Miracle-dz/UniFAR-FTUs huggingface dataset:
Shape Deformation via Interior RBF

We present a new framework for real-time shape deformation with local shape preservation and volume control. Given a 3D object, in any form, one would like to manipulate the object using convenient handles, so that the resulting shape is a natural variation of the given object. It is also important that the deformation is controlled, thereby enabling localized changes that do not influence nearby branches. For example, given a horse model, a movement of one of its hooves should not affect the other hooves. Another goal is the minimization of local shape distortion throughout the object. The first ingredient of our method is the use of interior radial basis functions (IRBF), where the functions are radial with respect to interior distances within the object. The second important ingredient is the reduction of local distortions by minimizing the distortion of a set of spheres placed within the object. Our method achieves the goals of convenient shape manipulation and local influence property, and improves the latest state-of-the-art cage-based methods by replacing the cage with the more flexible IRBF centers. The latter enables extra flexibility and fully automated construction, as well as simpler formulation. We also suggest the IRBF interpolation method that can extend any surface mapping to the whole subspace in a shape-aware manner.
Inductors Allow LossLess Current Sensing in Multiphase DC-DC Converters

igh performance microprocessors require a lowvoltage, high-current power supply with fast transient response. Therefore, interleaved multiphase synchronous buck converters have gained popularity as the VRM for these microprocessors. Multiphase converters must share load current to balance thermal stress on each phase, so it’s important to address current sensing and sharing. You can use the current signal in adaptive voltage positioning to reduce the output voltage deviation during transients, which requires accurate current information. Current sense resistors have high accuracy, less than ±5%, and their temperature coeffi cient (TC) is small. However, the sense resistor connection is in the power path, which generates additional power loss and lowers effi ciency—especially in high output current applications . Another disadvantage of the sense resistor is its relatively high cost. Current sensing through MOSFET R DS(on) is a loss-less method, but this on-resistance has a large tolerance from lot to lot even for a given manufacturer and changes with the gate-drive voltage of MOSFET . The TC tolerance of R DS(on) isn’t well defi ned, and is not always available. You can use a dc resistance of an inductor to sense current. The inductor dc resistance changes with temperature, but the TC of copper wire is well defi ned, and independent of the inductor design of the manufacturer. A resistor-capacitor circuit in parallel with the inductor supplies the current information, which is then amplifi ed by a current sense amplifi er. The use of the amplifi ed current signal is not only for the PWM ramp and adaptive voltage positioning, but also for current protection. Fig. 1, on page 60, shows a buck converter with the inductor current sensing circuit, where L is the inductance and R L is the inductor’s dc resistance. In parallel with the inductor is a fi lter consisting of low-power resistor R S and small ceramic capacitor C S . Current sense amplifi er, CSA, amplifi es the voltage across C S , which represents dc and ac components of inductor current. One reference cited a similar scheme [4] to obtain dc current information, mainly for overcurrent protection. It received a patent in 1995, despite a prior art in 1981 [5] and a relevant paper in 1994 . There are other current sensing schemes that utilize inductor dc resistance. Instead of the simple resistor-capacitor fi lter across the inductor, you can use the differential active fi lter [7] or inductor current estimator circuit . As shown in Fig. 1, if the current through the inductor is i L , the voltage across the capacitor C S is:
A new genus and species of marine crayfish, Palibythus magnificus, and new records of Palinurellus (Decapoda : Palinuridae) from the Pacific Ocean

A new genus and species of marine crayfish, Palibythus magnificus, is described from deep water off Western Samoa. Palibythus is placed in the Palinuridae, among the 'Stridentes' group of genera, because of the well-developed stridulatory organ. It differs from all other known genera, except Palinurellus, by the flat triangular rostrum and the narrow thoracic sternum; Palinurellus, however, lacks a stridulatory organ. The relationships of Palinurellus are discussed and the Synaxidae is replaced in synonymy with the Palinuridae. Palinurellus wieneckii is recorded from New Guinea and Solomon Islands waters for the first time.
An analysis of querying behaviors of domain knowledgeable users and novice users

