EndNet: Sparse AutoEncoder Network for Endmember Extraction and Hyperspectral Unmixing

Data acquired from multichannel sensors are a highly valuable asset to interpret the environment for a variety of remote sensing applications. However, low spatial resolution is a critical limitation for previous sensors, and the constituent materials of a scene can be mixed in different fractions due to their spatial interactions. Spectral unmixing is a technique that allows us to obtain the material spectral signatures and their fractions from hyperspectral data. In this paper, we propose a novel endmember extraction and hyperspectral unmixing scheme, so-called EndNet, that is based on a two-staged autoencoder network. This well-known structure is completely enhanced and restructured by introducing additional layers and a projection metric [i.e., spectral angle distance (SAD) instead of inner product] to achieve an optimum solution. Moreover, we present a novel loss function that is composed of a Kullback-Leibler divergence term with SAD similarity and additional penalty terms to improve the sparsity of the estimates. These modifications enable us to set the common properties of endmembers, such as nonlinearity and sparsity for autoencoder networks. Finally, due to the stochastic-gradient-based approach, the method is scalable for large-scale data and it can be accelerated on graphical processing units. To demonstrate the superiority of our proposed method, we conduct extensive experiments on several well-known data sets. The results confirm that the proposed method considerably improves the performance compared to the state-of-the-art techniques in the literature

Communication-Efficient Zeroth-Order Distributed Online Optimization: Algorithm, Theory, and Applications

This paper focuses on a multi-agent zeroth-order online optimization problem in a federated learning setting for target tracking. The agents only sense their current distances to their targets and aim to maintain a minimum safe distance from each other to prevent collisions. The coordination among the agents and dissemination of collision-prevention information is managed by a central server using the federated learning paradigm. The proposed formulation leads to an instance of distributed online nonconvex optimization problem that is solved via a group of communication-constrained agents. To deal with the communication limitations of the agents, an error feedback-based compression scheme is utilized for agent-to-server communication. The proposed algorithm is analyzed theoretically for the general class of distributed online nonconvex optimization problems. We provide non-asymptotic convergence rates that show the dominant term is independent of the characteristics of the compression scheme. Our theoretical results feature a new approach that employs significantly more relaxed assumptions in comparison to standard literature. The performance of the proposed solution is further analyzed numerically in terms of tracking errors and collisions between agents in two relevant applications.Comment: 21 pages, 5 figures, and this paper has been accepted by IEEE Acces

Outcomes for revision total knee replacement after unicompartmental knee replacement

Objective: The aim of this retrospective, observational study was to describe the outcomes of total knee replacement (TKR) after failed Oxford phase 3 medial unicompartmental knee replacement (UKR). Methods: The study included 24 revision TKRs (20 females, 4 males; mean age: 61 years) performed following failed aseptic UKR. Outcomes were assessed using the Knee Society Score (KSS). Results: The most common causes for revision were mobile bearing dislocation and unexplained pain. Mean preoperative KSS was 50.3 (range: 37 to 66) and 82.2 (range: 58 to 97) after TKR. There were 17 excellent, 4 good, 2 fair and 1 poor results. Conclusion: The type of UKR performed (cemented versus uncemented) had no effect on TKR success. Revision for failed UKR with TKR appears to be a technically straightforward procedure with satisfactory early clinical results

Using synchronizing heuristics to construct homing sequences

Computing a shortest synchronizing sequence of an automaton is an NP-Hard problem. There are well-known heuristics to find short synchronizing sequences. Finding a shortest homing sequence is also an NP-Hard problem. Unlike existing heuristics to find synchronizing sequences, homing heuristics are not widely studied. In this paper, we discover a relation between synchronizing and homing sequences by creating an automaton called homing automaton. By applying synchronizing heuristics on this automaton we get short homing sequences. Furthermore, we adapt some of the synchronizing heuristics to construct homing sequences

Shuttle-based storage and retrieval systems designs from multi-objective perspectives: total investment cost, throughput rate and sustainability

