Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Global Clustering Algorithm for the Identification of Functional Connectivity from BOLD fMRI

(5) . To eliminate manual selection of the k parameter, we repeatedly applied the algorithm to the SOM nodes, starting with k=2 and incrementally adding cluster candidates until the stopping criterion, based on minimization of quantization error (QE), is reached. At each k-value, 10 initializations of the k-means starting partition are attempted and the best result is selected. This process automatically divides the map into similarity regions with minimal QE. For each cluster centroid identified by k-means, we assign the points from the original data that are nearest in Euclidean distance. Finally each cluster is analyzed with respect to its centroid, removing any intra-cluster points outside a distance of 1.5 · IQR and those beyond of a pre-specified correlation p-value. Mapping the data back to the 3D brain space while maintaining the cluster labels provides a global visualization of regions that belong to the same clusters. Results A representative sample result based on the artificial FSL data set is provided in Figure 1, depicting the isolated cluster "S" returned under increasing p-value thresholds. The "F" and "L" slices on the same data represented slightly worse and better cluster identifications, respectively. A sample result for the second data set (depicting the letters "N" and "C") is provided in Figure 2. Results for the second data set were analyzed by using the known pattern image as a label template and calculating the area under the ROC curve (AUC) after each of 20 initializations. The resulting distribution of AUC values had a median of 0.895, with upper/ lower quartile values of 0.900 and 0.885 respectively, indicating relatively strong detection accuracy with low variation in the results returned. The system has an asymptotic run time complexity of O(N N ), with N being the number of voxel inputs from the data volume. Conclusions The SOM clustering algorithm was applied to the resting state BOLD data. The ensuing models are a sufficient approximation of the original time course data to allow a global, hard clustering step on the SOM nodes directly. Our preliminary results suggest that the global clustering approach efficiently identifies the embedded patterns from the perspective of both highly noisy data and real-world data and appear to be applicable to the identification of the whole brain functional connectivity. Future work will evaluate the proposed approach over a large database of resting state data against a standard suite of model-free algorithms. Moreover, we intend to consider the use of SOM and feature selection methods for providing more efficient temporal representations prior to application of the global clustering step.
Topic-based targeted influence maximization

Social Networks play a very important role as a medium to propagate information among people. Marketers use this to campaign for their products and influence customers. However, it is not practically possible for a marketer to reach out to each and every individual prospective/existing customer due to the sheer size of the networks (in the orders of millions or billions). Therefore, marketers reach out to a small set of people (influencers) who have the potential to further influence/reach out to the targeted customers. Practically, it is not just enough if these influencers have a large following, they also need to have to be able to influence people in the topic that is relevant to the marketer and the influencer must be able to address the target segment that the marketer is targeting. In this paper, we first analyze various edge weighting mechanisms to incorporate influencing probability and utilize this to propose an algorithm to find influencers to maximize the spread to a specified set of targets.
Bounded arithmetic theory for the counting functions and Toda's theorem (Proof Theory, Computation Theory and Related Topics)

In this paper we give a two sort bounded arithmetic whose provably total functions coincide with the class $FP\# P$ . Our first aim is to show that the theory proves Toda’s theorem in the sense that any formula in $\Sigma_{\infty}^{B}$ is provably equivalent to a $\Sigma_{0}^{B}$ formula in the language of $FP\# P$ . We also argue about some problems concerning logical theories for counting classes.
Adaptive compression of image data

In this paper we will introduce a method of analyzing images, a criterium to differentiate between images, a compression method of medical images in digital form based on the classification of the image bit plane and finally an algorithm for adaptive image compression. The analysis of the image content is based on a valuation of the relative number and absolute values of the wavelet coefficients. A comparison between the original image and the decoded image will be done by a difference criteria calculated by the wavelet coefficients of the original image and the decoded image of the first and second iteration step of the wavelet transformation. This adaptive image compression algorithm is based on a classification of digital images into three classes and followed by the compression of the image by a suitable compression algorithm. Furthermore we will show that applying these classification rules on DICOM-images is a very effective method to do adaptive compression. The image classification algorithm and the image compression algorithms have been implemented in JAVA.
Reply to Chang and Ram: Statistical Adequacy and the Reliability of Inference

