An improved machine learning technique based on downsized KPCA for Alzheimer's disease classification

Alzheimer's disease (AD), a neurodegenerative disorder, is a very serious illness that cannot be cured, but the early diagnosis allows precautionary measures to be taken. The current used methods to detect Alzheimer's disease are based on tests of cognitive impairment, which does not provide an exact diagnosis before the patient passes a moderate stage of AD. In this article, a novel classifier of brain magnetic resonance images (MRI) based on the new downsized kernel principal component analysis (DKPCA) and multiclass support vector machine (SVM) is proposed. The suggested scheme classifies AD MRIs. First, a multiobjective optimization technique is used to determine the optimal parameter of the kernel function in order to ensure good classification results and to minimize the number of retained principle components simultaneously. The optimal parameter is used to build the optimized DKPCA model. Second, DKPCA is applied to normalized features. Downsized features are then fed to the classifier to output the prediction. To validate the effectiveness of the proposed method, DKPCA was tested using synthetic data to demonstrate its efficiency on dimensionality reduction, then the DKPCA based technique was tested on the OASIS MRI database and the results were satisfactory compared to conventional approaches.     

Inhibition of HSP90 with Pochoximes: SAR and Structure‐Based Insights

The pochoximes, based on the radicicol pharmacophore, are potent inhibitors of heat shock protein 90 (HSP90) that retain their activity in vivo. Herein we report an extended library that broadly explores the structure–activity relationship (SAR) of the pochoximes with four points of diversity. Several modifications were identified that afford improved cellular efficacy, new opportunities for conjugation, and further diversifications. Cocrystal structures of pochoximes A and B with HSP90 show that pochoximes bind to a different conformation of HSP90 than radicicol and provide a rationale for the enhanced affinity of the pochoximes relative to radicicol and the pochonins.     

Use of climate scenarios to aid in decision analysis for interannual water supply planning

This work addresses the issue of climate change in the context of water resource planning on the time scale of a few years. Planning on this time scale generally ignores the role of climate change. However, where the climate of a region has already shifted, the use of historical data for planning purposes may be misleading. In order to test this, a case study is conducted for a region, the Australian Capital Territory, where long term drought is raising concerns of a possible climate shift. The issue is cast in terms of a particular planning decision; the option to augment water supply in the next few years to hedge against the drought persisting. A set of climate scenarios are constructed for the region corresponding to the historical climate regime and to regimes where progressively greater levels of change are assumed to have already taken place (5%, 10%, 20% reductions in mean rainfall). Probabilities of the drought persisting are calculated for each of the scenarios. The results show substantial increases in the probability of the drought persisting for even moderate reductions in mean rainfall. The sensitivity of the decision to augment supply to the scenario results depends ultimately on the planners tolerable thresholds for the probability of the drought persisting. The use of different scenarios enables planners to explore the sensitivity of the decision in terms of their risk tolerance to ongoing drought and to their degree of belief in each of the scenarios tested.     

Attractor selection in a modulated laser and in the Lorenz circuit

By tuning a control parameter, a chaotic system can either display two or more attractors (generalized multistability) or exhibit an interior crisis, whereby a chaotic attractor suddenly expands to include the region of an unstable orbit (bursting regime).Recently, control of multistability and bursting have been experimentally proved in a modulated class B laser by means of a feedback method. In a bistable regime, the method relies on the knowledge of the frequency components of the two attractors. Near an interior crisis, the method requires retrieval of the unstable orbit colliding with the chaotic attractor.We also show that a suitable parameter modulation is able to control bistability in the Lorenz system. We observe that, for every given modulation frequency, the chaotic attractor is destroyed under a boundary crisis. The threshold control amplitude depends on the control frequency and the location of the operating point in the bistable regime. Beyond the boundary crisis, the system remains in the steady state even if the control is switched off, demonstrating control of bistability.     

