the advantage of not requiring column pivoting and thus does not interfere with the fill-reducing ordering. For sufficiently large problems, the resulting sparse QR factorization obtains a substantial fraction of the theoretical peak performance of a multicore computer.
Three-dimensional shape and connectivity of physical networks

Data describing the three-dimensional structure of physical networks is increasingly available, leading to a surge of interest in network science to explore the relationship between the shape and connectivity of physical networks. We contribute to this effort by standardizing and analyzing 15 data sets from different domains. Treating junction points as nodes and connections between them as links, we divide the networks into three categories: lattice-like networks, trees, and linked trees. We find that the degree distribution of physical networks is bounded, with most nodes having degree one or three. Characterizing the physical properties of links, we show that links have an elongated shape and tend to follow a nearly straight trajectory, while a small fraction of links follow a winding path. These typical node and link properties must be reflected by physical network models. We also measure how confined a link is in space by comparing its trajectory to a randomized null-model, showing that links that are central in the abstract network tend to be physically confined by their neighbors. The fact that the shape and connectivity of the physical networks are intertwined highlights that their three-dimensional layout must be taken into account to understand the evolution and function of physical networks.
A Knowledge-based Approach for Scenario-specific Content Correlation in a Medical Digital Library ∗

Manually searching the web for medical literature and teaching materials is labor-intensive and time-consuming. Content Correlation automatically creates semantic links among documents from different collections. As a result, navigating from a patient report to online medical documents is much easier for the user. In this paper, we present a knowledge-based (e.g. UMLS) approach for content correlation. First, we index each medical document using phrases (a combination of word stems and concepts). We illustrate how phrase-based indexing greatly ameliorates the problem of vocabulary mismatch among multiple document collections. Second, we use a phrase-indexed patient report to automatically form a query, and expand the query with scenario-specific phrases derived from a knowledge base. Experimental results reveal that the phrase-based indexing and the knowledge-based query expansion together, yield scenario-specific content correlation.
The EASTR study: a new approach to determine the reasons for transfusion in epidemiological studies

summary Previous studies of blood use have used different methods to obtain and classify transfusion indications. Before undertaking a national study of transfusion recipients, a pilot study was performed over 2 months at two teaching and two district general hospitals to match information from hospital transfusion laboratories with clinical coding data from the hospital’s Patients Administration System to determine the indication for transfusion in 2468 recipients. Data analysis revealed major limitations in the conventional use of primary diagnostic International Statistical Classification of Disease and Related Health Problems 10th Revision (ICD‐10) or procedure Office of Population, Censuses and Surveys – Classification of Surgical Operations and Procedures – 4th Revision (OPCS‐4) codes alone in allocating transfusion indications. A novel algorithm was developed, using both types of code, to select the probable indication for transfusion for each patient. A primary OPCS‐4 code was selected for recipients transfused in relation to surgery (43%) and either the primary (36%) or the secondary (12%) ICD‐10 code was chosen for recipients transfused for medical reasons. The remaining patients were unclassified. Selected codes were then collated into Epidemiology and Survival of Transfusion Recipients (EASTR) casemix groups (E‐CMGs). The most frequent E‐CMGs were haematology (15% of recipients), musculoskeletal (14%), digestive system (12%) and cardiac (10%). The haematology E‐CMG includes patients with malignant and non‐malignant blood disorders and recipients transfused for anaemia where no cause was listed. Recipients undergoing hip and knee replacement and coronary artery bypass grafting are within the musculoskeletal and cardiac E‐CMGs. The digestive E‐CMG includes recipients transfused for gastrointestinal (GI) bleeds and those undergoing GI surgery. This methodology provides a more useful means of establishing the probable indication for transfusion and arranging recipients into clinically relevant groups.
Modeling Spatial Relationships in International and Comparative Political Economy: An Application to Globalization and Capital Taxation in Developed Democracies

