Miracle-dz/UniFAR-FTUs huggingface dataset:
A machine-checked proof of correctness of Pastry. (Une preuve certifiée par la machine de la correction du protocole Pastry)

A distributed hash table (DHT) is a peer-to-peer network that offers the function of a classic hash table, but where different key-value pairs are stored at different nodes on the network. Like a classic hash table, the main function provided by a DHT is key lookup, which retrieves the value stored at a given key. Examples of DHT protocols include Chord, Pastry, Kademlia and Tapestry. Such DHT protocols certain correctness and performance guarantees, but formal verification typically discovers border cases that violate those guarantees. In his PhD thesis, Tianxiang Lu reported correctness problems in published versions of Pastry and developed a model called {\LP}, for which he provided a partial proof of correct delivery of lookup messages assuming no node failure, mechanized in the {\TLA} Proof System. In analyzing Lu's proof, I discovered that it contained unproven assumptions, and found counterexamples to several of these assumptions. The contribution of this thesis is threefold. First, I present {\LPP}, a revised {\TLA} specification of {\LP}. Aside from needed bug fixes, {\LPP} contains new definitions that make the specification more modular and significantly improve proof automation. Second, I present a complete {\TLA} proof of correct delivery for {\LPP}. Third, I prove that the final step of the node join process of {\LP}/{\LPP} is not necessary to achieve consistency. In particular, I develop a new specification with a simpler node join process, which I denote by {\SLP}, and prove correct delivery of lookup messages for this new specification. The proof of correctness of {\SLP} is written by reusing the proof for {\LPP}, which represents a success story in proof reuse, especially for proofs of this size. Each of the two proofs amounts to over 32,000 proof steps; to my knowledge, they are currently the largest proofs written in the {\TLA} language, and---together with Lu's proof---the only examples of applying full theorem proving for the verification of DHT protocols
PHOSPHOTUNGSTIC ACID AS A SPECIFIC ELECTRON STAIN FOR COMPLEX CARBOHYDRATES

Statements in the literature assuming that phosphotungstic acid (PTA) is a stain for polysaccharide require correction. Most quioted is a publication of Pease (J. Ultrastruct. Res. 15: 555. 1966), the first paragraph of which has the following statement referring to tissues prepared for electron microscopy by displacement of water by glycol, embedment in hydroxypropyl methacrylate and eventual PTA staining: “Goblet cell mucus,
Preventing Opioid Prescription Theft and Ensuring SeCure Transfer of Personal Health Information when Patients Transition from the Hospital to a Nursing Home

of potentially inappropriate medications for elderly patients in Taiwan. Pharmacoepidemiol Drug Saf 2012;21:1269–1279. 7. Zhang YJ, Liu WW, Wang JB et al. Potentially inappropriate medication use among older adults in the USA in 2007. Age Ageing 2011;40:398– 401. 8. Pugh MJ, Fincke BG, Bierman AS et al. Potentially inappropriate prescribing in elderly veterans: Are we using the wrong drug, wrong dose, or wrong duration? J Am Geriatr Soc 2005;53:1282–1289. 9. Gallagher P, Barry P, O’Mahony D. Inappropriate prescribing in the elderly. J Clin Pharm Ther 2007;32:113–121.
ISOTOP

Multi-tenancy in the cloud is a double-edged sword. While it enables cost-effective resource sharing, it increases security risks for the hosted applications. Indeed, multiplexing virtual resources belonging to different tenants on the same physical substrate may lead to critical security concerns such as cross-tenants data leakage and denial of service. Particularly, virtual networks isolation failures are among the foremost security concerns in the cloud. To remedy these, automated tools are needed to verify security mechanisms compliance with relevant security policies and standards. However, auditing virtual networks isolation is challenging due to the dynamic and layered nature of the cloud. Particularly, inconsistencies in network isolation mechanisms across cloud-stack layers, namely, the infrastructure management and the implementation layers, may lead to virtual networks isolation breaches that are undetectable at a single layer. In this article, we propose an offline automated framework for auditing consistent isolation between virtual networks in OpenStack-managed cloud spanning over overlay and layer 2 by considering both cloud layers’ views. To capture the semantics of the audited data and its relation to consistent isolation requirement, we devise a multi-layered model for data related to each cloud-stack layer’s view. Furthermore, we integrate our auditing system into OpenStack, and present our experimental results on assessing several properties related to virtual network isolation and consistency. Our results show that our approach can be successfully used to detect virtual network isolation breaches for large OpenStack-based data centers in reasonable time.
Inference methods in discrete Bayesian networks

