Miracle-dz/UniFAR-FTUs huggingface dataset:
A Short History of Computational Complexity

It all started with a machine. In 1936, Turing developed his theoretical computational model. He based his model on how he perceived mathematicians think. As digital computers were developed in the 40’s and 50’s, the Turing machine proved itself as the right theoretical model for computation. Quickly though we discovered that the basic Turing machine model fails to account for the amount of time or memory needed by a computer, a critical issue today but even more so in those early days of computing. The key idea to measure time and space as a function of the length of the input came in the early 1960’s by Hartmanis and Stearns. And thus computational complexity was born. In the early days of complexity, researchers just tried understanding these new measures and how they related to each other. We saw the first notion of efficient computation by using time polynomial in the input size. This led to complexity’s most important concept, NP-completeness, and its most fundamental question, whether P = NP. The work of Cook and Karp in the early 70’s showed a large number of combinatorial and logical problems were NP-complete, i.e., as hard as any problem computable in nondeterministic polynomial time. The P = NP question is equivalent to an efficient solution of any of these problems. In the thirty years hence this problem has become one of the outstanding open questions in computer science and indeed all of mathematics. In the 70’s we saw the growth of complexity classes as researchers tried to encompass different models of computations. One of those models, probabilistic computation, started with a probabilistic test for primality, led to probabilistic complexity classes and a new kind of interactive proof system that itself led to hardness results for approximating certain NP-complete problems. We have also seen strong evidence that we can remove the randomness from computations and most recently a deterministic algorithm for the original primality problem. In the 80’s we saw the rise of finite models like circuits that capture computation in an inherently different way. A new approach to problems like P = NP arose from these circuits and though they have had limited success in separating complexity classes, this approach brought combinatorial techniques into the area and led to a much better understanding of the limits of these devices. ∗URL: http://www.neci. nj.nec.com/homepages/fortnow. Email: fortnow@research.nj.nec.com. †URL: http://www.cs.bu.edu/faculty/homer. Email: homer@cs.bu.edu. Supported in part by the NSF under grant NSF-CCR-998310 and by the ARO under grant DAAD19-02-1-0058.
Bypass Valve Modeling and Surge Control for turbocharged SI engines

Since measurements in engine test cells are closely coupled with high costs it is of interest to use physically interpretable engine models instead of engine maps. Such engine models can also be used to do off-line tests of how new or altered components affect engine performance. In the thesis an existing mean value engine model will be extended with a model of a compressor bypass valve. A controller for that valve will also be developed. The purpose with that controller is to save torque and boost pressure but at the same time avoid having the compressor entering surge during fast closing transients in the throttle position. Both the extension and controller is successfully developed and implemented. The extension lowers the pressure after the compressor and increases the pressure before the compressor when the bypass valve is being opened and the controller shows better results in simulations than the present controller used in the research lab. By using the proposed controller, as much as 5 percent higher torque can be achieved in simulations. Finally, there is a discussion on wastegate control alternatives and the use of TOMOC for optimization of wastegate control.
Performance Analysis of Low Power Null Convention Logic Units with Power Cutoff

Null convention logic units are the most important logic units in asynchronous circuits. This paper proposes a new realization of null convention logic unit based on semi-static threshold gates. Through adding a cutoff transistor into the pull-up path, the leakage current can be greatly decreased, which can resolve the issue of leakage current increment in deep submicron technology. Comparisons are made on delay, area, power consumption as well as working speed with the conventional logic units. One bit asynchronous adder and basic gates are realized based on the proposed null convention logic unit and comparisons are made on performance and power consumption. Results have shown that the new null convention logic unit has significant decrements in dynamic and static power consumption. Dynamic power consumption of TH33 gate has decreased by 13.6%, and 72.9% to the static power consumption. The newly design proposal can satisfy the requirement of low power asynchronous design.
Recommending the Right Activities based on the Needs of each Student