Users with different amount of domain or topic knowledge tend to find different results, when searching on the same topic. We were interested in finding out how domain or topic knowledge is associated with users’ querying behaviors, which would result in different results. In this study, thirty-five students participated in a user experiment, conducted searches from genomics data set that was used by TREC Genomics track 2004. The participants’ background domain knowledge and the knowledge of each individual topics was assessed, before they performed the search tasks. Their querying behaviors were recorded. The results demonstrate that domain knowledge level is significantly associated with the number of search terms in queries: the more knowledgeable, the more search terms. Further analyses are planned to be conducted.
Adaptive Snoop Granularity and Transactional Snoop Filtering in Hardware Transactional Memory

Hardware transactional memory (HTM) offers a promising parallel programming model for chip multiprocessors. The performance aspect of HTMs has been explored extensively, whereas little research has addressed the power of HTMs. In this paper, we investigate power consumption in HTMs and propose two optimization techniques. The first optimization technique is adaptive snoop granularity (ASG). HTMs rely on cache coherence protocols to detect conflicts and maintain consistency of transactional data. One of the main design issues facing HTMs is the growing number of snoops required to maintain coherency of transactional data. We found that many transactions access consecutive memory locations which are not shared by other transactions. ASG monitors these transactional accesses and dynamically changes snoop granularity to reduce the power of the interconnection network and eliminate needless cache snoops. The second optimization technique is transactional snoop filtering (TSF). TSF dynamically tracks accesses to the coherence caches and eliminates cache snoops that would result in cache misses. TSF relies on small filters to monitor cache addresses. Energy is reduced as accesses to the much more demanding data caches are decreased. We extended the Gem5 simulator to model ASG and TSF. Our simulation results show that ASG and TSF are effective and reduce energy of interconnects and caches up to 44% and 89%, respectively.
A scalable model for efficient information diffusion in large real world networks

Real world networks represent the relationships and interactions of real world entities, such as individuals in a social network. They usually have millions of vertices, and are very complex as they are dynamic, real time and fast growing. Information diffusion models on such graphs have a major role in spreading information at a very large scale. Influential nodes are a small subset of nodes in a graph that could maximize the spread of information. Finding influential nodes in real graphs has applications ranging from viral marketing to vaccination strategies during epidemics. We propose a model to find a set of influential nodes from a very large real world graph effectively by taking into account both the structural features and centrality measures of the graph. To this end, the community structures within the graph are identified. We convert COPRA algorithm for finding overlapping communities to an equivalent Bulk Synchronous Parallel(BSP) algorithm for parallel processing of the graph. We then applied PageRank algorithm to the isolated communities to find influential nodes within each community. Finally the top k influential nodes are identified by applying a ranking function to the influential nodes generated from both isolated and overlapped communities. We found that by dividing the graph into communities and by finding influential nodes within each of those communities, a better set of nodes for fast information diffusion is obtained.
Multi-Lateral Trade Negotiations and the Most Favored Nation Clause

This paper considers the interaction between private information and the Most Favored Nation clause in trade negotiations. It demonstrates that by aggregating uncertainty over a number of trading partners, the Most Favored Nation clause may offer a welfare improvement over a set of bi-lateral trade negotiations. This improvement is shown to be most pronounced when a large number of countries are involved in negotiations.
Modeling and Applying of RBF Neural Network Based on Fuzzy Clustering and Pseudo-Inverse Method

The key of advancing radial basis function neural network (RBFNN) is how to choose the data center and the number of cluster perfectly. In this paper fuzzy C-means clustering is used as K-means clustering ameliorated algorithm to determine the data center of RBF neural networks hidden nodes. Combined pseudo-inverse method RBF network model is constructed. Simulation test on the dimension predicting in selective laser sintering process showed the model is able to provide higher accurate predict, as well as less calculate quantity and quick training. KeywordsRBFNN; Fuzzy c-means clustering; Pseudo-inverse method; Selective laser sintering
A comparison of early family life events amongst monozygotic twin women with lifetime anorexia nervosa, bulimia nervosa, or major depression.

