On Multiple Hypothesis Testing with Rejection Option

We study the problem of multiple hypothesis testing (HT) in view of a rejection option. That model of HT has many different applications. Errors in testing of M hypotheses regarding the source distribution with an option of rejecting all those hypotheses are considered. The source is discrete and arbitrarily varying (AVS). The tradeoffs among error probability exponents/reliabilities associated with false acceptance of rejection decision and false rejection of true distribution are investigated and the optimal decision strategies are outlined. The main result is specialized for discrete memoryless sources (DMS) and studied further. An interesting insight that the analysis implies is the phenomenon (comprehensible in terms of supervised/unsupervised learning) that in optimal discrimination within M hypothetical distributions one permits always lower error than in deciding to decline the set of hypotheses. Geometric interpretations of the optimal decision schemes are given for the current and known bounds in multi-HT for AVS's.Comment: 5 pages, 3 figures, submitted to IEEE Information Theory Workshop 201

Distributed demand side management with battery storage for smart home energy scheduling

Abstract: The role of Demand Side Management (DSM) with Distributed Energy Storage (DES) has been gaining attention in recent studies due to the impact of the latter on energy management in the smart grid. In this work, an Energy Scheduling and Distributed Storage (ESDS) algorithm is proposed to be installed into the smart meters of Time-of-Use (TOU) pricing consumers possessing in-home energy storage devices. Source of energy supply to the smart home appliances was optimized between the utility grid and the DES device depending on energy tariff and consumer demand satisfaction information. This is to minimize consumer energy expenditure and maximize demand satisfaction simultaneously. The ESDS algorithm was found to offer consumer-friendly and utility-friendly enhancements to the DSM program such as energy, financial, and investment savings, reduced/eliminated consumer dissatisfaction even at peak periods, Peak-to-Average-Ratio (PAR) demand reduction, grid energy sustainability, socio-economic benefits, and other associated benefits such as environmental-friendliness

Distributed Tracing for Troubleshooting of Native Cloud Applications via Rule-Induction Systems

Diagnosing IT issues is a challenging problem for large-scale distributed cloud environments due to complex and non-deterministic interrelations between the system components. Modern monitoring tools rely on AI-empowered data analytics for detection, root cause analysis, and rapid resolution of performance degradation. However, the successful adoption of AI solutions is anchored on trust. System administrators will not unthinkingly follow the recommendations without sufficient interpretability of solutions. Explainable AI is gaining popularity by enabling improved confidence and trust in intelligent solutions. For many industrial applications, explainable models with moderate accuracy are preferable to highly precise black-box ones. This paper shows the benefits of rule-induction classification methods, particularly RIPPER, for the root cause analysis of performance degradations. RIPPER reveals the causes of problems in a set of rules system administrators can use in remediation processes. Native cloud applications are based on the microservices architecture to consume the benefits of distributed computing. Monitoring such applications can be accomplished via distributed tracing, which inspects the passage of requests through different microservices. We discuss the application of rule-learning approaches to trace traffic passing through a malfunctioning microservice for the explanations of the problem. Experiments performed on datasets from cloud environments proved the applicability of such approaches and unveiled the benefits

Challenges and Experiences in Designing Interpretable KPI-diagnostics for Cloud Applications

Automated root cause analysis of performance problems in modern cloud computing infrastructures is of a high technology value in the self-driving context. Those systems are evolved into large scale and complex solutions which are core for running most of today’s business applications. Hence, cloud management providers realize their mission through a “total” monitoring of data center flows thus enabling a full visibility into the cloud. Appropriate machine learning methods and software products rely on such observation data for real-time identification and remediation of potential sources of performance degradations in cloud operations to minimize their impacts. We describe the existing technology challenges and our experiences while working on designing problem root cause analysis mechanisms which are automatic, application agnostic, and, at the same time, interpretable for human operators to gain their trust. The paper focuses on diagnosis of cloud ecosystems through their Key Performance Indicators (KPI). Those indicators are utilized to build automatically labeled data sets and train explainable AI models for identifying conditions and processes “responsible” for misbehaviors. Our experiments on a large time series data set from a cloud application demonstrate that those approaches are effective in obtaining models that explain unacceptable KPI behaviors and localize sources of issues

7-Chloro-11a-phenyl-2,3,5,10,11,11a-hexa­hydro-1H-pyrrolo[2,1-c][1,4]benzodiazepine-5,11-dione

The title compound, C18H15ClN2O2, is a potential human immunodeficiency virus type-1 (HIV-1) non-nucleoside reverse transcriptase inhibitor. The pyrrolidine ring adopts an envelope and the diazepine ring a boat conformation. In the crystal structure, two isomers (R and S) form centrosymmetric dimers via N—H⋯O hydrogen bonds

Frequent deletions of JARID2 in leukemic transformation of chronic myeloid malignancies