Social scientists have long recognized that time-series-cross-section (TSCS) data typically correlate across time and space. Today, standard social-science practice is to model dynamics (i.e., temporal dependence) directly, typically with lags of the dependent variable, but to address spatial dependence solely by applying panel-corrected (robust) standard-errors (PCSE), thereby treating spatial dependence as a nuisance (Beck and Katz's 1996 terminology). However, regardless of the analyst's substantive interest in these relationships, direct modeling of spatial dependence (plus PCSE perhaps) enhances efficiency and is required for unbiased and consistent estimates of the coefficients on non-spatial regressors and any associated hypothesis tests or confidence intervals. Whereas analysts less interested in spatial relations per se will understandably wish to employ simple proxies for more complicated diffusion processes, those directly interested will prefer more sophisticated modeling techniques for estimating the dyadic patterns of diffusion in their data. Our broad project uses Monte Carlo experiments to evaluate the performance of several simple and sophisticated estimators under three important types of spatial correlation (the more-complex being spatial analogues to estimators devised for dynamic panel models: e.g., Hsiao 1986; Baltagi 1995) and develops a set of techniques and guidelines to help analysts diagnose, characterize, and gauge various sorts of spatial correlation, and to choose and interpret appropriate estimators based on their objectives. This paper leverages globalization and capital taxation as substantive venue to start such methodological explorations. Many academic and casual observers argue that the dramatic post- 1970s rise in international capital mobility and the steadily upward postwar trend in trade integration, by sharpening capital's threat against domestic governments to flee purportedly excessive and inefficient taxation, has forced and will continue to force welfare-/tax-state retrenchment and tax-burden shifts away from more-mobile capital (especially financial capital) and toward less-mobile labor (especially manual labor). Several important recent studies of the international and comparative political economy of policy change over this period challenge such claims. We offer a preliminary comparison of several such arguments, using specifications that reflect the spatial relationships central to such diffusion processes.
Mitochondrial and Nuclear DNA Analysis of Genetic Heterogeneity Among Recruitment Cohorts of the European Flat Oyster Ostrea edulis

Marine species with high fecundity and high early mortality may also have high variance in reproductive success among individuals due to stochastic factors, making successful reproduction a “sweepstakes. ” In some cases, the impact is sufficient to reduce the effective number of breeders in wild populations. We tested two predictions of the sweepstakes reproductive success hypothesis in a French Atlantic population of the European flat oyster, Ostrea edulis, by evaluating (1) whether individuals belonging to temporally discrete recruitment cohorts within a single reproductive season displayed reduced genetic variation relative to the entire adult population, and (2) whether these temporal cohorts of recruits were genetically differentiated from each other. We assayed genetic variation at four nuclear microsatellites and a 12S mitochondrial fragment in four recruitment cohorts. Nuclear markers provided no evidence for differentiation between recruitment cohorts and adults or between temporal cohorts. However, mitochondrial data indicate that the first temporal cohort showed significant differentiation with the last (Fst = 0.052, P < 0.05) and with the adult sample (Fst = 0.058, P < 0.05). These differences are most likely due to the smaller effective size of the mitochondrial genome—and hence its increased sensitivity to drift compared to the nuclear genome. This slight mitochondrial signal indicates a certain limitation in the number of contributing female parents in this species. The “sweepstakes” phenomenon was therefore limited in our case. Hypothetically, this phenomenon may occur or not, with a high variance as a result of the interaction between the oyster reproductive biology and different environmental conditions.
A study of how mathematics teachers in secondary schools in Hong Kong cater for students' individual differences

The purpose of this study is to investigate how teachers cater for students’ individual differences in the context of a reform-based Mathematics curriculum, using the topic ‘Similar triangles’. A group of six Hong Kong secondary schools in different locations, and with different banding and setting policies, took part in the study. The students were in the age-group 12 to 13 years. A naturalistic research design, without any interference from the researcher, was chosen to examine teacher behaviour. The emphasis was on observing, describing, interpreting and exploring events in the complex setting of the classroom, via a case study approach. Data were collected from the six teachers through interviews, questionnaires, and video and audio recording of five to six lessons for each teacher. There was also one focus group interview with students from each teacher’s classes. This research reports on how the methods suggested in the Curriculum Guide for catering for individual differences were implemented in the classroom. In general, the teachers involved: (1) attempted to check students’ prior knowledge, but only a small number of students was involved; (2) asked questions at different levels, but did not know about the students’ learning progress; (3) chose content which was most likely to follow the textbook; (4) were unable to vary the focus to help students to learn; and (5) could not identify what was hindering students in working out problems during seatwork. This study indicates that teachers are using their own methods to try to solve the problem of catering for student diversity, but the approaches they employ are not of a high enough quality to help students. Also, the ways in which teachers catered for individual differences in students varied considerably. This was found to depend on: the learning atmosphere; the opportunities created for student responses; variations in the scaffolding used; and the level of students’ motivation for learning. It is strongly recommended that teachers open their minds to contacts outside the classroom to refresh their teaching repertoire, and try to use some new methods which are related to the theories discussed in this research. Also, it is suggested that policy makers could build on the teachers’ experiences to enhance their ability to handle student diversity.
Cryptic relatedness in epidemiologic collections accessed for genetic association studies: experiences from the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study and the National Health and Nutrition Examination Surveys (NHANES)