Today more than ever, personalization is the most important feature that a system needs to exhibit. The goal of many online systems, which are available in many areas, is to address the needs or desires of each individual user. To achieve this goal, these systems need to rely on a good recommendation system. Hence, recommendation systems must work under the assumption that an individual’s need could also be applied to someone else who has similar desires, tastes, and/or necessities. In this paper, we took this assumption into account and applied it to the context of learning computer programming. As a result, we present a system that recommends additional activities to students according to their individual needs. An additional assumption that is used is that a prompt reply and tailored guidance at each step of the learning process improves an individual’s chances of success. We propose the use of the kNN algorithm to recommend activities that are as similar as possible to those that an expert would assign. The results are promising because we were able to mimic the human assessment decisions 90.0% of the time.
Earthquake Recurrence and the Resolution Potential of Tectono‐Geomorphic Records

The author would like to thank James Dolan for his encouragement to finalize this study. The author also wants to thank the reviewers, Editor-in-Chief Thomas Pratt, and Associate Editor Richard Briggs for their valuable comments that helped further strengthen this contribution. This study was supported by the P. M. Mai and Computational Earthquake Seismology Group, with funding from King Abdullah University of Science and Technology (KAUST).
WAVY LEAF1, an Ortholog of Arabidopsis HEN1, Regulates Shoot Development by Maintaining MicroRNA and Trans-Acting Small Interfering RNA Accumulation in Rice1[C][W]

In rice (Oryza sativa), trans-acting small interfering RNA (ta-siRNA) is essential for shoot development, including shoot apical meristem (SAM) formation and leaf morphogenesis. The rice wavy leaf1 (waf1) mutant has been identified as an embryonic mutant resembling shoot organization1 (sho1) and sho2, homologs of a loss-of-function mutant of DICER-LIKE4 and a hypomorphic mutant of ARGONAUTE7, respectively, which both act in the ta-siRNA production pathway. About half of the waf1 mutants showed seedling lethality due to defects in SAM maintenance, but the rest survived to the reproductive phase and exhibited pleiotropic phenotypes in leaf morphology and floral development. Map-based cloning of WAF1 revealed that it encodes an RNA methyltransferase, a homolog of Arabidopsis (Arabidopsis thaliana) HUA ENHANCER1. The reduced accumulation of small RNAs in waf1 indicated that the stability of the small RNA was decreased. Despite the greatly reduced level of microRNAs and ta-siRNA, microarray and reverse transcription-polymerase chain reaction experiments revealed that the expression levels of their target genes were not always enhanced. A double mutant between sho and waf1 showed an enhanced SAM defect, suggesting that the amount and/or quality of ta-siRNA is crucial for SAM maintenance. Our results indicate that stabilization of small RNAs by WAF1 is indispensable for rice development, especially for SAM maintenance and leaf morphogenesis governed by the ta-siRNA pathway. In addition, the inconsistent relationship between the amount of small RNAs and the level of the target mRNA in waf1 suggest that there is a complex regulatory mechanism that modifies the effects of microRNA/ta-siRNA on the expression of the target gene.
Phase Minimization for Glottal Model Estimation

In glottal source analysis, the phase minimization criterion has already been proposed to detect excitation instants. As shown in this paper, this criterion can also be used to estimate the shape parameter of a glottal model (ex. Liljencrants-Fant model) and not only its time position. Additionally, we show that the shape parameter can be estimated independently of the glottal model position. The reliability of the proposed methods is evaluated with synthetic signals and compared to that of the IAIF and minimum/maximum-phase decomposition methods. The results of the methods are evaluated according to the influence of the fundamental frequency and noise. The estimation of a glottal model is useful for the separation of the glottal source and the vocal-tract filter and therefore can be applied in voice transformation, synthesis, and also in clinical context or for the study of the voice production.
A Machine Learning Approach to Enhance Scoring Performance in Docking-Based Virtual Screening Experiments: COX-1 as a Case Study