Chronic myeloproliferative neoplasms (MPN) and myelodysplastic syndromes (MDS) have an inherent tendency to progress to acute myeloid leukemia (AML). Using high-resolution SNP microarrays, we studied a total of 517 MPN and MDS patients in different disease stages, including 77 AML cases with previous history of MPN (N = 46) or MDS (N = 31). Frequent chromosomal deletions of variable sizes were detected, allowing the mapping of putative tumor suppressor genes involved in the leukemic transformation process. We detected frequent deletions on the short arm of chromosome 6 (del6p). The common deleted region on 6p mapped to a 1.1-Mb region and contained only the JARID2 genemember of the polycomb repressive complex 2 (PRC2). When we compared the frequency of del6p between chronic and leukemic phase, we observed a strong association of del6p with leukemic transformation (P = 0.0033). Subsequently, analysis of deletion profiles of other PRC2 members revealed frequent losses of genes such as EZH2, AEBP2, and SUZ12; however, the deletions targeting these genes were large. We also identified two patients with homozygous losses of JARID2 and AEBP2. We observed frequent codeletion of AEBP2 and ETV6, and similarly, SUZ12 and NF1. Using next generation exome sequencing of 40 patients, we identified only one somatic mutation in the PRC2 complex member SUZ12. As the frequency of point mutations in PRC2 members was found to be low, deletions were the main type of lesions targeting PRC2 complex members. Our study suggests an essential role of the PRC2 complex in the leukemic transformation of chronic myeloid disorders. Am. J. Hematol. 2012

Complex Patterns of Chromosome 11 Aberrations in Myeloid Malignancies Target CBL, MLL, DDB1 and LMO2

Exome sequencing of primary tumors identifies complex somatic mutation patterns. Assignment of relevance of individual somatic mutations is difficult and poses the next challenge for interpretation of next generation sequencing data. Here we present an approach how exome sequencing in combination with SNP microarray data may identify targets of chromosomal aberrations in myeloid malignancies. The rationale of this approach is that hotspots of chromosomal aberrations might also harbor point mutations in the target genes of deletions, gains or uniparental disomies (UPDs). Chromosome 11 is a frequent target of lesions in myeloid malignancies. Therefore, we studied chromosome 11 in a total of 813 samples from 773 individual patients with different myeloid malignancies by SNP microarrays and complemented the data with exome sequencing in selected cases exhibiting chromosome 11 defects. We found gains, losses and UPDs of chromosome 11 in 52 of the 813 samples (6.4%). Chromosome 11q UPDs frequently associated with mutations of CBL. In one patient the 11qUPD amplified somatic mutations in both CBL and the DNA repair gene DDB1. A duplication within MLL exon 3 was detected in another patient with 11qUPD. We identified several common deleted regions (CDR) on chromosome 11. One of the CDRs associated with de novo acute myeloid leukemia (P=0.013). One patient with a deletion at the LMO2 locus harbored an additional point mutation on the other allele indicating that LMO2 might be a tumor suppressor frequently targeted by 11p deletions. Our chromosome-centered analysis indicates that chromosome 11 contains a number of tumor suppressor genes and that the role of this chromosome in myeloid malignancies is more complex than previously recognized

Identification of germline genetic factors contributing to susceptibility and clinical phenotype in myeloproliferative neoplasms

