Criteria of efficiency for conformal prediction

We study optimal conformity measures for various criteria of efficiency of classification in an idealised setting. This leads to an important class of criteria of efficiency that we call probabilistic; it turns out that the most standard criteria of efficiency used in literature on conformal prediction are not probabilistic unless the problem of classification is binary. We consider both unconditional and label-conditional conformal prediction.Comment: 31 page

Underground trees inhabit varied environmental extremes across the Afrotropics

This is the final version. Available on open access from Oxford University Press via the DOI in this recordAbstract Background and Aims Geoxyles, a distinctive feature of Afrotropical savannas and grasslands, survive recurrent disturbances by resprouting subshrub branches from large below-ground woody structures. Underground trees are a type of geoxyle that independently evolved within woody genera of at least 40 plant families in Africa. The environmental limits and determinants of underground tree biogeography are poorly understood, with the relative influence of frost and fire debated in particular. We aim to quantify variability in the niche of underground tree species relative to their taller, woody tree/shrub congeners. Methods Using occurrence records of four Afrotropical genera, Parinari (Chrysobalanaceae), Ozoroa (Anacardiaceae), Syzygium (Myrtaceae) and Lannea (Anacardiaceae), and environmental data of nine climate and disturbance variables, the biogeography and niche of underground trees are compared with their open and closed ecosystem congeners. Key Results Along multiple environmental gradients and in a multidimensional environmental space, underground trees inhabit significantly distinct and extreme environments relative to open and closed ecosystem congeners. Niche overlap is low among underground trees and their congeners, and also among underground trees of the four genera. Of the study taxa, Parinari underground trees inhabit hotter, drier and more seasonal environments where herbivory pressure is greatest. Ozoroa underground trees occupy relatively more fire-prone environments, while Syzygium underground trees sustain the highest frost frequency and occur in relatively wetter conditions with seasonal waterlogging. Lannea underground trees are associated with the lowest temperatures, highest precipitation, and varying exposure to disturbance. Conclusions While underground trees exhibit repeated convergent evolution, varied environments shape the ecology and biogeography of this iconic plant functional group. The multiplicity of extreme environments related to fire, frost, herbivory and waterlogging that different underground tree taxa occupy, and the distinctiveness of these environments, should be recognized in the management of African grassy ecosystems

High Throughput WMN for the Communication in Disaster Scenario

The Wireless mesh network (WMN) is a popular network architecture used to support disaster recovery operations. However, few research works have addressed the capacity problem of such a network. This is due to the assumption that the communication network in disaster scenario is built to support services with a low rate requirement like delay tolerant messages. At the same time, the demand for higher data rates has increased in recent years due to the digitalisation of rescue operations and the use of new services (e.g. VoIP, drones and robots). Therefore, the capacity of the WMN is becoming a central issue in the design of future WMNs. This paper proposes a Layer 1 cluster-based network to solve the throughput bottleneck in the WMN. The proposed architecture is evaluated by several real world measurements. The obtained results are compared with the theory. The proposed solution shows a throughput improvement compared to a single-radio WMN and a multi-radio WMN using the CoMTaC channel allocation strategy

Possible Challenges and Appropriate Measures for a Resilient WMN-Based Disaster Network

A wireless mesh network (WMN)-based disaster network shall provide an emergency communication infrastructure in case of a catastrophe destroyed any existing communication infrastructure. Since the hardware of the disaster network is deployed in an environment affected by the outcome of a catastrophe, events such as aftershocks and/or outbreaking fires are likely to occur and may destroy the hardware of the disaster network. To maintain its provided functionality and thus its usability, the network requires to be resilient to these and other events which are affecting the network infrastructure. To achieve a resilient network, the normal state of the network as well as possible challenges affecting the normal state need to be defined in prior. This scientific work deals with the derivation and definition of the required normal state of the WMN-based disaster network, as well as the definition of possible challenges resulting from environmental-based events. Since each possible challenge is influencing the network infrastructure of the WMN-based disaster network, possible measures for preventing and/or reducing the impact of each challenge are defined. In addition, emergency corrections capable of resolving the influences of an occurring challenge are defined