OBJECTIVES To investigate the differential profile of early family life events associated with lifetime anorexia nervosa (AN), bulimia nervosa (BN), and major depression (MD). METHOD Only data from the monozygotic twins (n = 622) were examined from a community sample of female twins who had participated in three waves of data collection. Eating disorder and MD diagnoses were ascertained from the Eating Disorder Examination at Wave 3 and interview at Wave 2 respectively. Early family events were ascertained from self-report measures at Waves 1 and 3. Two case control designs were used, including a comparison of women: (1) who had lifetime AN, BN, MD, and controls, and (2) twin pairs discordant for either AN, BN, or MD (where the unaffected cotwin formed the control group). RESULTS Across the two types of designs, compared to controls, both AN and BN were associated with more comments from the family about weight and shape when growing up. AN was uniquely associated with higher levels of paternal protection while BN was associated with higher levels of parental expectations. CONCLUSION While some overlap among early life events was indicated, especially related to parental conflict and criticism, there was evidence to support some degree of nonoverlap among life events associated with AN, BN, and MD.
Toward emotion-sensitive multimodal interfaces : the challenge of the European Network of Excellence HUMAINE

The network of excellence HUMAINE is currently making a co-ordinated, interdisciplinary effort to develop a consistent view on emotion-oriented computing. This overview paper proposes a “map” of the research area, distinguishing core technologies from application-oriented and psychologically oriented work. First results from the on-going research in the thematic workpackages are reported.
Murine Lupus Kidney-Infiltrating Effector T Cells in Trafficking Receptor Expression of ICOS Controls Effector Function but Not

Renal pathology in systemic lupus erythematosus involves both autoantibody deposition and a cellular inﬂammatory response, both of which are mediated by effector CD4 T cells. MRL lpr mice spontaneously develop massive perivascular inﬁltrates, but the pathways that regulate the development, trafﬁcking, and effector functions of kidney-inﬁltrating T cells are poorly deﬁned. To address these questions, we ﬁrst surveyed inﬂammatory chemokine protein levels in nephritic kidneys from lupus-prone MRL lpr mice. After identifying highly elevated levels of the CXCR3 ligand CXCL9, we found that kidney-inﬁltrating effectors are enriched for expression of CXCR3, as well as P-selectin ligand and ICOS. Using genetic ablation, we demonstrate that ICOS plays an essential role in the establishment of renal perivascular inﬁltrates, although a small number of inﬁltrating cells remain around the blood vessels. Interestingly, though IgG autoantibody production is substantially reduced in Icos (cid:1) / (cid:1) MRL lpr mice, the progression of immune complex glomerulonephritis is only modestly diminished and the production of inﬂammatory chemokines, such as CXCL9, remains high in the kidney. We ﬁnd that Icos (cid:1) / (cid:1) effector cell numbers are only slightly reduced and these have normal expression of CXCR3 and P-selectin ligand with intact migration to CXCL9. However, they have impaired production of inﬂammatory cytokines and fail to show evidence of efﬁcient proliferation in the kidney. Thus, while dispensable for acquisition of renal trafﬁcking receptor expression, ICOS
Risk of bipolar disorder and schizophrenia in relatives of people with attention-deficit hyperactivity disorder

Background Attention-deficit hyperactivity disorder (ADHD) is associated with bipolar disorder and schizophrenia, and it has been suggested that combined bipolar disorder and ADHD is aetiologically distinct from the pure disorders. Aims To clarify whether ADHD shares genetic and environmental factors with bipolar disorder and schizophrenia. Method By linking longitudinal Swedish national registers, we identified 61 187 persons with ADHD (the proband group) and their first- and second-degree relatives, and matched them with a control group of people without ADHD and their corresponding relatives. Conditional logistic regression was used to determine the risks of bipolar disorder and schizophrenia in the relatives of the two groups. Results First-degree relatives of the ADHD proband group were at increased risk of both bipolar disorder (odds ratio (OR) = 1.84−2.54 for parents, offspring and full siblings) and schizophrenia (OR = 1.71−2.22 for parents, offspring and full siblings). The risks of bipolar disorder and schizophrenia among second-degree relatives were substantially lower than among full siblings. Conclusions These findings suggest that the co-occurrence of ADHD and bipolar disorder as well as ADHD and schizophrenia is due to shared genetic factors, rather than representing completely aetiologically distinct subsyndromes.
Semiautomatic quality determination of 3D confocal microscope scans of neuronal cells denoised by 3D wavelet shrinkage

