On the convergence rate of distributed gradient methods for finite-sum optimization under communication delays

Motivated by applications in machine learning and statistics, we study distributed optimization problems over a network of processors, where the goal is to optimize a global objective composed of a sum of local functions. In these problems, due to the large scale of the data sets, the data and computation must be distributed over processors resulting in the need for distributed algorithms. In this paper, we consider a popular distributed gradient-based consensus algorithm, which only requires local computation and communication. An important problem in this area is to analyze the convergence rate of such algorithms in the presence of communication delays that are inevitable in distributed systems. We prove the convergence of the gradient-based consensus algorithm in the presence of uniform, but possibly arbitrarily large, communication delays between the processors. Moreover, we obtain an upper bound on the rate of convergence of the algorithm as a function of the network size, topology, and the inter-processor communication delays

American Sign Language Legal Interpretation Complications: A Comprehensive Analysis of Linguistic Barriers within the Criminal Justice System

The founding documents of the United States of America tend to be rather universal and impartial in their vernacular. Because all citizens of a nation are deserving of the same rights and privileges regardless of age, race, ethnicity, or disability status, accommodations must be provided to the Deaf to give them equal access to information throughout interrogations, trials, and police interactions. While it may seem obvious that interpreters should be provided during legal situations involving a Deaf individual, visual communication can make legal interactions quite complicated when police or attorneys can only reveal limited details. When Deaf culture involving expansion techniques and human rights regarding legal proceedings conflict with each other, a qualified and experienced sign language interpreter must be conscious of not only mediating cultures and languages, but also facilitating lawful interactions and not violating the rights of the Deaf person. These types of unique situations can further complicate already intricate circumstances

Removing a Log from the Nation’s Eye: A National Self-Analysis of the Domestic Terrorism Question

Terroristic values are easy to be ascribed to foreign enemies, but it is far more difficult to admit that domestic citizens could be extremist to the point of being labeled a terrorist. Terrorists are not born; they are made. The following research focuses on the commonalities of upbringing in known domestic terrorists within the United States of America that may reveal noticeable similarities in education, radicalization, and identity. The criminal justice system has yet to discover a perfect method of administering retribution to terrorists. While they have broken the law, their intentions and results are not the same as an ordinary criminal. While criminals tend to focus on personal gain, financial rewards, and secrecy, terrorists are far more interested in making a political statement in the open to begin immediate and drastic change even if they are killed for it. The media has the constitutional right to information, but if that information being distributed to the public could cause undue panic, perhaps it should not be released in such a biased manner. The name ‘terrorist’ is one that is placed on a person, government state, or idea. It is not specific to a nationality or ethnic group, which means that the United States is not in any way immune to this label. Domestic terrorism must be understood so that it can be prevented

Predicting success for new flavors with information known pre-launch: a flavored snack food case study

Success in the marketplace is the goal of every product launch. Knowing what data to collect before launching a product that could predict success would be valuable to companies. Thus, the objective of this study was to determine whether success of new line extensions for a multi-flavored snack product available internationally could be predicted from information available before launch. Staff from 15 countries completed a questionnaire for each product and included questions related to authenticity, familiarity, and capturing current trends, packaging and market place issues such as product competition and pricing. Using 63 flavors, a discriminant function correctly identified 75.8% successful products as successful and 66.7% unsuccessful products as unsuccessful. Stepwise comparison determined the variables necessary to correctly categorize the snack products: being a trendy flavor, new to the category, based off foods from restaurants or traditional foods. These variables assisted in predicting in market success for this product category

Metagenomic deep sequencing of aqueous fluid detects intraocular lymphomas.

IntroductionCurrently, the detection of pathogens or mutations associated with intraocular lymphomas heavily relies on prespecified, directed PCRs. With metagenomic deep sequencing (MDS), an unbiased high-throughput sequencing approach, all pathogens as well as all mutations present in the host's genome can be detected in the same small amount of ocular fluid.MethodsIn this cross-sectional case series, aqueous fluid samples from two patients were submitted to MDS to identify pathogens as well as common and rare cancer mutations.ResultsMDS of aqueous fluid from the first patient with vitreal lymphoma revealed the presence of both Epstein-Barr virus (HHV-4/EBV) and human herpes virus 8 (HHV-8) RNA. Aqueous fluid from the second patient with intraocular B-cell lymphoma demonstrated a less common mutation in the MYD88 gene associated with B-cell lymphoma.ConclusionMDS detects pathogens that, in some instances, may drive the development of intraocular lymphomas. Moreover, MDS is able to identify both common and rare mutations associated with lymphomas

Achieving sub-diffraction imaging through bound surface states in negative-refracting photonic crystals at the near-infrared

We report the observation of imaging beyond the diffraction limit due to bound surface states in negative refraction photonic crystals. We achieve an effective negative index figure-of-merit [-Re(n)/Im(n)] of at least 380, ~125x improvement over recent efforts in the near-infrared, with a 0.4 THz bandwidth. Supported by numerical and theoretical analyses, the observed near-field resolution is 0.47 lambda, clearly smaller than the diffraction limit of 0.61 lambda. Importantly, we show this sub-diffraction imaging is due to the resonant excitation of surface slab modes, allowing refocusing of non-propagating evanescent waves