Using Crowdsourcing for Fine-Grained Entity Type Completion in Knowledge Bases

Recent years have witnessed the proliferation of large-scale Knowledge Bases (KBs). However, many entities in KBs have incomplete type information, and some are totally untyped. Even worse, fine-grained types (e.g., BasketballPlayer) containing rich semantic meanings are more likely to be incomplete, as they are more difficult to be obtained. Existing machine-based algorithms use predicates (e.g., birthPlace) of entities to infer their missing types, and they have limitations that the predicates may be insufficient to infer fine-grained types. In this paper, we utilize crowdsourcing to solve the problem, and address the challenge of controlling crowdsourcing cost. To this end, we propose a hybrid machine-crowdsourcing approach for fine-grained entity type completion. It firstly determines the types of some “representative” entities via crowdsourcing and then infers the types for remaining entities based on the crowdsourcing results. To support this approach, we first propose an embedding-based influence for type inference which considers not only the distance between entity embeddings but also the distances between entity and type embeddings. Second, we propose a new difficulty model for entity selection which can better capture the uncertainty of the machine algorithm when identifying the entity types. We demonstrate the effectiveness of our approach through experiments on real crowdsourcing platforms. The results show that our method outperforms the state-of-the-art algorithms by improving the effectiveness of fine-grained type completion at affordable crowdsourcing cost.Peer reviewe

Energy-efficient placement of virtual network functions in a wireless mesh network

This is the author accepted manuscript. The final version is available from the Institute of Electrical and Electronics Engineers via the DOI in this record In the context of service provisioning, the integration of Network Functions Virtualization (NFV) enhances the flexibility, scalability, and programmability of telecommunication networks. However, this integration introduces challenges, particularly in optimizing the placement of Virtualized Network Functions (VNFs) within the NFV Infrastructure (NFVI). Existing studies have predominantly focused on well-connected, mains-powered ecosystems like datacentres and cloud networks. In contrast, the aim of this paper is to identify a solution that distributes and deploys a Wireless Mesh Network (WMN) as the backbone for a disaster management communication and service infrastructure. Given the mobility of mesh routers in such scenarios, these devices are often battery-powered. Consequently, the placement of VNFs directly impacts the energy consumption in the network and, subsequently, its lifetime. The proposed solution for the energy-efficient placement of VNF is formulated as a multi-objective optimization problem. This context introduces different approaches and proposes a heuristic algorithm to optimize the placement of VNFs. The evaluation results indicate that the proposed algorithm outperforms prior alternatives in various scenarios. Notably, it surpasses established methods like the Nondominated Sorting Genetic Algorithm II (NSGA-II), commonly used to solve similar problems. This research signifies a significant advancement in addressing the specific challenges associated with NFV integration in wireless mesh networks, particularly in disaster management contexts

Phenotypic and molecular assessment of seven patients with 6p25 deletion syndrome: Relevance to ocular dysgenesis and hearing impairment

BACKGROUND: Thirty-nine patients have been described with deletions involving chromosome 6p25. However, relatively few of these deletions have had molecular characterization. Common phenotypes of 6p25 deletion syndrome patients include hydrocephalus, hearing loss, and ocular, craniofacial, skeletal, cardiac, and renal malformations. Molecular characterization of deletions can identify genes that are responsible for these phenotypes. METHODS: We report the clinical phenotype of seven patients with terminal deletions of chromosome 6p25 and compare them to previously reported patients. Molecular characterization of the deletions was performed using polymorphic marker analysis to determine the extents of the deletions in these seven 6p25 deletion syndrome patients. RESULTS: Our results, and previous data, show that ocular dysgenesis and hearing impairment are the two most highly penetrant phenotypes of the 6p25 deletion syndrome. While deletion of the forkhead box C1 gene (FOXC1) probably underlies the ocular dysgenesis, no gene in this region is known to be involved in hearing impairment. CONCLUSIONS: Ocular dysgenesis and hearing impairment are the two most common phenotypes of 6p25 deletion syndrome. We conclude that a locus for dominant hearing loss is present at 6p25 and that this locus is restricted to a region distal to D6S1617. Molecular characterization of more 6p25 deletion patients will aid in refinement of this locus and the identification of a gene involved in dominant hearing loss

Vitamin D receptor ChIP-seq in primary CD4+ cells: relationship to serum 25-hydroxyvitamin D levels and autoimmune disease

PMCID: PMC3710212This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited