Safeguarding people living in vulnerable conditions in the COVID-19 era through universal health coverage and social protection

The COVID-19 pandemic is unprecedented. The pandemic not only induced a public health crisis, but has led to severe economic, social, and educational crises. Across economies and societies, the distributional consequences of the pandemic have been uneven. Among groups living in vulnerable conditions, the pandemic substantially magnified the inequality gaps, with possible negative implications for these individuals' long-term physical, socioeconomic, and mental wellbeing. This Viewpoint proposes priority, programmatic, and policy recommendations that governments, resource partners, and relevant stakeholders should consider in formulating medium-term to long-term strategies for preventing the spread of COVID-19, addressing the virus's impacts, and decreasing health inequalities. The world is at a never more crucial moment, requiring collaboration and cooperation from all sectors to mitigate the inequality gaps and improve people's health and wellbeing with universal health coverage and social protection, in addition to implementation of the health in all policies approach

Exchangeable Hoeffding-decomposition over finite sets: a characterization and counterexamples

We study Hoeffding decomposable exchangeable sequences with values in a finite set D = {d1, . . . , dK}. We provide a new combinatorial characterization of Hoeffding decomposability and use this result to show that, for every K≥ 3, there exists a class of neither Polya nor i.i.d. D-valued exchangeable sequences that are Hoeffding decomposable

Incoherent Discriminative Dictionary Learning for Speech Enhancement

Speech enhancement is one of the many challenging tasks in signal processing, especially in the case of nonstationary speech-like noise. In this paper a new incoherent discriminative dictionary learning algorithm is proposed to model both speech and noise, where the cost function accounts for both “source confusion” and “source distortion” errors, with a regularization term that penalizes the coherence between speech and noise sub-dictionaries. At the enhancement stage, we use sparse coding on the learnt dictionary to find an estimate for both clean speech and noise amplitude spectrum. In the final phase, the Wiener filter is used to refine the clean speech estimate. Experiments on the Noizeus dataset, using two objective speech enhancement measures: frequency-weighted segmental SNR and Perceptual Evaluation of Speech Quality (PESQ) demonstrate that the proposed algorithm outperforms other speech enhancement methods tested

Cloud computing applications and platforms: a survey

The implementation of cloud computing application takes the higher necessity, especially after suffering from modern problems, such as providing proper funds for social service and purchasing programs. For that, the cloud computing applications propose a promising solution to solve such issues. In this paper, we will discuss the implemention of cloud computing over Smart Grid system; a reliable, cost effective guaranteed and efficient system, it is expected to be Long Term Evolution (LTE): which allows larger pieces of spectrum, or bands to be used furthermore with more coverage and less latency and the third technology is Vehicular network: which is an important research area because of unique features and applications that offers. In this survey, we will present an overview of the smart grid, LTE and the vehicular network when they get integrated with cloud computing, in addition we will highlight the open issues and research direction which faces these technologies with cloud computing implementing in terms of Energy management, Information management for smart grid. In terms of applying cloud computing platforms for 4G Networks to achieve specific criteria and finally in terms of Architectural formation and Privacy and security for Vehicular cloud computing

Integrated health messaging for multiple neglected zoonoses : approaches, challenges and opportunities in Morocco

Integrating the control of multiple neglected zoonoses at the community-level holds great potential, but critical data is missing to inform the design and implementation of different interventions. In this paper we present an evaluation of an integrated health messaging intervention, using powerpoint presentations, for five bacterial (brucellosis and bovine tuberculosis) and dog-associated (rabies, cystic echinococcosis and leishmaniasis) zoonotic diseases in Sidi Kacem Province, northwest Morocco. Conducted by veterinary and epidemiology students between 2013 and 2014, this followed a process-based approach that encouraged sequential adaptation of images, key messages, and delivery strategies using auto-evaluation and end-user feedback. We describe the challenges and opportunities of this approach, reflecting on who was targeted, how education was conducted, and what tools and approaches were used. Our results showed that: (1) replacing words with local pictures and using "hands-on" activities improved receptivity; (2) information "overload" easily occurred when disease transmission pathways did not overlap; (3) access and receptivity at schools was greater than at the community-level; and (4) piggy-backing on high-priority diseases like rabies offered an important avenue to increase knowledge of other zoonoses. We conclude by discussing the merits of incorporating our validated education approach into the school curriculum in order to influence long-term behaviour change