Molecular docking can be reasonably successful at reproduc- ing X-ray poses of a ligand in the binding site of a protein. However, scoring functions are typically unsuccessful at correctly ranking ligands according to their binding anity. Using cyclooxygenase-1 (COX-1), a particularly challenging workhorse in virtual screening (VS) we show how the use of support vector machines (SVMs), trained with the indi- vidual energy terms retrieved from docking-based VS experiments, can improve the discrimination between active and inactive compounds. Ac- tives and inactives for COX-1 were obtained from the Directory of Use- ful Decoys (DUD) and docked into COX-1 with AutoDock Vina (Vina). The energy parameters of Vina's scoring function were used to train classication models with SVM-light. The results show that Vina oers acceptable pose prediction accuracy, but its scoring function performs poorly compared to our SVM classication models. The superior per- formance of the trained classication models highlights the potential of using non-linear machine learning methods to identify bioactive com- pounds through docking-based screening.
Divisive Gain Modulation with Dynamic Stimuli in Integrate-and-Fire Neurons

The modulation of the sensitivity, or gain, of neural responses to input is an important component of neural computation. It has been shown that divisive gain modulation of neural responses can result from a stochastic shunting from balanced (mixed excitation and inhibition) background activity. This gain control scheme was developed and explored with static inputs, where the membrane and spike train statistics were stationary in time. However, input statistics, such as the firing rates of pre-synaptic neurons, are often dynamic, varying on timescales comparable to typical membrane time constants. Using a population density approach for integrate-and-fire neurons with dynamic and temporally rich inputs, we find that the same fluctuation-induced divisive gain modulation is operative for dynamic inputs driving nonequilibrium responses. Moreover, the degree of divisive scaling of the dynamic response is quantitatively the same as the steady-state responses—thus, gain modulation via balanced conductance fluctuations generalizes in a straight-forward way to a dynamic setting.
Geometric Models of Rolling-Shutter Cameras

Cameras with rolling shutters are becoming more common as low-power, low-cost CMOS sensors are being used more frequently in cameras. The rolling shutter means that not all scanlines are exposed over the same time interval. The effects of a rolling shutter are noticeable when either the camera or objects in the scene are moving and can lead to systematic biases in projection estimation. We develop a general projection equation for a rolling shutter camera and show how it is affected by different types of camera motion. In the case of fronto-parallel motion, we show how that camera can be modeled as an X-slit camera. We also develop approximate projection equations for a non-zero angular velocity about the optical axis and approximate the projection equation for a constant velocity screw motion. We demonstrate how the rolling shutter effects the projective geometry of the camera and in turn the structure-from-motion.
A minimax approach to Bayesian estimation with partial knowledge of the observation model

We address the problem of Bayesian estimation where the statistical relation between the signal and measurements is only partially known. We propose modeling partial Baysian knowledge by using an auxiliary random vector called instrument. The joint probability distributions of the instrument and the signal, and of the instrument and the measurements, are known. However, the joint probability function of the signal and measurements is unknown. Our model generalizes that underlying the method of instrumental variables from statistics, in that the instrument does not have to satisfy any requirements and no parametric form for the optimal regressor needs to be available. We begin by deriving an estimator for this scenario, via a worst-case design strategy. We then propose a non-parametric method for learning this estimator from a set of examples. Finally, we demonstrate our approach in the context of enhancement of facial images that have undergone an unknown degradation.
Design of a Rotational Hydroelastic Actuator for a Powered Exoskeleton for Upper Limb Rehabilitation

