Towards Distributed Two-Stage Stochastic Optimization

The weighted vertex cover problem is concerned with selecting a subset of the vertices that covers a target set of edges with the objective of minimizing the total cost of the selected vertices. We consider a variant of this classic combinatorial optimization problem where the target edge set is not fully known; rather, it is characterized by a probability distribution. Adhering to the model of two-stage stochastic optimization, the execution is divided into two stages so that in the first stage, the decision maker selects some of the vertices based on the probabilistic forecast of the target edge set. Then, in the second stage, the edges in the target set are revealed and in order to cover them, the decision maker can augment the vertex subset selected in the first stage with additional vertices. However, in the second stage, the vertex cost increases by some inflation factor, so the second stage selection becomes more expensive. The current paper studies the two-stage stochastic vertex cover problem in the realm of distributed graph algorithms, where the decision making process (in both stages) is distributed among the vertices of the graph. By combining the stochastic optimization toolbox with recent advances in distributed algorithms for weighted vertex cover, we develop an algorithm that runs in time O(log (?) / ?), sends O(m) messages in total, and guarantees to approximate the optimal solution within a (3 + ?)-ratio, where m is the number of edges in the graph, ? is its maximum degree, and 0 < ? < 1 is a performance parameter

On the Polytopal Generalization of Sperner’s Lemma

We introduce and prove Sperner’s lemma, the well known combinatorial analogue of the Brouwer fixed point theorem, and then attempt to gain a better understanding of the polytopal generalization of Sperner’s lemma conjectured in Atanassov (1996) and proven in De Loera et al. (2002). After explaining the polytopal generalization and providing examples, we present a new, simpler proof of a slightly weaker result that helps us better understand the result and why it is correct. Some ideas for how to generalize this proof to the complete result are discussed. In the last two chapters we provide a brief introduction to the basics of matroid theory before generalizing a matroid generalization of Sperner’s lemma proven in Lovász (1980) to polytopes. At the end we present some partial progress towards proving the polytopal generalization of Sperner’s lemma using this matroid generalization

Design of Self-Stabilizing Approximation Algorithms via a Primal-Dual Approach

Self-stabilization is an important concept in the realm of fault-tolerant distributed computing. In this paper, we propose a new approach that relies on the properties of linear programming duality to obtain self-stabilizing approximation algorithms for distributed graph optimization problems. The power of this new approach is demonstrated by the following results: - A self-stabilizing 2(1+?)-approximation algorithm for minimum weight vertex cover that converges in O(log? /(?log log ?)) synchronous rounds. - A self-stabilizing ?-approximation algorithm for maximum weight independent set that converges in O(?+log^* n) synchronous rounds. - A self-stabilizing ((2?+1)(1+?))-approximation algorithm for minimum weight dominating set in ?-arboricity graphs that converges in O((log?)/?) synchronous rounds. In all of the above, ? denotes the maximum degree. Our technique improves upon previous results in terms of time complexity while incurring only an additive O(log n) overhead to the message size. In addition, to the best of our knowledge, we provide the first self-stabilizing algorithms for the weighted versions of minimum vertex cover and maximum independent set

On the Runtime of Chemical Reaction Networks Beyond Idealized Conditions

This paper studies the (discrete) chemical reaction network (CRN) computational model that emerged in the last two decades as an abstraction for molecular programming. The correctness of CRN protocols is typically established under one of two possible schedulers that determine how the execution advances: (1) a stochastic scheduler that obeys the (continuous time) Markov process dictated by the standard model of stochastic chemical kinetics; or (2) an adversarial scheduler whose only commitment is to maintain a certain fairness condition. The latter scheduler is justified by the fact that the former one crucially assumes "idealized conditions" that more often than not, do not hold in real wet-lab experiments. However, when it comes to analyzing the runtime of CRN protocols, the existing literature focuses strictly on the stochastic scheduler, thus raising the research question that drives this work: Is there a meaningful way to quantify the runtime of CRNs without the idealized conditions assumption? The main conceptual contribution of the current paper is to answer this question in the affirmative, formulating a new runtime measure for CRN protocols that does not rely on idealized conditions. This runtime measure is based on an adapted (weaker) fairness condition as well as a novel scheme that enables partitioning the execution into short rounds and charging the runtime for each round individually (inspired by definitions for the runtime of asynchronous distributed algorithms). Following that, we turn to investigate various fundamental computational tasks and establish (often tight) bounds on the runtime of the corresponding CRN protocols operating under the adversarial scheduler. This includes an almost complete chart of the runtime complexity landscape of predicate decidability tasks

Breaking Bad: De-Anonymising Entity Types on the Bitcoin Blockchain Using Supervised Machine Learning

Bitcoin is a cryptocurrency whose transactions are recorded on a distributed, openly accessible ledger. On the Bitcoin Blockchain, an entity’s real-world identity is hidden behind a pseudonym, a so-called address. Therefore, Bitcoin is widely assumed to provide a high degree of anonymity, which is a driver for its frequent use for illicit activities. This paper presents a novel approach for reducing the anonymity of the Bitcoin Blockchain by using Supervised Machine Learning to predict the type of yet-unidentified entities. We utilised a sample of 434 entities with ≈ 200 million transactions), whose identity and type had been revealed, as training set data and built classifiers differentiating among 10 categories. Our main finding is that we can indeed predict the type of a yet-identified entity. Using the Gradient Boosting algorithm, we achieve an accuracy of 77% and F1-score of ≈ 0.75. We discuss our novel approach of Supervised Machine Learning for uncovering Blockchain anonymity and its potential applications to forensics and financial compliance and its societal implications, outline study limitations and propose future research directions

