Miracle-dz/UniFAR-FTUs huggingface dataset:
The Best of Many Worlds: Dual Mirror Descent for Online Allocation Problems

A Novel Class of Robust and Fast Algorithms for Online Allocation Problems A central problem in operations research is allocating limited resources sequentially to maximize cumulative rewards. Applications abound and include network revenue management and internet advertising among many others. Existing data-driven algorithms are tailored for convex settings with either adversarial or stochastic inputs. Many modern applications of online allocations problems, however, are nonconvex. Furthermore, algorithms for adversarial inputs may be too conservative in practice, whereas algorithms for stochastic inputs can perform poorly when the model is misspecified. In the paper “The Best of Many Worlds: Dual Mirror Descent for Online Allocation Problems,” Balseiro, Lu, and Mirrokni present a novel class of algorithms for nonconvex online allocation problems that attain good performance simultaneously in stochastic and adversarial input models and also in various nonstationary settings. The resulting algorithms are simple, fast, and robust to noise and corruption in the observations, in contrast to existing methods from the literature.
Hop-constrained oblivious routing

We prove the existence of an oblivious routing scheme that is poly(logn)-competitive in terms of (congestion + dilation), thus resolving a well-known question in oblivious routing. Concretely, consider an undirected network and a set of packets each with its own source and destination. The objective is to choose a path for each packet, from its source to its destination, so as to minimize (congestion + dilation), defined as follows: The dilation is the maximum path hop-length, and the congestion is the maximum number of paths that include any single edge. The routing scheme obliviously and randomly selects a path for each packet independent of (the existence of) the other packets. Despite this obliviousness, the selected paths have (congestion + dilation) within a poly(logn) factor of the best possible value. More precisely, for any integer hop-bound h, this oblivious routing scheme selects paths of length at most h · poly(logn) and is poly(logn)-competitive in terms of congestion in comparison to the best possible congestion achievable via paths of length at most h hops. These paths can be sampled in polynomial time. This result can be viewed as an analogue of the celebrated oblivious routing results of R'acke [FOCS 2002, STOC 2008], which are O(logn)-competitive in terms of congestion, but are not competitive in terms of dilation.
Reconstruct Kaplan--Meier Estimator as M-estimator and Its Confidence Band

The Kaplan--Meier (KM) estimator, which provides a nonparametric estimate of a survival function for time-to-event data, has wide application in clinical studies, engineering, economics and other fields. The theoretical properties of the KM estimator including its consistency and asymptotic distribution have been extensively studied. We reconstruct the KM estimator as an M-estimator by maximizing a quadratic M-function based on concordance, which can be computed using the expectation--maximization (EM) algorithm. It is shown that the convergent point of the EM algorithm coincides with the traditional KM estimator, offering a new interpretation of the KM estimator as an M-estimator. Theoretical properties including the large-sample variance and limiting distribution of the KM estimator are established using M-estimation theory. Simulations and application on two real datasets demonstrate that the proposed M-estimator is exactly equivalent to the KM estimator, while the confidence interval and band can be derived as well.
MRAC-RL: A Framework for On-Line Policy Adaptation Under Parametric Model Uncertainty

Reinforcement learning (RL) algorithms have been successfully used to develop control policies for dynamical systems. For many such systems, these policies are trained in a simulated environment. Due to discrepancies between the simulated model and the true system dynamics, RL trained policies often fail to generalize and adapt appropriately when deployed in the real-world environment. Current research in bridging this sim-to-real gap has largely focused on improvements in simulation design and on the development of improved and specialized RL algorithms for robust control policy generation. In this paper we apply principles from adaptive control and system identification to develop the model-reference adaptive control & reinforcement learning (MRAC-RL) framework. We propose a set of novel MRAC algorithms applicable to a broad range of linear and nonlinear systems, and derive the associated control laws. The MRAC-RL framework utilizes an inner-loop adaptive controller that allows a simulation-trained outer-loop policy to adapt and operate effectively in a test environment, even when parametric model uncertainty exists. We demonstrate that the MRAC-RL approach improves upon state-of-the-art RL algorithms in developing control policies that can be applied to systems with modeling errors.
Higher order statistics of shear field: a machine learning approach