FIRST, WE WOULD LIKE TO APOLOGIZE TO JIH CHANG AND RATI Ram for the tone of our Comment; we in no way meant to be denigrating. When submitting the paper we had no clue that such offense would be taken. On receiving the response from Chang and Ram and rereading what we said, we can see why offense was taken. If we could reword our Comment as it goes to electronic press, we would.
Routing method with backup path in WDM networks

This paper proposes a novel backup path reservation method for achieving high capacity in a WDM all-optical network. A set of core routers with wavelength converters configure an overlay network for providing higher shared backup path. The simulation results show that by applying the proposed method, wavelengths are reserved along 15.8% more message transmission routes than path protection
The Cost Effectiveness of Surgical Versus Nonoperative Treatment for Lumbar Disc Herniation Over Two Years: Evidence From the Spine Patient Outcomes Research Trial (SPORT)

Study Design. Spine Patient Outcomes Research Trial observational and randomized cohort participants with a confirmed diagnosis of intervertebral disc herniation (IDH) who received either usual nonoperative care and/or standard open discectomy were followed from baseline at 6 weeks, 3, 6, 12, and 24 months at 13 spine clinics in 11 US states. Objective. To evaluate the cost-effectiveness of surgery relative to nonoperative care among patients with a confirmed diagnosis of lumbar IDH. Summary of Background Data. The cost-effectiveness of surgery as a treatment for conditions associated with low back and leg symptoms remains poorly understood. Methods. Incremental cost-effectiveness ratio, reported as discounted cost per quality adjusted life year (QALY) gained in 2004 US dollars based on EuroQol EQ-5D health state values with US scoring, and information on resource utilization and time away from work. Results. Among 775 patients who underwent surgery and 416 who were treated nonoperatively, the mean difference in QALYs over 2 years was 0.21 (95% CI: 0.16–0.25) in favor of surgery. Surgery was more costly than nonoperative care; the mean difference in total cost was $14,137(95% CI: $11,737–16,770). The cost per QALY gained for surgery relative to nonoperative care was $69,403 (95% CI: $49,523–94,999) using general adult surgery costs and $34,355 (95% CI: $20,419–52,512) using Medicare population surgery costs. Conclusion. Surgery for IDH was moderately cost-effective when evaluated over 2 years. The estimated economic value of surgery varied considerably according to the method used for assigning surgical costs.
The Landscape of Complex Networks

Topological landscape is introduced for networks with functions defined on the nodes. By extending the notion of gradient flows to the network setting, critical nodes of different indices are defined. This leads to a concise and hierarchical representation of the network. Persistent homology from computational topology is used to design efficient algorithms for performing such analysis. Applications to some examples in social and biological networks are demonstrated, which show that critical nodes carry important information about structures and dynamics of such networks.
Understanding Policy Convergence in Britain and Germany

This introduction considers reasons why public policies might be expected to converge between Britain and Germany, arguing that the inter-related forces of globalisation, Europeanisation, policy transfer (in various guises) and the election of centre-left governance in 1997 and 1998 could be expected to lead to such convergence. It then outlines important reasons why such convergence may not occur, due to the radically different institutional settings, as well as ‘path dependence’ and the resilience of established institutions all playing a role in continuing divergence in a number of important areas of public policy.
Heteromeric Acid-Sensing Ion Channels (ASICs) Composed of ASIC2b and ASIC1a Display Novel Channel Properties and Contribute to Acidosis-Induced Neuronal Death