The main goal of this work is to denoise 3D confocal microscope scans of neuronal cells taken at high resolution such that neuronal structures of size smaller than 1 micrometers become visible. Although scanning confocal microscopes give much clearer images than ordinary light microscopes do, the images are still noisy and blurred. Our goal is to filter out the noise in these images without disturbing the smallest neuronal structures which have the same signal amplitude and geometric size as the noise. In order to obtain a good scale-space representation of the analyzed image, we use the 3D-wavelet transformation. We extend the denoising method of Donoho for 3D data and obtain several ways of computing thresholds and noise variances. Finally we develop a quality measure, for images with tree like structures, to determine the denoising method and wavelet form best suited for a particular confocal scan.
Error propagation mitigation by exploiting source-relay correlation with limited channel feed-forward bits

In this paper, a complexity-reduced error propagation mitigation algorithm is presented by exploiting source-relay (S-R) correlation information with the limited channel feed-forward bits from the relay node to the destination node. The proposed idea employs the limited channel feed-forward bits as the S-R correlation information indicator and uses it for the iterative decoding at the destination node. Comparing with the conventional threshold-based S-R correlation estimation algorithm, the proposed algorithm can provide close bit error rate performance and omit the iterative S-R correlation estimation process at the destination node. Moreover, the results also show that the proposed algorithm outperforms some of the existing relaying protocols up to 1 dB gain.
International multicenter comparative trial of endoscopic ultrasonography-guided gastroenterostomy versus surgical gastrojejunostomy for the treatment of malignant gastric outlet obstruction

Abstract Background and study aims EUS-guided gastroenterostomy (EUS-GE) is a novel procedure that potentially offers long-lasting luminal patency without the risk of tumor ingrowth/overgrowth. This study compared the clinical success, technical success, adverse events (AEs), length of hospital stay (LOHS) and symptom recurrence in EUS-GE versus SGJ. Methods This was a multicenter international retrospective comparative study of EUS-GE and SGJ in patients with malignant gastric outlet obstruction (GOO) who underwent either EUS-GE or SGJ. EUS-GE was performed using lumen apposing metal stents. Results A total of 93 patients with malignant GOO treated with either EUS-GE (n = 30) or SGJ (n = 63) were identified. Peritoneal carcinomatosis was present in 13 (43 %) patients in the EUS-GE group and 7 (11 %) patients in the SGJ group (P < 0.001). Although the technical success rate was significantly higher in the SGJ group as compared to the EUS-GE group (100 % vs. 87 %, P = 0.009), the clinical success rate was not different (90 % vs. 87 %, P = 0.18, OR 0.8, 95 %CI 0.44 – 7.07). The rate of AEs was lower in the EUS-GE group, but the difference was not statistically significant (16 % vs 25 %, P = 0.3). The mean LOHS was similar in the EUS-GE group compared to SGJ (P = 0.35). The rate of recurrent GOO was not different between the two groups (3 % vs. 14 %, P = 0.08). Similarly, the mean time to reintervention was similar (88 days vs. 121 days, P = 0.83). Conclusions EUS-GE is associated with equivalent efficacy and safety as compared to surgical GJ. This is the first comparative trial between both techniques and suggests EUS-GE as a non-inferior but less invasive alter to surgery.
Snowflake universality of Wasserstein spaces