Bayesian networks are used to model complex uncertain systems with interrelated components. A reason for using Bayesian networks to model these systems is the correspondence to the abstract human notion of causal reasoning. Since many real-world relations are assumed to be deterministic, we also allow the models in this work to contain deterministic relations. This thesis concerns discrete Bayesian networks and corresponding inference methods. Exact inference in Bayesian networks is often too computationally intensive. On the other hand, most approximate inference methods have serious drawbacks in handling Bayesian networks with deterministic relations. In the case of importance sampling, we have a rejection problem: many of the samples may have high probability to get rejected due to the fact that the samples are incompatible with the evidence. In the case of Markov chain Monte Carlo methods, the deterministic relations can prevent the Markov chain from visiting certain regions in the state space. A sound Markov chain Monte Carlo algorithm is presented: prune sampling. This algorithm guarantees convergence under certain circumstances and it achieves better results than the commonly used methods, especially in the presence of determinism. Title: Inference methods in discrete Bayesian networks Author: Ron Weikamp, ron.weikamp@student.uva. nl, 6060919 Supervisor UvA: prof. dr. R. Núñez Queija Internship supervisor TNO: dr. F. Phillipson Second examiner: prof. dr. M.J. Sjerps Final date: 30-10-2015
Experiments with induction of association rules with respect to support and anti – support

Evaluating the interestingness of decision rules or trees is a challenging problem of knowledge discovery and data mining. In recent studies, the use of two interestingness measures at the same time was prevailing. Mining of Pareto– optimal borders according to support and confidence, or support and anti– support are examples of that approach. In this paper, we consider induction of “ if. , then. ” association rules with a fixed conclusion. We investigate ways to limit the set of association rules non – dominated with respect to support and confidence on one hand and support and anti – support on the other hand, to a subset of truly interesting rules. Analytically, and through experiments on real life dataset, we show that both of the considered sets can be easily reduced by using the valuable semantic of confirmation measures.
Effects of Involvement in Recreational Sports on Physical and Mental Health, Quality of Life of the Elderly

Abstract This study aims to discuss the effects of involvement in recreational sports on physical and mental health and satisfaction with life. The elderly aged 65 and above in Changhua City in Taiwan were selected by convenience sampling, and total 212 valid copies were acquired. Questionnaire survey and Structural Equation Modeling (SEM) were utilized for testing the model in this study. The analysis results show the favorable goodness of fit and the following findings. 1. Involvement in recreational sports would positively affect physical and mental health of the elderly. 2. Physical and mental health shows positive effects on their quality of life of the elderly. 3. Physical and mental health shows mediating effects on the relations between involvement in recreational sports and quality of life of the elderly. The results indicated that the main consideration for involvement in recreational sports was “centrality”. “Mental health” in physical and mental health is mostly emphasized by the elderly; “social interactions” were considered an important dimension of their quality of life. These findings suggested that in response to the advent of rapidly aging society, senior citizens are encouraged to engage in leisure activities, which could promote physical and mental health, improve quality of life, and achieve “successful aging” in their senior life.
Grasp Pose Detection in Dense Clutter

Recently, a number of grasp detection methods have been proposed that can be used to localize robotic grasp configurations directly from sensor data without estimating object pose. The underlying idea is to treat grasp perception analogously to object detection in computer vision. These methods take as input a noisy and partially occluded RGBD image or point cloud and produce as output pose estimates of viable grasps, without assuming a known CAD model of the object. Although these methods generalize grasp knowledge to new objects well, they have not yet been demonstrated to be reliable enough to be used widely. Many grasp detection methods achieve grasp success rates (grasp successes as a fraction of the total number of grasp attempts) between 75% and 95% for novel objects presented in isolation or in light clutter. Not only are these success rates too low for practical grasping applications, but the light clutter scenarios that are evaluated often do not reflect the realities of real world grasping. This paper proposes a number of innovations that together result in a significant improvement in grasp detection performance. The specific improvement in performance due to each of our contributions is quantitatively measured either in simulation or on robotic hardware. Ultimately, we report a series of robotic experiments that average a 93% end-to-end grasp success rate for novel objects presented in dense clutter.
Transgenerational hypocortisolism and behavioral disruption are induced by the antidepressant fluoxetine in male zebrafish Danio rerio