Acid-sensing ion channel (ASIC) subunits associate to form homomeric or heteromeric proton-gated ion channels in neurons throughout the nervous system. The ASIC1a subunit plays an important role in establishing the kinetics of proton-gated currents in the CNS, and activation of ASIC1a homomeric channels induces neuronal death after local acidosis that accompanies cerebral ischemia. The ASIC2b subunit is expressed in the brain in a pattern that overlaps ASIC1a, yet the contribution of ASIC2b has remained elusive. We find that coexpression of ASIC2b with ASIC1a in Xenopus oocytes results in novel proton-gated currents with properties distinct from ASIC1a homomeric channels. In particular, ASIC2b/1a heteromeric channels are inhibited by the nonselective potassium channel blockers tetraethylammonium and barium. In addition, steady-state desensitization is induced at more basic pH values, and Big Dynorphin sensitivity is enhanced in these unique heteromeric channels. Cultured hippocampal neurons show proton-gated currents consistent with ASIC2b contribution, and these currents are lacking in neurons from mice with an ACCN1 (ASIC2) gene disruption. Finally, we find that these ASIC2b/1a heteromeric channels contribute to acidosis-induced neuronal death. Together, our results show that ASIC2b confers unique properties to heteromeric channels in central neurons. Furthermore, these data indicate that ASIC2, like ASIC1, plays a role in acidosis-induced neuronal death and implicate the ASIC2b/1a subtype as a novel pharmacological target to prevent neuronal injury after stroke.
Metabolite Profiling of Hydroxycinnamate Derivatives in Plasma and Urine after the Ingestion of Coffee by Humans: Identification of Biomarkers of Coffee Consumption

Human subjects drank coffee containing 412 μmol of chlorogenic acids, and plasma and urine were collected 0 to 24 h after ingestion and were analyzed by high-performance liquid chromatography-mass spectrometry. Within 1 h, some of the components in the coffee reached nanomole peak plasma concentrations (Cmax), whereas chlorogenic acid metabolites, including caffeic acid-3-O-sulfate and ferulic acid-4-O-sulfate and sulfates of 3- and 4-caffeoylquinic acid lactones, had higher Cmax values. The short time to reach Cmax (Tmax) indicates absorption of these compounds in the small intestine. In contrast, dihydroferulic acid, its 4-O-sulfate, and dihydrocaffeic acid-3-O-sulfate exhibited much higher Cmax values (145–385 nM) with Tmax values in excess of 4 h, indicating absorption in the large intestine and the probable involvement of catabolism by colonic bacteria. These three compounds, along with ferulic acid-4-O-sulfate and dihydroferulic acid-4-O-glucuronide, were also major components to be excreted in urine (8.4–37.1 μmol) after coffee intake. Feruloylglycine, which is not detected in plasma, was also a major urinary component (20.7 μmol excreted). Other compounds, not accumulating in plasma but excreted in smaller quantities, included the 3-O-sulfate and 3-O-glucuronide of isoferulic acid, dihydro(iso)ferulic acid-3-O-glucuronide, and dihydrocaffeic acid-3-O-glucuronide. Overall, the 119.9 μmol excretion of the chlorogenic acid metabolites corresponded to 29.1% of intake, indicating that as well as being subject to extensive metabolism, chlorogenic acids in coffee are well absorbed. Pathways for the formation of the various metabolites within the body are proposed. Urinary dihydrocaffeic acid-3-O-sulfate and feruloylglycine are potentially very sensitive biomarkers for the consumption of relatively small amounts of coffee.
Protective Effect of Topiramate on Hyperglycemia-Induced Cerebral Oxidative Stress, Pericyte Loss and Learning Behavior in Diabetic Mice