The goal of this study was to validate the suitability of a novel rotational hydroelastic actuator (rHEA) for use in our new rehabilitation exoskeleton for the upper limbs, the Limpact. The rHEA consists of a rotational hydraulic actuator and a custom-designed symmetric torsion spring in a series-elastic configuration. For rehabilitation therapy and impairment quantification, both compliant impedance control and stiff admittance control modes are possible. In the validation experiments, the torque bandwidth of the rHEA was limited to 18 Hz for a desired 20 N·m reference signal (multisine, constant spectrum) due the transport delays in the long flexible tubes between the valve and cylinder. These transport delays also required changes to existing theoretical models to better fit the models on the measured frequency response functions. The (theoretical) measurable torque resolution was better than 0.01 N ·m and the (validated) delivered torque resolution below 1 N· m. After the validation experiments, further iterative improvements resulted in a spring design capable of a maximum output torque of 50 N·m with an intrinsic stiffness of 150 N· m/rad and a slightly higher bandwidth. With the design locked, the maximum measurable isometric torque is 100 N ·m. In conclusion, the rHEA is suitable for upper limb rehabilitation therapy as it matches the desired performance.
Genetic switchboard for synthetic biology applications

A key next step in synthetic biology is to combine simple circuits into higher-order systems. In this work, we expanded our synthetic riboregulation platform into a genetic switchboard that independently controls the expression of multiple genes in parallel. First, we designed and characterized riboregulator variants to complete the foundation of the genetic switchboard; then we constructed the switchboard sensor, a testing platform that reported on quorum-signaling molecules, DNA damage, iron starvation, and extracellular magnesium concentration in single cells. As a demonstration of the biotechnological potential of our synthetic device, we built a metabolism switchboard that regulated four metabolic genes, pgi, zwf, edd, and gnd, to control carbon flow through three Escherichia coli glucose-utilization pathways: the Embden–Meyerhof, Entner–Doudoroff, and pentose phosphate pathways. We provide direct evidence for switchboard-mediated shunting of metabolic flux by measuring mRNA levels of the riboregulated genes, shifts in the activities of the relevant enzymes and pathways, and targeted changes to the E. coli metabolome. The design, testing, and implementation of the genetic switchboard illustrate the successful construction of a higher-order system that can be used for a broad range of practical applications in synthetic biology and biotechnology.
Patch‐Collaborative Spectral Point‐Cloud Denoising

We present a new framework for point cloud denoising by patch‐collaborative spectral analysis. A collaborative generalization of each surface patch is defined, combining similar patches from the denoised surface. The Laplace–Beltrami operator of the collaborative patch is then used to selectively smooth the surface in a robust manner that can gracefully handle high levels of noise, yet preserves sharp surface features. The resulting denoising algorithm competes favourably with state‐of‐the‐art approaches, and extends patch‐based algorithms from the image processing domain to point clouds of arbitrary sampling. We demonstrate the accuracy and noise‐robustness of the proposed algorithm on standard benchmark models as well as range scans, and compare it to existing methods for point cloud denoising.
Aldehyde Dehydrogenase 1 Identifies Cells with Cancer Stem Cell-Like Properties in a Human Renal Cell Carcinoma Cell Line

Cancer stem cells (CSC) or cancer stem cell-like cells (CSC-LCs) have been identified in many malignant tumors. CSCs are proposed to be related with drug resistance, tumor recurrence, and metastasis and are considered as a new target for cancer treatment; however, there are only a few reports on CSCs or CSC-LCs in renal cell carcinoma (RCC). Different approaches have been reported for CSC identification, but there are no universal markers for CSC. We used two different approaches, the traditional side population (SP) approach, and the enzymatic (aldehyde dehydrogenase 1 (ALDH1)) approach to identify CSC-LC population in two RCC cell lines, ACHN and KRC/Y. We found that ACHN and KRC/Y contain 1.4% and 1.7% SP cells, respectively. ACHN SP cells showed a higher sphere forming ability, drug resistance, and a slightly higher tumorigenic ability in NOD/SCID mice than Non-SP (NSP) cells, suggesting that cells with CSC-LC properties are included in ACHN SP cells. KRC/Y SP and NSP cells showed no difference in such properties. ALDH1 activity analysis revealed that ACHN SP cells expressed a higher level of activity than NSP cells (SP vs. NSP: 32.7% vs 14.6%). Analysis of ALDH1-positive ACHN cells revealed that they have a higher sphere forming ability, self-renewal ability, tumorigenicity and express higher mRNA levels of CSC-LC property-related genes (e.g., ABC transporter genes, self-replication genes, anti-apoptosis genes, and so forth) than ALDH1-negative cells. Drug treatment or exposure to hypoxic condition induced a 2- to 3-fold increase in number of ALDH1-positive cells. In conclusion, the results suggest that the ALDH1-positive cell population rather than SP cells show CSC-LC properties in a RCC cell line, ACHN.
A Case Study of the Economic Impact of Seasonal Visitors to a Lake Watershed Environment