Epidemiologic collections have been a major resource for genotype–phenotype studies of complex disease given their large sample size, racial/ethnic diversity, and breadth and depth of phenotypes, traits, and exposures. A major disadvantage of these collections is they often survey households and communities without collecting extensive pedigree data. Failure to account for substantial relatedness can lead to inflated estimates and spurious associations. To examine the extent of cryptic relatedness in an epidemiologic collection, we as the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study accessed the National Health and Nutrition Examination Surveys (NHANES) linked to DNA samples (“Genetic NHANES”) from NHANES III and NHANES 1999–2002. NHANES are population-based cross-sectional surveys conducted by the National Center for Health Statistics at the Centers for Disease Control and Prevention. Genome-wide genetic data is not yet available in NHANES, and current data use agreements prohibit the generation of GWAS-level data in NHANES samples due issues in maintaining confidentiality among other ethical concerns. To date, only hundreds of single nucleotide polymorphisms (SNPs) genotyped in a variety of candidate genes are available for analysis in NHANES. We performed identity-by-descent (IBD) estimates in three self-identified subpopulations of Genetic NHANES (non-Hispanic white, non- Hispanic black, and Mexican American) using PLINK software to identify potential familial relationships from presumed unrelated subjects. We then compared the PLINKidentified relationships to those identified by an alternative method implemented in Kinship-based INference for Genome-wide association studies (KING). Overall, both methods identified familial relationships in NHANES III and NHANES 1999–2002 for all three subpopulations, but little concordance was observed between the two methods due in major part to the limited SNP data available in Genetic NHANES. Despite the lack of genome-wide data, our results suggest the presence of cryptic relatedness in this epidemiologic collection and highlight the limitations of restricted datasets such as NHANES in the context of modern day genetic epidemiology studies.
Opposite relationships between invasibility and native species richness at patch versus landscape scales

of native species. In 1 m 2 patches, native cover was positively associated with native richness and thus cover-related competition was a likely mechanism by which richness influenced R. cathartica . At the landscape scale (comparing the aggregate stand-scale metrics among the 17 stands), native cover and richness were still positively related, but had opposite relationships with R. cathartica cover. R. cathartica cover was positively related to species richness and negatively related to native species cover. The observed switch at different scales from a positive to a negative relationship between R. cathartica cover and native richness supported the hypothesized scale dependence of these relations. Propagule pressure, which we estimated by measuring the size of nearby mature R. cathartica shrubs, had a large positive effect on R. cathartica seedling cover at the landscape scale. These results suggest that landscape patterns of invasion may be best understood in light of the combination of many factors including native diversity, native cover, and propagule pressure.
RNAi Screening in Drosophila Cells Identifies New Modifiers of Mutant Huntingtin Aggregation

The fruitfly Drosophila melanogaster is well established as a model system in the study of human neurodegenerative diseases. Utilizing RNAi, we have carried out a high-throughput screen for modifiers of aggregate formation in Drosophila larval CNS-derived cells expressing mutant human Huntingtin exon 1 fused to EGFP with an expanded polyglutamine repeat (62Q). 7200 genes, encompassing around 50% of the Drosophila genome, were screened, resulting in the identification of 404 candidates that either suppress or enhance aggregation. These candidates were subjected to secondary screening in normal length (18Q)-expressing cells and pruned to remove dsRNAs with greater than 10 off-target effects (OTEs). De novo RNAi probes were designed and synthesized for the remaining 68 candidates. Following a tertiary round of screening, 21 high confidence candidates were analyzed in vivo for their ability to modify mutant Huntingtin-induced eye degeneration and brain aggregation. We have established useful models for the study of human HD using the fly, and through our RNAi screen, we have identified new modifiers of mutant human Huntingtin aggregation and aggregate formation in the brain. Newly identified modifiers including genes related to nuclear transport, nucleotide processes, and signaling, may be involved in polyglutamine aggregate formation and Huntington disease cascades.