The unprecedented amount and the excellent quality of lensing data that the upcoming ground- and space-based surveys will produce represent a great opportunity to shed light on the questions that still remain unanswered concerning our universe and the validity of the standard $\Lambda$CDM cosmological model. Therefore, it is important to develop new techniques that can exploit the huge quantity of data that future observations will give us access to in the most effective way possible. For this reason, we decided to investigate the development of a new method to treat weak lensing higher order statistics, which are known to break degeneracy among cosmological parameters thanks to their capability of probing the non-Gaussian properties of the shear field. In particular, the proposed method directly applies to the observed quantity, i.e., the noisy galaxy ellipticity. We produced simulated lensing maps with different sets of cosmological parameters and used them to measure higher order moments, Minkowski functionals, Betti numbers, and other statistics related to graph theory. This allowed us to construct datasets with different size, precision, and smoothing. We then applied several machine learning algorithms to determine which method best predicts the actual cosmological parameters associated with each simulation. The best model resulted to be simple multidimensional linear regression. We used this model to compare the results coming from the different datasets and found out that we can measure with good accuracy the majority of the parameters that we considered. We also investigated the relation between each higher order estimator and the different cosmological parameters for several signal-to-noise thresholds and redshifts bins. Given the promising results, we consider this approach as a valuable resource, worth of further development.
Convergence Analysis of Homotopy-SGD for non-convex optimization

First-order stochastic methods for solving large-scale non-convex optimization problems are widely used in many big-data applications, e.g. training deep neural networks as well as other complex and potentially non-convex machine learning models. Their inexpensive iterations generally come together with slow global convergence rate (mostly sublinear), leading to the necessity of carrying out a very high number of iterations before the iterates reach a neighborhood of a minimizer. In this work, we present a first-order stochastic algorithm based on a combination of homotopy methods and SGD, called Homotopy-Stochastic Gradient Descent (H-SGD), which finds interesting connections with some proposed heuristics in the literature, e.g. optimization by Gaussian continuation, training by diffusion, mollifying networks. Under some mild assumptions on the problem structure, we conduct a theoretical analysis of the proposed algorithm. Our analysis shows that, with a specifically designed scheme for the homotopy parameter, H-SGD enjoys a global linear rate of convergence to a neighborhood of a minimum while maintaining fast and inexpensive iterations. Experimental evaluations confirm the theoretical results and show that H-SGD can outperform standard SGD.
Two-photon edge states in photonic topological insulators: topological protection versus degree of entanglement

Topological insulators combine insulating properties in the bulk with scattering-free transport along edges, supporting dissipationless unidirectional energy and information flow even in the presence of defects and disorder. The feasibility of engineering quantum Hamiltonians with photonic tools, combined with the availability of entangled photons, raises the intriguing possibility of employing topologically protected entangled states in optical quantum computing and information processing. However, while two-photon states built as a product of two topologically protected single-photon states inherit full protection from their single-photon "parents", high degree of non-separability may lead to rapid deterioration of the two-photon states after propagation through disorder. We identify physical mechanisms which contribute to the vulnerability of entangled states in topological photonic lattices and present clear guidelines for maximizing entanglement without sacrificing topological protection.
HERD LEVEL RISK FACTORS FOR ELEVATED TOTAL BACTERIAL COUNT IN BULK TANK MILK OF DAIRY HERDS