Myeloproliferative neoplasms (MPN) are a group of hematological malignancies primarily driven by somatic mutations and chromosomal aberrations. In the recent years significant amount of evidence has been accumulating on the importance of hereditary factors in MPN. Familial clustering, cases of biclonal MPN and phenotypic diversity in the presence of the same mutation have provided a solid basis for research in MPN germline genetics. Despite comprehensive clinical characterization of familial MPN, the major germline mutations responsible for MPN susceptibility have not been found. The same is true for the association of MPN with common SNPs in the population. We performed a detailed study of germline genetic factors influencing MPN from multiple aspects. In order to study familial MPN, we first developed a nonparametric linkage analysis algorithm for high-throughput genotyping data. We validated the method on three families with known germline causative mutations and then applied it to a family with five affected MPN cases. Combining linkage analysis with exome sequencing and downstream validation of the identified hits, we found a mutation in RBBP6 gene as the candidate susceptibility gene. Additional screening in other families with MPN yielded another two families with germline RBBP6 mutations. RBBP6 is interacting with p53 and presumably the effect of mutation is mediated through p53 pathway. Moreover, we have shown an important role of p53 pathway in MPN, particularly in leukemic transformation, coming from the somatic genetics side. We have also contributed to the understanding of the role of common germline predisposition to MPN. We have identified the strongest common predisposition for JAK2-positive MPN: the 'GGCC' haplotype spanning JAK2 locus. Additionally, we have shown that although JAK2 'GGCC' haplotype confers the same risk in familial MPN, it cannot explain familial clustering of MPN. Finally, we have identified a phenomenon of the interaction of somatic genetic aberrations and germline mutations. We have shown that a deleterious heterozygous mutation can influence disease phenotype when combined with acquired chromosomal aberration. Overall, it seems that the inherited factors have quite an important role in MPN. The interconnection and overlap of somatic and germline genetics is particularly intriguing and will provide a new dimension in MPN research.Myeloproliferative Neoplasien (MPN) stellen eine Gruppe hämatologischer Erkrankungen dar, deren Ursache in erster Linie erworbene (somatische) Mutationen und chromosomale Veränderungen des Erbgutes sind. Forschungen der letzten Jahre haben zudem die Wichtigkeit von vererbten Faktoren in MPN gezeigt. Familiäre Häufungen, Fälle von biklonaler MPN sowie phänotypische Unterschiede bei Trägern der gleichen genetischen Veränderung rechtfertigen die Erforschung vererbter genetischer Veränderungen in MPN. Trotz umfangreicher Studien familiärer MPN wurden bisher keine Mutationen gefunden, die für MPN prädisponieren. Ebenso wurde bisher keine Assoziation von Einzelnukleotid-Polymorphismen (SNPs) mit MPN beschrieben. Im Zuge dieser Doktorarbeit untersuchten wir vererbte genetische Faktoren, die einen Einfluss auf MPN haben, aus unterschiedlichen Perspektiven. Zu diesem Zweck, haben wir zunächst einen Algorithmus zur nichtparametrischen Kopplungsanalyse basierend auf Hochdurchsatz-Genotypisierungsdaten entwickelt. Wir validierten diese Methode an drei Familien mit verschiedenen Erkrankungen bei denen eine ursächliche, vererbte Mutation bekannt war. Danach untersuchten wir eine Familie mit fünf MPN Fällen, in welcher eine entsprechende Mutation noch nicht gefunden wurde. Die Kopplungsanalyse kombinierten wir mit einer Exom Sequenzierung. Nach Validierung der gefundenen genetischen Varianten konnten wir eine Mutation im RBBP6 Gen nachweisen. In einer darauffolgenden Analyse von anderen Familien, in denen MPN gehäuft auftrat, identifizierten wir zwei weitere Familien mit vererbten Mutationen in RBBP6. Nachdem RBBP6 mit p53 interagiert, ist der Effekt der gefundenen Mutationen möglicherweise mit dem p53 Signaltransduktionsweg assoziiert. Wir konnten bereits vor dieser Studie durch eine Analyse somatischer Veränderungen zeigen, dass der p53 Signaltransduktionsweg eine wichtige Rolle in MPN spielt, im Besonderen bei der Transformation der Krankheit in eine akute myeloische Leukämie. In einem zweiten Projekt konnten wir zeigen, dass ein häufig in der Bevölkerung vorkommender Haplotyp des JAK2 Gens, der sogenannte 'GGCC' Haplotyp, die stärkste Prädisposition für JAK2-positive MPN darstellt. Das Risiko für Träger dieses Haplotyps eine MPN zu entwickeln ist zwar gleich für familiär gehäuft auftretende und sporadische MPN, dennoch kann der Haplotyp die Häufung von MPN in Familien nicht erklären. Zuletzt untersuchten wir das Zusammenwirken von vererbten und erworbenen genetischen Veränderungen in MPN. Eine heterozygote Mutation kann in Kombination mit einer erworbenen chromosomalen Veränderung die Charakteristika der Krankheit beeinflussen, wie wir an einem Beispiel zeigen konnten. Zusammenfassend lässt sich sagen, dass erbliche genetische Faktoren eine wichtige Rolle in MPN spielen. Das Zusammenwirken von vererbten und erworbenen genetischen Faktoren ist besonders interessant und erweitert die MPN Forschung um eine neue Dimension.submitted by Ashot HarutyunyanAbweichender Titel laut Übersetzung der Verfasserin/des VerfassersZsfassung in dt. SpracheWien, Med. Univ., Diss., 2013OeBB(VLID)171646

Dispute resolution mechanisms in “business to business relations” in Armenia

The problem related to ADR functioning in Armenia has a crucial importance for further economic development. The institutional development in Armenia has formed a peculiar reality of “institutional consistency” in this field, an essential element of which is a fragile dividing line between formal and informal institutions. Business reality shows that in Armenia the usage of ADR in “business to business” relations is widespread. The matter is that mostly it takes a form of informal relations, and actually formal ADR institutions have become “unclaimed”. This fact creates serious obstacles for the Government which seeks to establish effectively functioning formal ADR institutions. Unless the reasons as to why informal ADR mechanism is in high demand are identified, it is obvious that it will not be possible to elaborate a feasibly justified policy in this field. The aim of the study is to have a general overview on the dispute resolution mechanisms in Armenia and to study opportunities for their efficient implementation. Particularly the study is focusing on the following questions 1. What is the theoretical background of contract enforcement 2. What are the theoretical costs of contract enforcement to businesses? 3. How disputes in B2B are being solved in Armenia? 4. What are the real costs the businesses face during dispute resolution 5. How the costs of dispute resolution stipulate selection between different resolution mechanism