Miracle-dz/UniFAR-FTUs huggingface dataset:
pRAM n-tuple Classifier - a new architecture of probabilistic RAM neurons for classification problems

RAM-based neural networks have been in the market long before the MultiLayer Perceptrons but their developments have been concentrated in a few periods and research groups. Recently, one of the winners of the PAKDD 2007 Competition used a variation of one of such architectures in their data mining solution. Now, that approach for binary decision problems has been refined and is presented in this paper as the pRAM n-tuple Classifier. It consists of a single layer neural network inspired by the n-tuple classifier but with advantages in several aspects: 1) it does not need special binary encoding for continuous variables, 2) it generalizes smoothly, and 3) its performance improves with the increase in the amount of training examples without saturating. Experimental comparison carried out on the Proben1 benchmark problems against MultiLayer Perceptrons shows that there is no statistically significant difference between them. The pRAM n-tuple Classifier also has the advantage of using all modeling data for training once that it does not require a validation set, which is particularly important for problems with small data sets.
Induction of apoptosis by cancer chemotherapy.

Studies performed over the past five years have demonstrated that there are two major cell-intrinsic pathways for inducing apoptosis, one that begins with ligation of cell surface death receptors and another that involves mitochondrial release of cytochrome c. Several reports have suggested that anticancer drugs kill susceptible cells by inducing expression of death receptor ligands, especially Fas ligand (FasL). Other reports have indicated that chemotherapeutic agents trigger apoptosis by inducing release of cytochrome c from mitochondria. In this review, we describe the two prototypic death pathways, indicate experimental approaches for distinguishing whether chemotherapeutic agents trigger one pathway or the other, summarize current understanding of the role of the two pathways in chemotherapy-induced apoptosis, and discuss the implications of these studies for mechanisms of resistance to chemotherapeutic agents.
Reachability Does Not Explain the Middle Preference: A Comment on Bar-Hillel (2015)

Choosing an object from an array of similar objects is a task that people complete frequently throughout their lives (e.g., choosing a can of soup from many cans of soup). Research has also demonstrated that items in the middle of an array or scene are looked at more often and are more likely to be chosen. This middle preference is surprisingly robust and widespread, having been found in a wide range of perceptual-motor tasks. In a recent review of the literature, Bar-Hillel (2015) proposes, among other things, that the middle preference is largely explained by the middle item being easier to reach, either physically or mentally. We specifically evaluate Bar-Hillel’s reachability explanation for choice in non-interactive situations in light of evidence showing an effect of item valence on such choices. This leads us to conclude that the center-stage heuristic account is a more plausible explanation of the middle preference.
Privacy Implications of New York City's Stop-and-Frisk Data

A wider release of police datasets could enable social scientists, community activists, and civil libertarians to more effectively challenge discriminatory policing practices. However, the privacy implications of such sharing must be carefully considered. It is known that “de-identifying” data is not sufficient to protect the privacy of individuals. New York City’s stop-and-frisk data is an example of one such police dataset. The stop-and-frisk data contains information (including demographic information) about all people stopped by the program from 2003 to 2012. This paper examines the identifiability of this data. It examines the uniqueness of the data to investigate the privacy implications of its release for the individuals targeted by stop-and-frisk. It also suggests ways to re-identify this data. Thesis Supervisor: Darakhshan J. Mir Title: Norma Wilentz Hess Fellow in Computer Science
The Kalman Filter 1 Recursive State Estimation

The Kalman Filter developed in the early sixties by R.E. Kalman [7, 8] is a recursive state estimator for partially observed non-stationary stochastic processes. It gives an optimal estimate in the least squares sense of the actual value of a state vector from noisy observations. Consider a discrete-time stochastic process x k+1 = f (x k , u k , v k) (1) with system input u and unmodeled process dynamics plus noise v. The task at hand is to find an estimate of the state vector x. However, x is only accessible from noise distorted sensor measurements z k = h(x k , w k) (2) in which as with the process model, w represents observation model inaccuracies and sensor noise. Recursive state estimation consists on iteratively reconstructing the state vector from our knowledge of the process dynamics, the measurement model, and the sensed data.
Nonlinear Diffusion in Graphics Hardware

