Narrow Results

In this paper we discuss the possible use of chaotic signals for testing Analog-to-Digital Converters (ADCs), with particular reference to the well-known Code Density Test (CDT, also called Histogram Test). In detail, we discuss the implementation of a chaos-based discrete-time noise generator circuit, providing the theoretical analysis of its statistical characterization. The implementation of the chaos-based device is discussed with reference to a generic hardware architecture, taking into account the nonidealities introduced by the presence of noise and the variability of the circuit parameters. Based on this device, we propose a method for generating noisy samples that are distributed, over a target subinterval of the circuit output range, according to a probability density function (pdf) that can be made arbitrarily close to the ideal uniform pdf, in exchange for an acceptable reduction of the uniform-distributed samples generation rate. Theoretical results, also supported by two experiments, confirm the reliability of the proposed solution, showing that chaotic systems can represent an alternative with respect to traditional methods for the generation of signals to be used in the Code Density Test of ADCs.

The Appearance and Development of Commercial Laboratories in China.

Independent Medical Laboratories in China - A Sunrise Industry under the Circumstances of Healthcare Reformation.

Tracing the Rise of KingMed and its Future Route - A Correspondence with Hongbo Li.

Establishment of IML Quality Managerial System in China.

The Collaboration between IML and Community Medical Hospitals: Supplementary Service with Tests, Technologies and Beyond.

The Collaboration between IML and Major Medical Institutions - Supplement Service with Esoteric Testing.

Notice from Ministry of Health on Printing and Distributing "Basic Standards for Medical Laboratory (on Trial)" - Ministry of Health of the People's Republic of China.

Yak genome provides new insights into high altitude adaptation.

Gentris and Shanghai Institutes of Preventative Medicine expand collaboration.

Chinese researchers identify rice gene enhancing quality, productivity.

Quintiles opens new Center of Excellence in Dalian to support innovative drug development.

BGI demonstrated genomic data transfer at nearly 10 gigabits per second between US and China.

Quintiles deepens investment in China - New Quintiles China Headquarters and local lab testing solution announced.

Beike earns AABB Accreditation for cord blood and cord tissue banking.

Epigenomic differences between newborns and centenarians provide insight to the understanding of aging.

Metabolic Syndrome and Diabetes: Current Asian Perspectives.

A Crisis in the Development of Antibiotics.

The Marketing of Unapproved Stem Cell Products: An Industry-wide Challenge.

Draining the Goodwill of Science – The Direct-to-Consumer Genetic Testing Industry in East Asia.

Biodiesel – From Lab to Industry.

The Appearance and Development of Commercial Laboratories in China.

Cord Blood Banking – To Go Public or Stay Private.

Open Source – The Future of Drug Discovery.

VACCINES – Where are we headed?

Leveraging on External Expertise.

Asia-Pacific: Falling behind in the fight against HIV/AIDS

Emerging pathogens have no known therapies or vaccines and therefore can only be controlled via traditional methods of contact tracing, quarantine and isolation that require rapid and widespread testing. The most recent outbreak from an emerging pathogen is due to the highly transmissible SARS-CoV-2 virus causing COVID-19 disease, which is associated with no symptoms or mild symptoms in 80–90% of the infected individuals, while in the remainder of the patients it exhibits severe illness that can be lethal or persist for several weeks to months after infection. The first tests to diagnose infection by SARS-CoV-2 were developed soon after the genome of the virus became known, and use probes to measure viral RNA by reverse transcriptase-polymerase chain reaction (RT-PCR). These tests are highly sensitive and specific but can require several days to return results, which makes contact tracing and more generally efforts to control the spread of the infection very difficult. Furthermore, the sensitivity threshold is orders of magnitude below the viral load necessary for transmission; therefore, individuals recovering from the infection may still be have a positive test and be required to isolate unnecessarily while they are no longer infectious. Antigen tests were subsequently developed that use antibodies mostly targeted to the nucleocapsid protein of the virus. These tests are about 100 times less sensitive than RT-PCR, yes they detect viral loads that are about 1/10 that needed for transmission. Furthermore, such tests are potentially much cheaper than RT-PCR and yield results in 15 min or less. Antibody, also known as serological testing, is available and can provide useful information to understand the extent to which a population has been exposed to the virus; however, it is not a good indicator of current infection and not useful for infection control. Viral transmission models that incorporate testing and contact tracing show that infection control is much more readily achieved by increasing testing frequency than by using higher sensitivity testing. For example, compared to no testing at all, testing once every other week has a marginal benefit, while testing weekly can decrease the number of infections to 20–40%, and testing twice weekly or more can bring about a 95%$+$ reduction in infections. These lessons learned from dealing from the COVID-19 pandemic should guide future planning against potential emerging viruses.

Emerging pathogens have no known therapies or vaccines and therefore can only be controlled via traditional methods of contact tracing, quarantine and isolation that require rapid and widespread testing. The most recent outbreak from an emerging pathogen is due to the highly transmissible SARS-CoV-2 virus causing COVID-19 disease, which is associated with no symptoms or mild symptoms in 80–90% of the infected individuals, while in the remainder of the patients it exhibits severe illness that can be lethal or persist for several weeks to months after infection. The first tests to diagnose infection by SARS-CoV-2 were developed soon after the genome of the virus became known, and use probes to measure viral RNA by reverse transcriptase-polymerase chain reaction (RT-PCR). These tests are highly sensitive and specific but can require several days to return results, which makes contact tracing and more generally efforts to control the spread of the infection very difficult. Furthermore, the sensitivity threshold is orders of magnitude below the viral load necessary for transmission; therefore, individuals recovering from the infection may still be have a positive test and be required to isolate unnecessarily while they are no longer infectious. Antigen tests were subsequently developed that use antibodies mostly targeted to the nucleocapsid protein of the virus. These tests are about 100 times less sensitive than RT-PCR, yes they detect viral loads that are about 1/10 that needed for transmission. Furthermore, such tests are potentially much cheaper than RT-PCR and yield results in 15 min or less. Antibody, also known as serological testing, is available and can provide useful information to understand the extent to which a population has been exposed to the virus; however, it is not a good indicator of current infection and not useful for infection control. Viral transmission models that incorporate testing and contact tracing show that infection control is much more readily achieved by increasing testing frequency than by using higher sensitivity testing. For example, compared to no testing at all, testing once every other week has a marginal benefit, while testing weekly can decrease the number of infections to 20–40%, and testing twice weekly or more can bring about a 95%þ reduction in infections. These lessons learned from dealing from the COVID-19 pandemic should guide future planning against potential emerging viruses.