For $p\in (1,\infty)$ let $\mathscr{P}_p(\mathbb{R}^3)$ denote the metric space of all $p$-integrable Borel probability measures on $\mathbb{R}^3$, equipped with the Wasserstein $p$ metric $\mathsf{W}_p$. We prove that for every $\varepsilon>0$, every $\theta\in (0,1/p]$ and every finite metric space $(X,d_X)$, the metric space $(X,d_{X}^{\theta})$ embeds into $\mathscr{P}_p(\mathbb{R}^3)$ with distortion at most $1+\varepsilon$. We show that this is sharp when $p\in (1,2]$ in the sense that the exponent $1/p$ cannot be replaced by any larger number. In fact, for arbitrarily large $n\in \mathbb{N}$ there exists an $n$-point metric space $(X_n,d_n)$ such that for every $\alpha\in (1/p,1]$ any embedding of the metric space $(X_n,d_n^\alpha)$ into $\mathscr{P}_p(\mathbb{R}^3)$ incurs distortion that is at least a constant multiple of $(\log n)^{\alpha-1/p}$. These statements establish that there exists an Alexandrov space of nonnegative curvature, namely $\mathscr{P}_{\! 2}(\mathbb{R}^3)$, with respect to which there does not exist a sequence of bounded degree expander graphs. It also follows that $\mathscr{P}_{\! 2}(\mathbb{R}^3)$ does not admit a uniform, coarse, or quasisymmetric embedding into any Banach space of nontrivial type. Links to several longstanding open questions in metric geometry are discussed, including the characterization of subsets of Alexandrov spaces, existence of expanders, the universality problem for $\mathscr{P}_{\! 2}(\mathbb{R}^k)$, and the metric cotype dichotomy problem.
Components Associated With Home Visiting Program Outcomes: A Meta-analysis

BACKGROUND: Although several systematic reviews have concluded that home visiting has strong evidence of effectiveness, individual evaluations have produced inconsistent results. We used a component-based, domain-specific approach to determine which characteristics most strongly predict outcomes. METHODS: Medline and PsycINFO searches were used to identify evaluations of universal and selective home visiting programs implemented in the United States. Coders trained to the study criterion coded characteristics of research design, program content, and service delivery. We conducted random-effects, inverse-variance–weighted linear regressions by using program characteristics to predict effect sizes on 6 outcome domains (birth outcomes, parenting behavior and skills, maternal life course, child cognitive outcomes, child physical health, and child maltreatment). RESULTS: Aggregated to a single effect size per study (k = 51), the mean effect size was 0.20 (95% confidence interval: 0.14 to 0.27), with a range of –0.68 to 3.95. Mean effect sizes were significant and positive for 3 of the 6 outcome domains (maternal life course outcomes, child cognitive outcomes, and parent behaviors and skills), with heterogeneity of effect sizes in all 6 outcome domains. Research design characteristics generally did not predict effect sizes. No consistent pattern of effective components emerged across all outcome domains. CONCLUSIONS: Home visiting programs demonstrated small but significant overall effects, with wide variability in the size of domain-specific effects and in the components that significantly predicted domain-specific effects. Communities may need complementary or alternative strategies to home visiting programs to ensure widespread impact on these 6 important public health outcomes.
Graph Representation of Synonymy and Translation Resources for Crosslinguistic Modelisation of Meaning

In this paper we describe the data that will be used to compare the semantic struc- tures that emerge from synonymy in French and in Mandarin. We aim at studying these semantic structures at both a global, lexicographic level, using lexicons, synonymy and trans- lation dictionaries and at a more localised, experimental level, using data collected in parallel psycholinguistic experiments in French and Mandarin. After presenting our research project, the data we need to carry it out and the available resources, we analyse several linguistic issues arising from the structural differences between the French and Mandarin lexicons. We then explain the construction of the synonymy and translation networks from the available resources and detail specific choices that will enable us to produce meaningful experimental results based on this prepared data. Two kinds of networks are built: lexicographic networks and smaller movie-based networks extracted from experimental recordings. We conclude by describing how we intend to use this data.
Capital Structure in Venture Finance

Prior research has argued that convertible preferred equity is the optimal form of venture capital finance, based on datasets with up to 213 observations from the U.S., where unique tax biases exist in favour of convertible preferred. This paper introduces a comparable sample of 3083 Canadian corporate and limited partnership venture financing transactions spanning the years 1991-2000. The data indicate a variety of securities are used, and convertible preferred equity has not been the most frequent. Empirical tests offer strong support for the proposition that the mix of financing instruments minimizes the costs arising from a set of agency problems.