Significance Due to the high incidence of depression during childbearing, antidepressants such as fluoxetine (FLX) are highly prescribed during pregnancy, yet the risks to offspring are unknown. We report that a 6-day FLX exposure during early zebrafish development induces hypocortisolism for at least three generations. Gene expression analysis indicates that pathways controlling cortisol synthesis are altered in the descendants in the third generation. This FLX-induced low-cortisol phenotype is more prominent in males and is associated with significantly reduced exploratory behaviors for two generations. This is an important demonstration that, in an animal model, even a brief ancestral exposure to a common antidepressant modifies the stress response and critical coping behaviors for several generations. The global prevalence of depression is high during childbearing. Due to the associated risks to the mother and baby, the selective serotonin reuptake inhibitor fluoxetine (FLX) is often the first line of treatment. Given that FLX readily crosses the placenta, a fetus may be susceptible to the disruptive effects of FLX during this highly plastic stage of development. Here, we demonstrate that a 6-day FLX exposure to a fetus-relevant concentration at a critical developmental stage suppresses cortisol levels in the adult zebrafish (F0). This effect persists for three consecutive generations in the unexposed descendants (F1 to F3) without diminution and is more pronounced in males. We also show that the in vivo cortisol response of the interrenal (fish “adrenal”) to an i.p. injection of adrenocorticotropic hormone was also reduced in the males from the F0 and F3 FLX lineages. Transcriptomic profiling of the whole kidney containing the interrenal cells revealed that early FLX exposure significantly modified numerous pathways closely associated with cortisol synthesis in the male adults from the F0 and F3 generations. We also show that the low cortisol levels are linked to significantly reduced exploratory behaviors in adult males from the F0 to F2 FLX lineages. This may be a cause for concern given the high prescription rates of FLX to pregnant women and the potential long-term negative impacts on humans exposed to these therapeutic drugs.
Propranolol Promotes Glucose Dependence and Synergizes with Dichloroacetate for Anti-Cancer Activity in HNSCC

Tumor cell metabolism differs from that of normal cells, conferring tumors with metabolic advantages but affording opportunities for therapeutic intervention. Accordingly, metabolism-targeting therapies have shown promise. However, drugs targeting singular metabolic pathways display limited efficacy, in part due to the tumor’s ability to compensate by using other metabolic pathways to meet energy and growth demands. Thus, it is critical to identify novel combinations of metabolism-targeting drugs to improve therapeutic efficacy in the face of compensatory cellular response mechanisms. Our lab has previously identified that the anti-cancer activity of propranolol, a non-selective beta-blocker, is associated with inhibition of mitochondrial metabolism in head and neck squamous cell carcinoma (HNSCC). In response to propranolol, however, HNSCC exhibits heightened glycolytic activity, which may limit the effectiveness of propranolol as a single agent. Thus, we hypothesized that propranolol’s metabolic effects promote a state of enhanced glucose dependence, and that propranolol together with glycolytic inhibition would provide a highly effective therapeutic combination in HNSCC. Here, we show that glucose deprivation synergizes with propranolol for anti-cancer activity, and that the rational combination of propranolol and dichloroacetate (DCA), a clinically available glycolytic inhibitor, dramatically attenuates tumor cell metabolism and mTOR signaling, inhibits proliferation and colony formation, and induces apoptosis. This therapeutic combination displays efficacy in both human papillomavirus-positive (HPV(+)) and HPV(−) HNSCC cell lines, as well as a recurrent/metastatic model, while leaving normal tonsil epithelial cells relatively unaffected. Importantly, the combination significantly delays tumor growth in vivo with no evidence of toxicity. Additionally, the combination of propranolol and DCA enhances the effects of chemoradiation and sensitizes resistant cells to cisplatin and radiation. This novel therapeutic combination represents a promising treatment strategy which may overcome some of the limitations of targeting individual metabolic pathways in cancer.
A Survey On De-duplication Technique Over Distributed Cloud Environment With Improved Security.

De-duplication of data is the process of deleting redundant copies of stored data. It is single instance storage. It helps to achieve security requirements of data confidentiality in the cloud. As de-duplication has ability to improve storage utilization, it is most popular in academic as well as industry area. With the benefits and popularity of de-duplication it suffers from the problem such as, data reliability. Previously, existed systems have single server setting, which is not capable to preserve only single copy of the data in it due to privacy issue. Data privacy is a very challenging issue; it arises when more and more sensitive information is outsourced in cloud system. There is problem with encryption technique which is used by existing system, which required different cipher-texts for different users to share identical data. Today, there is need of achieving data confidentiality and reliability in distributed system by preserving data security requirements. Distributed de-duplication systems are efficient in which data blocks are spread across many cloud servers.
Privacy preserving neighbourhood-based collaborative filtering recommendation algorithms