The aim of this study was to determine the risk factors associated withhigh total bacterial count of bulk tank milk. Bulk tank milk sampleswere collected from all Prince Edward Island dairy herds (n=235)from March 2005 to March 2007. Biweekly total bacterial count wasconducted using a Petrifilm culture system. Data for on-farm riskfactors were collected via a mail-out survey which consisted of 4 mainsections: 1) general farm demographics and management, 2) cowcleanliness and hygiene, 3) milking procedures and mastitis control,and 4) equipment maintenance and cleaning.The total bacterial count was positively associated with the amount ofsoiling on the teats prior to udder preparation, manual cleaning of thebulk tank, and the use of a certain type of detergent. Additionally, variousmethods of premilking udder preparation were important, with predipfollowed by drying being superior to other methods in reducingbacterial count. Season was a strong predictor, with the lowest counttending to occur in winter. The results of this study highlight theimportance of total bacterial count as indicator of on-farm managementpractices, which influence bacteriological quality of milk.
Radioactive and Stable Isotope Tracers in Biomedicine: Principles and Practice of Kinetic Analysis

Basic characteristics of isotopic tracers terminology for tracer studies gas-chromatography mass-spectrometry - instrumentation separation of compounds by chromatographic techniques calculation of substrate kinetics - multiple-pool models selection of tracer infusion and sampling sites assessment of body composition technical aspects of performing tracer infusions glucose metabolism lipid kinetics specific application - UREA amino acid metabolism protein synthesis and breakdown laboratory methods.
HEAT TRANSFER FROM SPHERICAL ICE IN FLOWING WATER

Several experimental studies involving forced convection from non-melting spherical bodies in a variety of fluids have been reported in the literature. At present, no study concerned with forced convection from ice spheres is known to the authors. Therefore, a series of experiments were conducted to investigate heat transfer from spherical ice in flowing water. Different ice sphere diameters for a variety of water flow velocities were tested and resulted in a range of Reynolds numbers between 210 and 27,000. When the experimental data are compared to Whitaker non-melting sphere correlation it is found that in the Reynolds number range between 1500 and 10,000, the melting data are well represented by his equation. For Reynolds numbers less than 1500 and greater than 10,000, the experimental data of the current study result in Nusselt numbers greater than Whitaker's prediction. This can be attributed to greater free stream turbulence that was experimentally observed for the low Reynolds number region and to the pronounced changes in geometrical shape of the ice sphere for the large Reynolds number region.
The novel role of epidermal growth factor (EGF) in the regulation of ion channels in the calu-3 submucosal cell line

Cystic fibrosis transmembrane conductance regulator (CFTR) is a cell membrane bound chloride ion channel regulated by cyclic AMP-dependent phosphorylation and levels of intracellular ATP. Mutations in this channel, such as the common deletion of phenylalanine at residue 508 (CFTRΔF508), leads to a decrease in chloride transport seen in the disease condition cystic fibrosis (CF). The mutant CFTR is not processed in the normal way and consequently not delivered to the cell membrane. Currently, the effect of growth factors such as epidermal growth factor (EGF) on ion transport in the airway has not been previously researched and is consequently unknown. Therefore the aim of this thesis is to determine (i) if EGF has an effect on ion transport in the submucosal cell line Calu-3, (ii) what the mechanisms are behind this, and (iii) if the effect of EGF was due to induction of gelatinase activity or a transactivation process. Functional investigations looking at ion transport were carried out by using short circuit current. This technique was complemented by traditional molecular biology techniques such as RT-PCR, Western blotting, flow cytometry and gelatin zymography. The level of EGF, a potent inducer of gelatinases, is known to be elevated in the lungs during tissue repair in CF. Calu-3 cells preincubated with EGF on the basolateral membrane increased initial current at one hour via a EGFR-PI3K-PKC-δ-KCNN4/KCNQ1 signalling pathway. Similarly, preincubation with EGF also decreased forskolin induced short circuit current compared to untreated monolayers at 1 to 3 hours, with a recovery at 24 hours. The decreases were found to be dependent on the activation of KCNQ1 since chromanol 293B, a specific inhibitor for KCNQ1, restored the short circuit current back to untreated levels. Stimulation of the β2 adrenergic receptors with salbutamol were not reduced using metalloproteinase inhibitor, GM-6001 and EGFR inhibitor, AG1478. This suggested that stimulation of β2 adrenergic receptors does not lead to transactivation of EGFR via activation of sheddases and the release of EGF ligand. β3 adrenergic receptors are present in Calu-3, but produce negligible currents when stimulated. It was concluded that EGF induced potassium channel activation led to a change in chloride driving force. This activation of potassium channels has previously been linked to wound repair in the airway during disease. The implications of this study suggest that manipulation of the EGF signalling pathway and / or potassium channel activity in the lungs may be beneficial in disease conditions such as CF for increasing chloride transport.
Development of a Nephelometry Camera and Humidity Controlled Cavity Ring-Down Transmissometer for the Measurement of Aerosol Optical Properties