Ecosystem services generated by lake watershed environments can be important drivers of local and regional economic activity. In this analysis we use expenditure data collected from a survey of 445 seasonal visitors and year-round residents in a unique lake watershed environment to estimate their impact on the region’s economy. Our survey and research methods were designed to explore social and economic dimensions of the area as well as capture information on spending, income, and general knowledge of tourists to the region about the health of the lakes in the watershed. Using an Impact Analysis for Planning (IMPLAN) modeling framework, we quantify the direct, indirect and induced effects of spending by tourists in the watershed. We find an estimated annual impact of $6.8 million in spending, including multiplier effects, and support for 68 full and part-time jobs in the watershed. Our hope is that this information will help to better inform decisions by policy makers, developers, land use planners, and stakeholder groups about the effects of ecosystem services and conservation land-use practices on tourism and trade.
Syntrophin binds to an alternatively spliced exon of dystrophin

Dystrophin, the protein product of the Duchenne muscular dystrophy locus, is a protein of the membrane cytoskeleton that associates with a complex of integral and membrane-associated proteins. Of these, the 58- kD intracellular membrane-associated protein, syntrophin, was recently shown to consist of a family of three related but distinct genes. We expressed the cDNA of human beta 1-syntrophin and the COOH terminus of human dystrophin in reticulocyte lysates using an in vitro transcription/translation system. Using antibodies to dystrophin we immunoprecipitated these two interacting proteins in a variety of salt and detergent conditions. We demonstrate that the 53 amino acids encoded on exon 74 of dystrophin, an alternatively spliced exon, are necessary and sufficient for interaction with translated beta 1- syntrophin in our assay. On the basis of its alternative splicing, dystrophin may thus be present in two functionally distinct populations. In this recombinant expression system, the dystrophin relatives, human dystrophin related protein (DRP or utrophin) and the 87K postsynaptic protein from Torpedo electric organ, also bind to translated beta 1-syntrophin. We have found a COOH-terminal 37-kD fragment of beta 1-syntrophin sufficient to interact with translated dystrophin and its homologues, suggesting that the dystrophin binding site on beta 1-syntrophin occurs on a region that is conserved among the three syntrophin homologues.
Optimization of continuous queries with shared expensive filters

We consider the problem of optimizing and executing multiple continuous queries, where each query is a conjunction of filters and each filter may occur in multiple queries. When filters are expensive, significant performance gains are achieved by sharing filter evaluations across queries. A shared execution strategy in our scenario can either be fixed, in which filters are evaluated in the same predetermined order for all input, or adaptive, in which the next filter to be evaluated is chosen at runtime based on the results of the filters evaluated so far. We show that as filter costs increase, the best adaptive strategy is superior to any fixed strategy, despite the overhead of adaptivity. We show that itis NP-hard to find the optimal adaptive strategy, even if we are willing to approximate within any factor smaller than m where m is the number of queries. We then present a greedy adaptive execution strategy and show that it approximates the best adaptive strategy to within a factor O(log2m log n) where n is the number of distinct filters. We also give a precomputation technique that can reduce the execution overhead of adaptive strategies.