Evolution of Winning Solutions in the 2021 Low-Power Computer Vision Challenge

Mobile and embedded devices are becoming ubiquitous. Applications such as rescue with autonomous robots and event analysis on traffic cameras rely on devices with limited power supply and computational sources. Thus, the demand for efficient computer vision algorithms increases. Since 2015, we have organized the IEEE Low-Power Computer Vision Challenge to advance the state of the art in low-power computer vision. We describe the competition organizing details including the challenge design, the reference solution, the dataset, the referee system, and the evolution of the solutions from two winning teams. We examine the winning teams’ development patterns and design decisions, focusing on their techniques to balance power consumption and accuracy. We conclude that a successful competition needs a well-designed reference solution and automated referee system, and a solution with modularized components is more likely to win. We hope this paper provides guidelines for future organizers and contestants of computer vision competitions

An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry

Deep Neural Networks (DNNs) are being adopted as components in software systems. Creating and specializing DNNs from scratch has grown increasingly difficult as state-of-the-art architectures grow more complex. Following the path of traditional software engineering, machine learning engineers have begun to reuse large-scale pre-trained models (PTMs) and fine-tune these models for downstream tasks. Prior works have studied reuse practices for traditional software packages to guide software engineers towards better package maintenance and dependency management. We lack a similar foundation of knowledge to guide behaviors in pre-trained model ecosystems. In this work, we present the first empirical investigation of PTM reuse. We interviewed 12 practitioners from the most popular PTM ecosystem, Hugging Face, to learn the practices and challenges of PTM reuse. From this data, we model the decision-making process for PTM reuse. Based on the identified practices, we describe useful attributes for model reuse, including provenance, reproducibility, and portability. Three challenges for PTM reuse are missing attributes, discrepancies between claimed and actual performance, and model risks. We substantiate these identified challenges with systematic measurements in the Hugging Face ecosystem. Our work informs future directions on optimizing deep learning ecosystems by automated measuring useful attributes and potential attacks, and envision future research on infrastructure and standardization for model registries

Effects of continuity of care on hospitalizations and healthcare costs in older adults with dementia

Introduction People with dementia have high rates of hospitalization, and a share of these hospitalizations might be avoidable with appropriate ambulatory care, also known as potentially preventable hospitalization (PAH). This study investigates the associations between continuity of care and healthcare outcomes in the following year, including all-cause hospitalization, PAHs, and healthcare costs in patients with dementia. Methods This is a longitudinal retrospective cohort study of 69,658 patients with dementia obtained from the Taiwan National Health Insurance Research Database. The Continuity of Care Index (COCI) was calculated to measure the continuity of dementia-related visits across physicians. The PAHs were classified into five types as defined by the Medicare Ambulatory Care Indicators for the Elderly (MACIEs). Logistic regression models were used to examine the effect of COCI on all-cause hospitalizations and PAHs, while generalized linear models were used to analyze the effect of COCI on outpatient, hospitalization, and total healthcare costs. Results The high COCI group was significantly associated with a lower likelihood of all-cause hospitalization than the low COCI group (OR = 0.848, 95%CI: 0.821–0.875). The COCI had no significant effect on PAHs but was associated with lower outpatient costs (exp(β) = 0.960, 95%CI: 0.941 ~ 0.979), hospitalization costs (exp(β) = 0.663, 95%CI: 0.614 ~ 0.717), total healthcare costs (exp(β) = 0.962, 95%CI: 0.945–0.980). Conclusion Improving continuity of care for dementia-related outpatient visits is recommended to reduce hospitalization and healthcare costs, although there was no statistically significant effect of continuity of care found on PAHs

Emulsified Nanoparticles Containing Inactivated Influenza Virus and CpG Oligodeoxynucleotides Critically Influences the Host Immune Responses in Mice

Antigen sparing and cross-protective immunity are regarded as crucial in pandemic influenza vaccine development. Both targets can be achieved by adjuvantation strategy to elicit a robust and broadened immune response. We assessed the immunogenicity of an inactivated H5N1 whole-virion vaccine (A/Vietnam/1194/2004 NIBRG-14, clade 1) formulated with emulsified nanoparticles and investigated whether it can induce cross-clade protecting immunity.After formulation with PELC, a proprietary water-in-oil-in-water nanoemulsion comprising of bioresorbable polymer/Span(R)85/squalene, inactivated virus was intramuscularly administered to mice in either one-dose or two-dose schedule. We found that the antigen-specific serum antibody responses elicited after two doses of non-adjuvanted vaccine were lower than those observed after a single dose of adjuvanted vaccine, PELC and the conventional alum adjuvant as well. Moreover, 5 microg HA of PELC-formulated inactivated virus were capable of inducing higher antibodies than those obtained from alum-adjuvanted vaccine. In single-dose study, we found that encapsulating inactivated virus into emulsified PELC nanoparticles could induce better antibody responses than those formulated with PELC-adsorbed vaccine. However, the potency was rather reduced when the inactivated virus and CpG (an immunostimulatory oligodeoxynucleotide containing unmethylated cytosine-guanosine motifs) were co-encapsulated within the emulsion. Finally, the mice who received PELC/CpG(adsorption)-vaccine could easily and quickly reach 100% of seroprotection against a homologous virus strain and effective cross-protection against a heterologous virus strain (A/Whooper swan/Mongolia/244/2005, clade 2.2).Encapsulating inactivated H5N1 influenza virus and CpG into emulsified nanoparticles critically influences the humoral responses against pandemic influenza. These results demonstrated that the use of PELC could be as antigen-sparing in preparation for a potential shortage of prophylactic vaccines against local infectious diseases, in particular pandemic influenza. Moreover, the cross-clade neutralizing antibody responses data verify the potential of such adjuvanted H5N1 candidate vaccine as an effective tool in pre-pandemic preparedness