Multiscale methods have proved to be successful tools in image denoising, edge enhancement and shape recovery. They are based on the numerical solution of a nonlinear diffusion problem where a noisy or damaged image which has to be smoothed or restorated is considered as initial data. Here a novel approach is presented which will soon be capable to ensure real time performance of these methods. It is based on an implementation of a corresponding finite element scheme in texture hardware of modern graphics engines. The method regards vectors as textures and represents linear algebra operations as texture processing operations. Thus, the resulting performance can profit from the superior bandwidth and the build in parallelism of the graphics hardware. Here the concept of this approach is introduced and perspectives are outlined picking up the basic Perona Malik model on 2D images.
The Ordered Weighted $\ell_1$ Norm: Atomic Formulation, Dual Norm, and Projections.

The ordered weighted $\ell_1$ norm (OWL) was recently proposed, with two different motivations: because of its good statistical properties as a sparsity promoting regularizer, and as generalization of the so-called {\it octagonal shrinkage and clustering algorithm for regression} (OSCAR). The OSCAR is a convex group-sparsity inducing regularizer, which does not require the prior specification of the group structure. Also recently, much interest has been raised by the atomic norm formulation of several regularizers, not only because it provides an new avenue for their theoretical characterization, but also because it is particularly well suited to a type of method known as {\it conditional gradient} (CG), or Frank-Wolfe, algorithm. In this paper, we derive the atomic formulation of the OWL and exploit this formulation to show how Tikhonov regularization schemes can be handled using state-of-the-art proximal splitting algorithms, while Ivanov regularization can be efficiently implemented via the Frank-Wolfe algorithm.
Mobile phone addiction

Recent technological developments have turned mobile phones into multifunctional machines for everyday use. The arrival of the smartphone brought convenience to interpersonal conversation, social networking, agenda management, entertainment, shopping, and other personal activities. Probably no other modern device is embedded into our lives as deeply as the mobile phone. However, an alarming consequence of this embedding has begun to emerge. Excessive dependency upon this technology leads to serious psychological and behavioral impacts on mobile phone users. In particular, as mobile phones embrace features and capabilities from laptop computers and telecommunication technologies, such as easy-to-use interfaces, mobility, Internet access, interactive games, and access to social media (e.g., Facebook, WhatsApp, and Instagram), the potential risk of uncontrolled use increases greatly. In recent years, studies have shed light on the behavioral health issues related to the problematic use of mobile phones. Examining the literature, we can find a group of similar terminologies that fall under the conceptual umbrella of problematic mobile phone use, including mobile phone addiction, mobile phone dependency, and pathological or maladaptive mobile phone use. Since these constructs were developed in similar academic disciplines (e.g., social psychology, communication, and behavioral health) using theoretical models and explanations with shared focuses and elements, these concepts are often interchangeable. Today, as mobile phones become increasingly sophisticated and multifunctional, adolescents and young users are becoming increasingly dependent, or “addicted,” to this technology, not only for interpersonal communication through voice or text (i.e., short messaging service–SMS) but also as a tool for seeking gratification, searching for information, entertainment, relaxation, passing time, picture and video taking, and expressing status and identity, as well as currently undiscovered applications (Charlton, Panting, & Hannan, 2002; Leung & Wei, 2000). This chapter provides a clear definition of mobile phone addiction and reviews the literature surrounding it, focusing especially on diagnostic criteria, predictors, symptoms, and consequences of this addictive behavior.
Increasing propensity to mind-wander with transcranial direct current stimulation