This paper studies performance comparison of two shuttle-based storage and retrieval system (SBS/RS) configurations developed on flexible or non-flexible travel policies of shuttles in the system. In the non-flexible SBS/RS, a shuttle is dedicated to a tier so that it cannot travel out of its dedicated aisle and tier. A lifting mechanism is installed in each aisle to provide vertical travel for loads. In flexible SBS/RS, shuttles can travel between tiers by a separate lifting mechanism installed on the other edge point of each aisle. The advantage of that flexible design is that there might be decreased number of shuttles settling in the system compared to the non-flexible design. We simulate the two system configurations and conduct an experimental design for the comparison purpose. Based on the three-performance metrics: total investment cost, throughput rate and energy consumption per transaction, the results show that mainly the flexible system provides better results which might be considered as future system investment for SBS/RS

Prognostic factors for lymph node negative stage I and IIA non-small cell lung cancer: Multicenter experiences

Surgery is the only curative treatment for operable non-small lung cancer (NSCLC) and the importance of adjuvant chemotherapy for stage IB patients is unclear. Herein, we evaluated prognostic factors for survival and factors related with adjuvant treatment decisions for stage I and IIA NSCLC patients without lymph node metastasis. Materials and Methods: We retrospectively analyzed 302 patients who had undergone curative surgery for prognostic factors regarding survival and clinicopathological factors related to adjuvant chemotherapy. Results: Nearly 90% of the patients underwent lobectomy or pneumonectomy with mediastinal lymph node resection. For the others, wedge resection were performed. The patients were diagnosed as stage IA in 35%, IB in 49% and IIA in 17%. Histopathological type (p=0.02), tumor diameter (p=0.01) and stage (p<0.001) were found to be related to adjuvant chemotherapy decisions, while operation type, lypmhovascular invasion (LVI), grade and the presence of recurrence were important factors in predicting overall survival (OS), and operation type, tumor size greater than 4 cm, T stage, LVI, and visceral pleural invasion were related with disease free survival (DFS). Multivariate analysis showed operation type (p<0.001, hazard ratio (HR):1.91) and the presence of recurrence (p<0.001, HR:0.007) were independent prognostic factors for OS, as well visceral pleural invasion (p=0.01, HR:0.57) and LVI (p=0.004, HR:0.57) for DFS. Conclusions: Although adjuvant chemotherapy is standard for early stage lymph node positive NSCLC, it has less clear importance in stage I and IIA patients without lymph node metastasis

First-Line Molecular Genetic Evaluation of Autosomal Recessive Non-Syndromic Hearing Loss

Objective:The aim of this study is to investigate the efficiency of a first-line molecular genetic evaluation approach, in children with deafness.Methods:Patients who were found to have sensorineural hearing loss by age-appropriate audiological tests were selected for the molecular genetic evaluation. The molecular genetic evaluation was carried out with GJB2 gene sequence analysis and mtDNA m.1555A>G mutation Restriction Fragment Length Polymorphism (RFLP) analysis. Additionally, in a small group of patients, hearing loss Multiplex Ligation-dependent Probe Amplification (MLPA) analysis was done out to identify the possible role of copy number changes.Results:In this Turkish cohort, which included 104 index patients and 78 relatives, 33 (31.7%) had Pathogenic/Likely Pathogenic variants. One or more GJB2 sequence variants were identified in 46 (44.1%) of the 104 index patients. The homozygous c.35delG mutation by itself explained the etiology in 24% of our ARSNHL group. In one (5%) of the 20 patients of MLPA group, a hemizygous deletion in POU3F4 gene was detected.Conclusion:In our Turkish cohort, we applied a first-line molecular genetic evaluation approach using GJB2 gene sequence analysis and mtDNA m.1555A>G RFLP analysis. This approach revealed the genetic etiology of 44.1% of our index patients. Additionaly, the results of hearing loss MLPA analysis revealed the limited role of copy number changes in this patient group. Furthermore, with a detailed genotype-phenotype association workup, 2 rare cases of Deafness with Palmoplantar Hyperkeratosis and Keratitis-Ichthyosis-Deafness syndrome were reported