Recommender systems, which recommend users the potentially preferred items by aggregating similar interest neighbours’ history data, show an increasing importance in various Internet applications. As a well-known method in recommender systems, neighbourhoodbased collaborative filtering has received considerable attention recently because of its easy implementation and high recommendation accuracy. However, the risks of revealing customers’ privacy during the process of filtering have attracted noticeable public concern. Specifically, the kNN attack discloses the target user’s sensitive information by creating k fake nearest neighbours by non-sensitive information. Among the current solutions against the kNN attack, probabilistic methods showed a powerful privacy preserving effect. However, the existing probabilistic methods neither guarantee enough prediction accuracy due to the global randomness, nor provide assured security enforcement against the kNN attack. To overcome the problem of recommendation accuracy loss, we propose a novel approach called Partitioned Probabilistic Neighbour Selection. In this thesis, we define the sum of k neighbours’ similarity as the accuracy metric α , the number of user partitions, across which we select the k neighbours, as the security metric β . We consider two versions of the Partitioned Probabilistic Neighbour Selection schemes. Firstly, to ensure a required prediction accuracy while maintaining high security against the kNN attack, we propose an accuracyassured Partitioned Probabilistic Neighbour Selection algorithm. We select neighbours from each exclusive partition of size k with a decreasing probability. Theoretical and experimental analysis show that to provide an accuracy-assured recommendation, our method yields a suitable trade-off between the recommendation accuracy and system security. Secondly, to ensure a required security guarantee while achieving the optimal prediction accuracy against the kNN attack, we propose a security-assured accuracy-maximised Partitioned Probabilistic Neighbour Selection algorithm. We select neighbours from each partition with exponential differential privacy to reduce the magnitude of noise. Theoretical and experimental analyses show that to achieve the same security guarantee against the kNN attack, our approach ensures an optimal prediction accuracy.
Partial Least Squares Method Based on Double Mutual Information and its Application

As we all know, PCA algorithm provides a linear transformation matrix between high and low dimensions, which is processed with dimensionality reduction by means of projection, so as to intercept the main information useful to people. However, the PCA algorithm does not take into account that its residuals may also contain process variables closely related to quality. Therefore, no matter what is done with the extracted ingredients, it is possible to lose important information. PLS considers the deficiencies of PCA and is widely used in quality control systems. However, since there will be non-gaussian interference in the system, the covariance method of the original PLS does not adapt to system interference. Therefore, we propose a PLS method based on double mutual information (DMIPLS) to solve the above problems. This method first use mutual information to calculate the weighted mutual information between process variables X and quality variables Y, select a set of process variables X, which are closely related to the quality variables, to ensure that the following PLS have valid process variables. Then, in the second to calculate the mutual information between residual matrix, to ensure that the residual error matrix of the process variables related to quality is not missing. The problem of non-gaussian interference is solved by using the feature of mutual information. Finally, the effectiveness of the method is verified by the simulation of TE system.
A New Nonisolated Single-Input Three-Output High Voltage Gain Converter With Low Voltage Stresses on Switches and Diodes

In this paper, an expandable single-input three-output high step-up dc–dc boost converter is proposed. The voltage conversion ratio of the output ports of the converter can be increased by inductor-diode-capacitor and diode-capacitor cells. The proposed converter can be applied in renewable energy conversion systems, such as in photovoltaic and fuel cells. Also, due to the three output ports of the converter, it can be utilized in portable devices which require high voltage conversions. The main advantage of the proposed converter is supplying loads with different voltages and current ranges due to the expandable structure of the converter. Besides, the proposed converter has the merit of achieving high voltage gains at high frequencies without preselecting wide duty cycles. Furthermore, the proposed converter is able to achieve higher voltage ranges without having any transformer or coupled inductors in its structure; consequently, the related drawbacks are avoided. The switching pattern of the converter is simple and both switches are on and off simultaneously. In this study, a single switching period of the proposed converter, the voltage conversion ratios of the output ports and the expanded form of the structure are analyzed theoretically. Finally, to verify the theoretical results, the experimental results for 40-V input/200-V, 100-V and 360-V outputs with total 600-W output power are extracted and compared with each other.
Structures in Science: Heuristic Patterns Based on Cognitive Structures An Advanced Textbook in Neo-Classical Philosophy of Science

Foreword. Part I: Units of Scientific Knowledge and Knowledge Acquisition. 1. Research programs and research strategies. 2. Observational laws and proper theories. Part II: Patterns of Explanation and Description. 3. Explanation and reduction of laws. 4. Explanation and description by specification. Part III: Structures in Interlevel and Interfield Research. 5. Reduction and correlation of concepts. 6. Levels, styles, and mind-body research. Part IV: Confirmation and Empirical Progress. 7. Testing and further separate evaluation of theories. 8. Empirical progress and pseudoscience. Part V: Truth, Product, and Concept Approximation. 9. Progress in nomological, explicative and design research. 10. Design research programs. Part VI: Capita Selecta. 11. Computational philosophy of science. 12. The structuralist approach to theories. 13. 'Default-norms' in research ethics. Suggestions for further reading. Exercises. Notes. References. Index of Names. Index of Subjects.