Symbolic abstraction and deadlock-freeness verification of inter-enterprise processes

The design of complex inter-enterprise business processes (IEBP) is generally performed in a modular way. Each process is designed separately and then the whole IEBP is obtained by composition. Even if such a modular approach is intuitive and facilitates the design problem, it poses the problem that correct behavior of each business process of the IEBP taken alone does not guarantee a correct behavior of the composed IEBP (i.e. properties are not preserved by composition). Proving correctness of the (unknown) composed process is strongly related to the model checking problem of a system model. Among others, the symbolic observation graph based approach has proven to be very helpful for efficient model checking in general. Since it is heavily based on abstraction techniques and thus hides detailed information about system components that are not relevant for the correctness decision, it is promising to transfer this concept to the problem raised in this paper: How can the symbolic observation graph technique be adapted and employed for process composition? Answering this question is the aim of this paper.     

Supervised collaboration for syntactic annotation of Quranic Arabic

The Quranic Arabic Corpus (http://corpus.quran.com) is a collaboratively constructed linguistic resource initiated at the University of Leeds, with multiple layers of annotation including part-of-speech tagging, morphological segmentation (Dukes and Habash 2010) and syntactic analysis using dependency grammar (Dukes and Buckwalter 2010). The motivation behind this work is to produce a resource that enables further analysis of the Quran, the 1,400 year-old central religious text of Islam. This project contrasts with other Arabic treebanks by providing a deep linguistic model based on the historical traditional grammar known as i′rāb (?????). By adapting this well-known canon of Quranic grammar into a familiar tagset, it is possible to encourage online annotation by Arabic linguists and Quranic experts. This article presents a new approach to linguistic annotation of an Arabic corpus: online supervised collaboration using a multi-stage approach. The different stages include automatic rule-based tagging, initial manual verification, and online supervised collaborative proofreading. A popular website attracting thousands of visitors per day, the Quranic Arabic Corpus has approximately 100 unpaid volunteer annotators each suggesting corrections to existing linguistic tagging. To ensure a high-quality resource, a small number of expert annotators are promoted to a supervisory role, allowing them to review or veto suggestions made by other collaborators. The Quran also benefits from a large body of existing historical grammatical analysis, which may be leveraged during this review. In this paper we evaluate and report on the effectiveness of the chosen annotation methodology. We also discuss the unique challenges of annotating Quranic Arabic online and describe the custom linguistic software used to aid collaborative annotation.     

Probing entropic uncertainty relations under a two-atom system coupled with structured bosonic reservoirs

The uncertainty principle imposes constraints on an observer’s ability to make precision measurements for two incompatible observables; thus, uncertainty relations play a key role in quantum precision measurement in the field of quantum information science. Here, our aim is to examine non-Markovian effects on quantum-memory-assisted entropic uncertainty relations in a system consisting of two atoms coupled with structured bosonic reservoirs. Explicitly, we explore the dynamics of the uncertainty relations via entropic measures in non-Markovian regimes when two atomic qubits independently interact with their own infinite degree-of-freedom bosonic reservoir. We show that measurement uncertainty vibrates with periodically increasing amplitude with growing non-Markovianity of the observed system and ultimately saturates toward a fixed value at a long time limit. It is worth noting that there are several appealing conclusions raised by us: First, the uncertainty’s lower bound does not entirely depend on the quantum correlations within the two-qubit system, being affected by an interplay between the quantum discord and the minimal von Neumann conditional entropy \(\mathcal{S}_\mathrm{ce}\). Second, the dynamic characteristic of the measurement uncertainty is considerably distinctive with regard to Markovian and non-Markovian regimes, respectively. Third, the measurement uncertainty is closely correlated with the Bell non-locality \({\mathcal{B}}\). Moreover, we claim that the entropic uncertainty relation could be a promising tool with which to probe entanglement in current architecture.     

Minimizing the total completion time in a two-machine flowshop problem with time delays

This article proposes to solve the problem of minimizing the total completion time in a two-machine permutation flowshop environment in which time delays between the machines are considered. For this purpose, an enumeration algorithm based on the branch-and-bound framework is developed, which includes new lower and upper bounds as well as dominance rules. The computational study shows that problems with up to 40 jobs can be solved in a reasonable amount of time.