Diabetes mellitus-associated damage to the microvasculature of the brain is caused by hyperglycemia-induced oxidative stress, which results in pericyte loss, blood-brain barrier disruption, and impaired cognitive function. Oxidative stress, in diabetes, is caused by reactive oxygen species produced during accelerated respiration (mitochondrial oxidative metabolism of glucose). The rate of respiration is regulated by mitochondrial carbonic anhydrases (CAs). Inhibition of these enzymes protects the brain from diabetic damage. Previously, we reported that topiramate, a mitochondrial CA inhibitor, at a dose of 50 mg/kg/day protects the brain in diabetes by reducing oxidative stress and restoring pericyte numbers. Topiramate has high affinity for both mitochondrial CAs; therefore, it is conceivable that a much lower dose may inhibit these enzymes and thus protect the brain from hyperglycemia-induced oxidative damage. Therefore, in an effort to reduce the toxicity associated with higher doses of topiramate, the current study was designed to investigate the effect of 1.0 mg/kg topiramate on reducing oxidative stress, restoring pericyte numbers in the brain, and improving the impaired learning behavior in diabetic mouse. Diabetes was induced by a one-time injection of streptozotocin and topiramate was administered daily for 12 weeks. Levels of oxidative stress, reduced glutathione (GSH) and 4-hydroxy-2-trans-nonenal (HNE) were measured in the brain and pericyte/endothelial cell ratios in isolated brain microvessels. Learning behavior was assessed by T-maze foot shock avoidance test. A significant decrease in GSH (control, 12.2 ± 0.4 vs. diabetic, 10.8 ± 0.4 vs. diabetic + topiramate, 12.6 ± 0.6, p<0.05) and an increase in HNE (control, 100 ± 4.2, vs. diabetic, 127.3 ± 8.8 vs. diabetic + topiramate, 93.9 ± 8.4 p<0.05) in diabetic mice were corrected by topiramate treatment. Topiramate treatment also resulted in restoration of pericyte numbers in diabetic mice (control, 25.89 ± 0.85 vs. diabetic, 18.14 ± 0.66 vs. diabetic + topiramate, 24.35 ± 0.53, p<0.001) and improvement in learning behavior. In conclusion, these data clearly demonstrate that topiramate at 1.0 mg/kg protects the mouse brain from diabetic damage. A 1.0 mg/kg topiramate in the mouse translates to a 5.0 mg daily dose in a 60 kg human, which may help slow the onset and progression of diabetic complications in the human brain.
Difficulties with multiple time stepping and fast multipole algorithm in molecular dynamics

Numerical experiments are performed on a 36,000‐atom protein–DNA–water simulation to ascertain the effectiveness of two devices for reducing the time spent computing long‐range electrostatics interactions. It is shown for Verlet‐I/r‐RESPA multiple time stepping, which is based on approximating long‐range forces as widely separated impulses, that a long time step of 5 fs results in a dramatic energy drift and that this is reduced by using an even larger long time step. It is also shown that the use of as many as six terms in a fast multipole algorithm approximation to long‐range electrostatics still fails to prevent significant energy drift even though four digits of accuracy is obtained. © 1997 John Wiley & Sons, Inc. J Comput Chem 18: 1785–1791, 1997
Stable bipedal ramp climbing with torso

This paper presents an analytical technique to study the stability of a bipedal robot with torso in dynamic ramp climbing. Climbing is an indispensable part of locomotion on stochastically rough terrain. Kinematics of stance and swing legs have been derived from first principles. The Zero Moment Point (ZMP) criterion has been analyzed with an extension to controlling torso angle to maintain stability for different ramp angles, step sizes, stepping speeds, mass, length, and angle of torso. We found the sensitivity, upper and lower bounds of the effect of the above parameters on the stable behavior of the ZMP curve during the single support phase of bipedal walking. We also present a broad insight into the range of control strategies available for metastable bipedal walker. Moreover, analytical tools derived from first principles helped us to prove the optimality of some of the characteristic behaviors of bipedal ramp climbing.
The Effects of Digital Intensity on Combinations of Sequential and Configural Process Variety

Two forms of variety have been noted in organizational processes: sequential and configural. These describe variations in how a work process is ordered (sequential) or what is involved in enacting each work activity (configural). Each has been mainly studied in isolation. In organizations, these two types of variety are always co-present and scholars will miss important insights if their dependencies and interactions are not examined. This calls for theorizing and empirical inquiries regarding how these two types of variety are related and how digitalization influences them. Our contribution in this paper is to call attention to the need to analyze these forms of variety simultaneously and invite a more thorough treatment of both forms of variety. The results of this exploratory study indicate that digitalization increases configural variety, but decreases sequential variety, that sequential and configural variety are positively related, and that sequential variety increases in concert with process size.
A Greedy Approach to Answer Reachability Queries on DAGs

Several modern applications involve huge graphs and require fast answers to reachability queries. In more than two decades since first proposals, several approaches have been presented adopting on-line searches, hop labelling or transitive closure compression. Transitive closure compression techniques usually construct a graph reachability index, for example by decomposing the graph into disjoint chains. As memory consumption is proportional to the number of chains, the target of those algorithms is to decompose the graph into an optimal number \width\ of chains. However, commonly used techniques fail to meet general expectations, are exceedingly complex, and their application on large graphs is impractical. The main contribution of this paper is a novel approach to construct such reachability indexes. The proposed method decomposes the graph into a sub-optimal number $\widehat{c}$ of chains by following a greedy strategy. We show that, given a vertex topological order, such a decomposition is obtained in $\mathcal{O}(\widehat{c} m)$ time, and requires $\mathcal{O}(\widehat{c} n)$ space, with $\widehat{c}$ bounded by $[c \log(\frac{n}{c})]$. We provide experimental evidence suggesting that, on different categories of automatically generated benchmarks as well as on graphs arising from the field of logic synthesis and formal verification, the proposed method produces a number of chains very close to the optimum, while significantly reducing computation time.
SPECIFIC COAGULASES OF STAPHYLOCOCCUS AUREUS

Three staphylococcal coagulases termed I, II, and III were differentiated by measuring the antibody titer of human sera. Coagulases I and II are antigenically distinct; coagulase III appears to be related to both coagulases I and II. These results were confirmed by specific neutralization experiments. These observations emphasize the importance of employing the correct type of coagulase in studying the role of this substance in the pathogenesis of staphylococcal infections. Preliminary observations in animals indicate that specific anticoagulase develops following induced infections. The role of this antibody in the recovery mechanism remains to be determined.
Accelerating Approximate Consensus with Self-Organizing Overlays

Laplacian-based approximate consensus algorithms are an important and frequently used building block in many distributed applications, including formation control, sensor fusion, and synchronization. These algorithms, however, converge extremely slowly on networks that are more than a few hops in diameter and where values are spatially correlated. This paper presents a new algorithm, Power Law Driven Consensus, which uses a self-organizing virtual overlay network to accelerate convergence, at a cost of decreasing the predictability of the final converged value. Experimental comparison with the Laplacian approach confirms that PLD-consensus allows for drastically faster convergence in spatial networks.
Tax Auditing as a Public Good Game: An Experimental Study on Punishment and Compliance

Prior experimental studies on tax evasion generally assume that the budget and the probability of audit are exogenously given, and ignore taxpayers' incentives to detect evasion and their compliance behaviour under such incentives. The experimental evidence of the present paper shows that, on average, subjects are willing to spend 20 to 30% of their tax revenue on auditing. Compliance is also greatly improved if subjects can determine the budget and, hence, the probability of audit. These findings suggest that taking taxpayers' incentives to detect evasion into consideration is important for the design of compliance‐improvement audit schemes.
Employ Bump Mapping to Enrich the 3D NPR Image

this paper presents a simple approach for adding more details to non-photorealistic image without increasing the complexity of the model. Bump mapping technique is introduced to create the details that can vary automatically with the change of light and view direction, but this technique originally aims to make a rendered surface look more realistic, so we present an algorithm to stylize it the same to achieve overall stylistic effect. We also present a novel approach for drawing multiple lines in GPU, and all the algorithms in this paper are based on GPU.