This Dissertation is brought to you for free and open access. It has been accepted for inclusion in Dissertations and Theses by an authorized administrator of PDXScholar. For more information, please contact pdxscholar@pdx.edu. Recommended Citation Radney, James Gregory, "Development of a Nephelometry Camera and Humidity Controlled Cavity Ring-Down Transmissometer for the Measurement of Aerosol Optical Properties" (2012). Dissertations and Theses. Paper 907.
Anpassungsstörungen nach einem neuen diagnostischen Konzept bei Patienten einer psychosomatischen Poliklinik – Beschwerden, Veränderungsbereitschaft und Psychotherapiemotivation

New diagnostic concept of adjustment disorders in psychosomatic outpatients – Symptom severity, willingness to change, psychotherapy motivation Objectives: Adjustment disorders (AD) represent a frequently diagnosed type of disorder for which scientific interest has been limited because of insufficient diagnostic criteria. This study presents a concept comprising cognitive, behavioural, and emotional criteria (ADNM) which investigates differences in symptom severity, willingness to change, and motivation for psychotherapy in subjects with adjustment disorders. Method: 331 outpatients were examined with a number of tools (ADNM, SCL-90-R, FPTM-23, FEVER). The ADNM is evaluated on the basis of theoretical assumptions and divides the sample into subjects with elevated and normal scores. Results: The sample comprised patients with elevated scores (61 %) and normal scores (39 %). Subjects with AD scored higher on depression, anxiety, and impulsivity (p < 0.001) as well as exhibiting elevated scores on the SCL-90-R (p < 0.001), for contemplation/action (p = 0.003 | p < 0.001), and for psychotherapy motivation (p < 0.001). Conclusion: The ADNM identifies patients experiencing stress. Further longitudinal studies should examine whether patients more frequently enter psychotherapy or not.
A multi-scale strategy for handling broadband seismic data

SUMMARY Full waveform inversion is a promising imaging technology for high-resolution images of the subsurface, but suffers from intrinsic non-linearities that require adequate strategies for overcoming them. One crucial issue is related to the starting model from which one has to start when considering local optimization strategies. Depending on the complexity of the data often related to the frequency content of the waves, the initial model selection may range from a crude smooth model for low frequencies to already quite accurate models for high frequencies. We shall investigate relations between the data complexity either when recorded or after time transformation, the model discretisation as well as the optimization strategy in order to better quantify acquisition design and related data interpretation one should consider.
Spatial and temporal distribution of North Atlantic tropical cyclones