Significance Mind wandering is a spontaneous and self-generated behavior believed to be important for many mental functions, including creativity and future planning. Can the propensity to mind-wander be modulated externally? If so, this observation would mean that directly modifying spontaneous neural activity can change internally directed thought. To answer this question, we used noninvasive transcranial direct current stimulation (tDCS) to stimulate the prefrontal cortex. Our results showed, for the first time to our knowledge, that mind wandering, probably the most omnipresent internal cognitive function, can be enhanced by external stimulation. In addition, we showed that the frontal lobes play a causal role in mind wandering. We furthermore suggest that the executive control system, and specifically the dorsolateral prefrontal cortex, might play an important role in mind-wandering behavior. Humans mind-wander quite intensely. Mind wandering is markedly different from other cognitive behaviors because it is spontaneous, self-generated, and inwardly directed (inner thoughts). However, can such an internal and intimate mental function also be modulated externally by means of brain stimulation? Addressing this question could also help identify the neural correlates of mind wandering in a causal manner, in contrast to the correlational methods used previously (primarily functional MRI). In our study, participants performed a monotonous task while we periodically sampled their thoughts to assess mind wandering. Concurrently, we applied transcranial direct current stimulation (tDCS). We found that stimulation of the frontal lobes [anode electrode at the left dorsolateral prefrontal cortex (DLPFC), cathode electrode at the right supraorbital area], but not of the occipital cortex or sham stimulation, increased the propensity to mind-wander. These results demonstrate for the first time, to our knowledge, that mind wandering can be enhanced externally using brain stimulation, and that the frontal lobes play a causal role in mind-wandering behavior. These results also suggest that the executive control network associated with the DLPFC might be an integral part of mind-wandering neural machinery.
Less Pollen-Mediated Gene Flow for More Signatures of Glacial Lineages: Congruent Evidence from Balsam Fir cpDNA and mtDNA for Multiple Refugia in Eastern and Central North America

The phylogeographic structure and postglacial history of balsam fir (Abies balsamea), a transcontinental North American boreal conifer, was inferred using mitochondrial DNA (mtDNA) and chloroplast DNA (cpDNA) markers. Genetic structure among 107 populations (mtDNA data) and 75 populations (cpDNA data) was analyzed using Bayesian and genetic distance approaches. Population differentiation was high for mtDNA (dispersed by seeds only), but also for cpDNA (dispersed by seeds and pollen), indicating that pollen gene flow is more restricted in balsam fir than in other boreal conifers. Low cpDNA gene flow in balsam fir may relate to low pollen production due to the inherent biology of the species and populations being decimated by recurrent spruce budworm epidemics, and/or to low dispersal of pollen grains due to their peculiar structural properties. Accordingly, a phylogeographic structure was detected using both mtDNA and cpDNA markers and population structure analyses supported the existence of at least five genetically distinct glacial lineages in central and eastern North America. Four of these would originate from glacial refugia located south of the Laurentide ice sheet, while the last one would have persisted in the northern Labrador region. As expected due to reduced pollen-mediated gene flow, congruence between the geographic distribution of mtDNA and cpDNA lineages was higher than in other North American conifers. However, concordance was not complete, reflecting that restricted but nonetheless detectable cpDNA gene flow among glacial lineages occurred during the Holocene. As a result, new cpDNA and mtDNA genome combinations indicative of cytoplasmic genome capture were observed.
Nonminimum Phase Dynamic Inversion for Settle Time Applications