Ritalinic acid stimulates human sperm motility and maintains vitality in vitro

To evaluate the in vitro impact of ritalinic acid (RA), a major metabolite of methylphenidate (drug to treat attention-deficit hyperactivity disorder), on sperm motility, vitality and oxidative stress. Materials and Methods: Semen samples (n=13) were collected from healthy donors and a semen analysis was performed according to World Health Organization. Density gradient centrifugation was performed to isolate motile sperm. Samples were incubated with different concentrations (0, 1, 10, 100, and 1,000 ng/mL) of RA. The non-exposed group (0 ng/mL) was defined as the control group. Samples were analyzed for motility at different time points (0, 60, 150, 240, and 300 minutes) and for vitality and oxidation reduction potential (ORP) (at 0, 240, and 300 minutes). Sperm motility was assessed manually and motion kinetic parameters were recorded by computer aided semen analysis. Results: RA at any tested concentration significantly increased sperm motility compared to the control in a time-dependent manner with a maximum increase after 240 minutes. Motion kinetic parameters were not comparable

Ritalinic acid stimulates human sperm motility and maintains vitality in vitro

Purpose To evaluate the in vitro impact of ritalinic acid (RA), a major metabolite of methylphenidate (drug to treat attention-deficit hyperactivity disorder), on sperm motility, vitality and oxidative stress. Materials and Methods Semen samples (n=13) were collected from healthy donors and a semen analysis was performed according to World Health Organization. Density gradient centrifugation was performed to isolate motile sperm. Samples were incubated with different concentrations (0, 1, 10, 100, and 1,000 ng/mL) of RA. The non-exposed group (0 ng/mL) was defined as the control group. Samples were analyzed for motility at different time points (0, 60, 150, 240, and 300 minutes) and for vitality and oxidation reduction potential (ORP) (at 0, 240, and 300 minutes). Sperm motility was assessed manually and motion kinetic parameters were recorded by computer aided semen analysis. Results RA at any tested concentration significantly increased sperm motility compared to the control in a time-dependent manner with a maximum increase after 240 minutes. Motion kinetic parameters were not comparable. For sperm vitality, supplementation with RA significantly maintained survival at higher levels, while non-treated sperm gradually died. These higher levels of vitality were maintained with rising RA concentrations of up to 1,000 ng/mL. A non-significant trend of increased ORP was observed in all study groups. Conclusions RA increases sperm motility and maintains vitality at any concentration tested. Therefore, RA might be utilized to improve sperm quality in asthenozoospermic specimens. However, further investigation is ongoing to evaluate the effect of RA on other sperm parameters

Antioxidants and Polyphenols: Concentrations and Relation to Male Infertility and Treatment Success

Oxidative stress is induced by reactive oxygen substances (ROS) that are known to affect male fertility. The aims of this study were to prospectively investigate and characterize total antioxidant and specifically polyphenols concentrations and their relations to sperm quality and fertility treatment success. During their infertility treatment, sixty-seven males were prospectively recruited to this study. After separation of the sperm from the semen sample, the semen fluid samples antioxidants and polyphenols concentrations were determined. Antioxidant concentration was significantly associated with sperm concentration and total motile count. Antioxidants concentration in the group of male with sperm concentration ≥ 15 × 106 was significantly higher than in the group of male with antioxidants concentration < 15 × 106 (830.3 ± 350 μM and 268.3 ± 220 μM, resp., p<0.001). Polyphenols concentration did not differ between the groups of sperm concentration above and below 15 × 106 (178.7 ± 121 μM and 161.7 ± 61 μM, resp., p-NS). No difference was found between fertilization rates and antioxidants or polyphenols concentrations. This is the first study that reports on polyphenols concentration within semen fluid. More studies are needed in order to investigate polyphenols role in male fertility

Iron Deposition following Chronic Myocardial Infarction as a Substrate for Cardiac Electrical Anomalies: Initial Findings in a Canine Model

Purpose: Iron deposition has been shown to occur following myocardial infarction (MI). We investigated whether such focal iron deposition within chronic MI lead to electrical anomalies. Methods: Two groups of dogs (ex-vivo (n = 12) and in-vivo (n = 10)) were studied at 16 weeks post MI. Hearts of animals from ex-vivo group were explanted and sectioned into infarcted and non-infarcted segments. Impedance spectroscopy was used to derive electrical permittivity () and conductivity (). Mass spectrometry was used to classify and characterize tissue sections with (IRON+) and without (IRON-) iron. Animals from in-vivo group underwent cardiac magnetic resonance imaging (CMR) for estimation of scar volume (late-gadolinium enhancement, LGE) and iron deposition (T2*) relative to left-ventricular volume. 24-hour electrocardiogram recordings were obtained and used to examine Heart Rate (HR), QT interval (QT), QT corrected for HR (QTc) and QTc dispersion (QTcd). In a fraction of these animals (n = 5), ultra-high resolution electroanatomical mapping (EAM) was performed, co-registered with LGE and T2* CMR and were used to characterize the spatial locations of isolated late potentials (ILPs). Results: Compared to IRON- sections, IRON+ sections had higher, but no difference in. A linear relationship was found between iron content and (p1.5%)) with similar scar volumes (7.28%±1.02% (Iron (1.5%)), p = 0.51) but markedly different iron volumes (1.12%±0.64% (Iron (1.5%)), p = 0.02), QT and QTc were elevated and QTcd was decreased in the group with the higher iron volume during the day, night and 24-hour period (p<0.05). EAMs co-registered with CMR images showed a greater tendency for ILPs to emerge from scar regions with iron versus without iron. Conclusion: The electrical behavior of infarcted hearts with iron appears to be different from those without iron. Iron within infarcted zones may evolve as an arrhythmogenic substrate in the post MI period