The aim of this work is to provide a classification of tropical cyclones (TC) according to their location, month of genesis and their lifecycles and to study the role of African Easterly Waves (AEWs) in North Atlantic cyclogenesis. Between 1980 and 2004, 269 tropical cyclones (TCs) were formed over the North Atlantic, 77% of which occurred during the August-October period and 95% of major hurricanes (TCs in which the maximum sustained wind was greater or equal to 50 m/s) were generated in the same period. The high activity of the August-October period was due to the favourable thermodynamic and dynamic conditions that simultaneously exist over the main development region (MDR). A classification of TCs according to their months of genesis and lifecycles showed that TCs generated before August and after October have no preferential latitude and longitude of genesis. TCs generated at the East of 60°W and over the southern part of the MDR have long lifecycles. Major hurricanes have long lifecycles and are generally initiated over the southern part of the MDR and East of 60°W. The spatial representation of the cyclogenesis area shows that cyclones are generated along two main axes; one is situated around 12.5°N (southern axis) and the second around 27.5°N (northern axis). 56% (44%) of TCs are generated over the southern axis (northern axis). 92% of TCs initiated along the southern axis originate from African Easterly Waves. While 64% of those generated over the northern axis are linked to mid-latitude baroclinic systems and upper level cold lows. This study contributes to a better understanding of North Atlantic cyclogenesis characteristics as well as the role of AEWs. Key words: North Atlantic tropical cyclones, major hurricanes, African easterly waves
Nonlinear and two-photon-induced fluorescence

The Theory of Two-Photon Induced Fluorescence Anisotropy P.R. Callis. Anisotropy Decays Induced by Two-Photon Excitation C.K. Johnson, C. Wan. Multiphoton Excitation of Biochemical Fluorophores J.R. Lakowicz, I. Gryczynski. Two-Photon Excitation and Anisotropy Decays in Membranes and Oriented Systems W. van der Meer, S. -Y.S. Chen. Two-Photon Induced Fluorescence of Proteins b. Kierdaszuk, et al. Fluorescence and Multiwave Mixing Induced by Photon Absorption of Excited Molecules V. Bogdanov. Ultrafast Stimulated Emission Spectroscopy G.J. Blanchard. Fluorescence Quenching by Stimulated Emission J.R. Lakowicz, I. Gryczynski. Increasing the Resolution of Far-Field Fluorescence Light Microscopy by Point Spread Functional Engineering S.W. Hell. Time-Resolved Stimulated-Emission and Transient-Absorption Microscopy and Spectroscopy P.T. C. So, et al. Index.
Weekly Open-Ended Exercises and Student Motivation in CS1

Improving student engagement and learning within introductory Computer Science (CS1) courses has been heavily studied within CS Education (CSE) research due to their fundamental role in a student’s early experiences with learning foundational CS concepts. One issue with many CS1 courses is that the practice of standardized grading leads to limited opportunities for students to find personal relevance within school projects, which could be demotivating for beginner students. This paper examines the impact of incorporating opportunities for creative thinking into a CS1 course through the use of weekly open-ended exercises. Data was collected from 284 students in a CS1 course, where roughly half of the students completed weekly exercises which included an open-ended aspect that allowed them to make their own decisions about their projects. The other half completed similar exercises but with a specifically defined, closed-ended checklist of requirements. Although no effect on academic performance was found, an analysis of survey data collected throughout the course revealed a significant connection between open-ended exercises and increased motivation, especially in terms of confidence and satisfaction. A deeper look at each particular exercise showed variances in how motivating an exercise was based on time in the semester and structure of the exercise, revealing important lessons about the design of effective open-ended CS1 exercises.
Primal/Dual Descent Methods for Dynamics

We examine the relationship between primal, or force‐based, and dual, or constraint‐based formulations of dynamics. Variational frameworks such as Projective Dynamics have proved popular for deformable simulation, however they have not been adopted for contact‐rich scenarios such as rigid body simulation. We propose a new preconditioned frictional contact solver that is compatible with existing primal optimization methods, and competitive with complementarity‐based approaches. Our relaxed primal model generates improved contact force distributions when compared to dual methods, and has the advantage of being differentiable, making it well‐suited for trajectory optimization. We derive both primal and dual methods from a common variational point of view, and present a comprehensive numerical analysis of both methods with respect to conditioning. We demonstrate our method on scenarios including rigid body contact, deformable simulation, and robotic manipulation.