Single-track hard disk drive (HDD) seek performance is measured by settle time, ts. In this paper, we show the effective use of feedforward dynamic inversion, coupled with reference trajectory yd generation, to achieve high performance ts. Models of HDD dynamics are typically nonminimum phase (NMP), and it is well known that the exact tracking solution for NMP systems requires noncausal preactuation to maintain bounded internal signals. In the specific HDD operating modes of interest, anticipation of a seek command is unrealistic, and thus preactuation adds to the overall computation of settle time. Unlike many dynamic inversion tracking applications, this negative effect of preactuation leads to interesting trade-offs between preactuation delay, yd tracking accuracy, and achievable settle performance. We investigate multiple single-input single-output (SISO) inversion architectures, and we show that the feedforward closed-loop inverse (FFCLI) achieves superior settle performance to the feedforward plant inverse (FFPI) in our application because FFCLI does not excite the closed-loop dynamics. Using the FFCLI architecture, we further investigate numerous NMP inversion algorithms, including both exact inversion schemes with initial condition preloading and stable approximate NMP inverse techniques. We conclude that the settle performance of the zero-order Taylor series stable NMP approximation matches the best performance of the exact inversion techniques in our application, and does so without the high frequency excitation required by the zero magnitude error tracking controller (ZMETC), or the excessive preactuation required by the zero phase error tracking controller (ZPETC). Minimum energy optimal trajectory generation methods show that the system order n is a limiting factor in settle performance. This confirms that the zero-order series method, which is capable of producing settle times in less than n samples, is on par with optimal approaches yet much simpler to implement. Multiple NMP inversion algorithms are experimentally validated on a servo track writer (STW), which reinforces the general trends observed in ideal simulations.
Sulfated Polysaccharide, Curdlan Sulfate, Efficiently Prevents Entry/Fusion and Restricts Antibody-Dependent Enhancement of Dengue Virus Infection In Vitro: A Possible Candidate for Clinical Application

Curdlan sulfate (CRDS), a sulfated 1→3-β-D glucan, previously shown to be a potent HIV entry inhibitor, is characterized in this study as a potent inhibitor of the Dengue virus (DENV). CRDS was identified by in silico blind docking studies to exhibit binding potential to the envelope (E) protein of the DENV. CRDS was shown to inhibit the DENV replication very efficiently in different cells in vitro. Minimal effective concentration of CRDS was as low as 0.1 µg/mL in LLC-MK2 cells, and toxicity was observed only at concentrations over 10 mg/mL. CRDS can also inhibit DENV-1, 3, and 4 efficiently. CRDS did not inhibit the replication of DENV subgenomic replicon. Time of addition experiments demonstrated that the compound not only inhibited viral infection at the host cell binding step, but also at an early post-attachment step of entry (membrane fusion). The direct binding of CRDS to DENV was suggested by an evident reduction in the viral titers after interaction of the virus with CRDS following an ultrafiltration device separation, as well as after virus adsorption to an alkyl CRDS-coated membrane filter. The electron microscopic features also showed that CRDS interacted directly with the viral envelope, and caused changes to the viral surface. CRDS also potently inhibited DENV infection in DC-SIGN expressing cells as well as the antibody-dependent enhancement of DENV-2 infection. Based on these data, a probable binding model of CRDS to DENV E protein was constructed by a flexible receptor and ligand docking study. The binding site of CRDS was predicted to be at the interface between domains II and III of E protein dimer, which is unique to this compound, and is apparently different from the β-OG binding site. Since CRDS has already been tested in humans without serious side effects, its clinical application can be considered.
Box-trees for collision checking in industrial installations

A box-tree is a bounding-volume hierarchy that uses axis-aligned boxes as bounding volumes. We describe a new algorithm to construct a box-tree for a 3D scene consisting of n objects, and we analyze its worst-case query time for approximate range queries. If the input scene has certain characteristics that we derived from our application---collision detection in industrial installations---then the query times are polylogarithmic, not only for searching with boxes but also for range searching with other constant-complexity ranges.
β3 Integrin in Cardiac Fibroblast Is Critical for Extracellular Matrix Accumulation during Pressure Overload Hypertrophy in Mouse