Using an Uncertainty-Coding Matrix in Bayesian Regression Models for Haplotype-Specific Risk Detection in Family Association Studies

Haplotype association studies based on family genotype data can provide more biological information than single marker association studies. Difficulties arise, however, in the inference of haplotype phase determination and in haplotype transmission/non-transmission status. Incorporation of the uncertainty associated with haplotype inference into regression models requires special care. This task can get even more complicated when the genetic region contains a large number of haplotypes. To avoid the curse of dimensionality, we employ a clustering algorithm based on the evolutionary relationship among haplotypes and retain for regression analysis only the ancestral core haplotypes identified by it. To integrate the three sources of variation, phase ambiguity, transmission status and ancestral uncertainty, we propose an uncertainty-coding matrix which combines these three types of variability simultaneously. Next we evaluate haplotype risk with the use of such a matrix in a Bayesian conditional logistic regression model. Simulation studies and one application, a schizophrenia multiplex family study, are presented and the results are compared with those from other family based analysis tools such as FBAT. Our proposed method (Bayesian regression using uncertainty-coding matrix, BRUCM) is shown to perform better and the implementation in R is freely available

Production of Inactivated Influenza H5N1 Vaccines from MDCK Cells in Serum-Free Medium

BACKGROUND: Highly pathogenic influenza viruses pose a constant threat which could lead to a global pandemic. Vaccination remains the principal measure to reduce morbidity and mortality from such pandemics. The availability and surging demand for pandemic vaccines needs to be addressed in the preparedness plans. This study presents an improved high-yield manufacturing process for the inactivated influenza H5N1 vaccines using Madin-Darby canine kidney (MDCK) cells grown in a serum-free (SF) medium microcarrier cell culture system. PRINCIPAL FINDING: The current study has evaluated the performance of cell adaptation switched from serum-containing (SC) medium to several commercial SF media. The selected SF medium was further evaluated in various bioreactor culture systems for process scale-up evaluation. No significant difference was found in the cell growth in different sizes of bioreactors studied. In the 7.5 L bioreactor runs, the cell concentration reached to 2.3 × 10(6) cells/mL after 5 days. The maximum virus titers of 1024 Hemagglutinin (HA) units/50 µL and 7.1 ± 0.3 × 10(8) pfu/mL were obtained after 3 days infection. The concentration of HA antigen as determined by SRID was found to be 14.1 µg/mL which was higher than those obtained from the SC medium. A mouse immunogenicity study showed that the formalin-inactivated purified SF vaccine candidate formulated with alum adjuvant could induce protective level of virus neutralization titers similar to those obtained from the SC medium. In addition, the H5N1 viruses produced from either SC or SF media showed the same antigenic reactivity with the NIBRG14 standard antisera. CONCLUSIONS: The advantages of this SF cell-based manufacturing process could reduce the animal serum contamination, the cost and lot-to-lot variation of SC medium production. This study provides useful information to manufacturers that are planning to use SF medium for cell-based influenza vaccine production

Pilot Scale Production of Highly Efficacious and Stable Enterovirus 71 Vaccine Candidates

BACKGROUND: Enterovirus 71 (EV71) has caused several epidemics of hand, foot and mouth diseases (HFMD) in Asia and now is being recognized as an important neurotropic virus. Effective medications and prophylactic vaccine against EV71 infection are urgently needed. Based on the success of inactivated poliovirus vaccine, a prototype chemically inactivated EV71 vaccine candidate has been developed and currently in human phase 1 clinical trial. PRINCIPAL FINDING: In this report, we present the development of a serum-free cell-based EV71 vaccine. The optimization at each step of the manufacturing process was investigated, characterized and quantified. In the up-stream process development, different commercially available cell culture media either containing serum or serum-free was screened for cell growth and virus yield using the roller-bottle technology. VP-SFM serum-free medium was selected based on the Vero cell growth profile and EV71 virus production. After the up-stream processes (virus harvest, diafiltration and concentration), a combination of gel-filtration liquid chromatography and/or sucrose-gradient ultracentrifugation down-stream purification processes were investigated at a pilot scale of 40 liters each. Although the combination of chromatography and sucrose-gradient ultracentrifugation produced extremely pure EV71 infectious virus particles, the overall yield of vaccine was 7-10% as determined by a VP2-based quantitative ELISA. Using chromatography as the downstream purification, the virus yield was 30-43%. To retain the integrity of virus neutralization epitopes and the stability of the vaccine product, the best virus inactivation was found to be 0.025% formalin-treatment at 37 °C for 3 to 6 days. Furthermore, the formalin-inactivated virion vaccine candidate was found to be stable for >18 months at 4 °C and a microgram of viral proteins formulated with alum adjuvant could induce strong virus-neutralizing antibody responses in mice, rats, rabbits, and non-human primates. CONCLUSION: These results provide valuable information supporting the current cell-based serum-free EV71 vaccine candidate going into human Phase I clinical trials