The adhesion receptor β3 integrin regulates diverse cellular functions in various tissues. As β3 integrin has been implicated in extracellular matrix (ECM) remodeling, we sought to explore the role of β3 integrin in cardiac fibrosis by using wild type (WT) and β3 integrin null (β3−/−) mice for in vivo pressure overload (PO) and in vitro primary cardiac fibroblast phenotypic studies. Compared to WT mice, β3−/− mice upon pressure overload hypertrophy for 4 wk by transverse aortic constriction (TAC) showed a substantially reduced accumulation of interstitial fibronectin and collagen. Moreover, pressure overloaded LV from β3−/− mice exhibited reduced levels of both fibroblast proliferation and fibroblast-specific protein-1 (FSP1) expression in early time points of PO. To test if the observed impairment of ECM accumulation in β3−/− mice was due to compromised cardiac fibroblast function, we analyzed primary cardiac fibroblasts from WT and β3−/− mice for adhesion to ECM proteins, cell spreading, proliferation, and migration in response to platelet derived growth factor-BB (PDGF, a growth factor known to promote fibrosis) stimulation. Our results showed that β3−/− cardiac fibroblasts exhibited a significant reduction in cell-matrix adhesion, cell spreading, proliferation and migration. In addition, the activation of PDGF receptor associated tyrosine kinase and non-receptor tyrosine kinase Pyk2, upon PDGF stimulation were impaired in β3−/− cells. Adenoviral expression of a dominant negative form of Pyk2 (Y402F) resulted in reduced accumulation of fibronectin. These results indicate that β3 integrin-mediated Pyk2 signaling in cardiac fibroblasts plays a critical role in PO-induced cardiac fibrosis.
Cell-probe lower bounds for dynamic problems via a new communication model

In this paper, we develop a new communication model to prove a data structure lower bound for the dynamic interval union problem. The problem is to maintain a multiset of intervals I over [0, n] with integer coordinates, supporting the following operations: 1) insert(a, b), add an interval [a, b] to I, provided that a and b are integers in [0, n]; 2) delete(a, b), delete an (existing) interval [a, b] from I; 3) query(), return the total length of the union of all intervals in I. It is related to the two-dimensional case of Klee’s measure problem. We prove that there is a distribution over sequences of operations with O(n) insertions and deletions, and O(n0.01) queries, for which any data structure with any constant error probability requires Ω(nlogn) time in expectation. Interestingly, we use the sparse set disjointness protocol of Håstad and Wigderson to speed up a reduction from a new kind of nondeterministic communication games, for which we prove lower bounds. For applications, we prove lower bounds for several dynamic graph problems by reducing them from dynamic interval union.
Measuring skeletal muscle strength and endurance, from bench to bedside.

Peripheral muscle dysfunction is a recognized and important systemic consequence of many chronic diseases. Peripheral muscle weakness is associated with excess utilization of health care recourses, morbidity and /or mortality in patients with COPD, congestive heart failure, liver and frail elderly. In the latter group, muscle weakness was associated with significant increase in falling and falling related injury. Exercise training does enhance skeletal muscle function and exercise performance. In addition, patients who start a training program with impaired skeletal muscle function may be more likely to respond adequately to an exercise training program. It is beyond the scope of the present review to discuss in detail the factors that may contribute to muscle dysfunction in chronic conditions. Clearly, muscle weakness is multi-factorial. Factors associated with skeletal muscle force are general factors (such as age, body weight, sex), disease related factors (such as inactivity) and disease specific factors (for example in COPD drug treatment, i.e. corticosteroid treatment, inflammation, oxidative stress and hypoxia have been shown to contribute to muscle dysfunction). This review will focus on the different ways to assess skeletal muscle function in patients with chronic disease. More specifically, techniques to assess skeletal muscle strength, skeletal muscle endurance and skeletal muscle fatigue will be discussed. For the American College of Sport Medicine (ACSM) not only muscle strength but also muscle endurance are health- related fitness components. Loss in one of these muscle characteristics results in impaired muscle. Muscle function tests are very specific to the muscle group tested, the type of contraction, the velocity of muscle motion, the type of equipment and the joint range of motion. Results of any test are specific to the procedures used. Individuals should participate in familiarization sessions with the equipment, and adhere to a specific protocol in order to obtain a true and reliable score. A change in one’s muscular fitness over time can be based on the absolute value of the external force (Newton (N)), but when comparisons are made between individuals, the values should be expressed as relative values (percentage of a predicted normal value). In both cases, caution must be taken in the interpretation of the result because the norms may not include a representative sample of the individual being measured, a standardized protocol may be absent, or the exact test being used may differ.