Canadian National Site Licensing Project: getting ready for CNSLP at the University of Saskatchewan Library

The Canadian National Site Licensing Project (CNSLP) is a national effort by a consortium of 64 Canadian university libraries to provide access to full text electronic journals. The first part of this paper describes the organization, funding structure, and activities, including license negotiations, of the CNSLP. The second part of this paper deals with the technical and operational issues related to electronic journal management. It describes the process developed at the University of Saskatchewan for incorporating the CNSLP material into the Library's collections and finding tools. An assessment of the jake utility as a reliable source of metadata is also presented

Adaptive Distributed Resource Allocation in Wireless Sensor Networks

Wireless sensor networks have emerged as a promising technology for a wide range of important applications. A major research challenge in this field is the distributed resource allocation problem, which concerns how the limited resources in a wireless sensor network should be allocated or scheduled to minimize costs and maximize the network capability. In this paper, we propose the Adaptive Distributed Resource Allocation (ADRA) scheme, an adaptive approach for distributed resource allocation in wireless sensor networks. Our scheme specifies relatively simple local actions to be performed by individual sensor nodes in a wireless sensor network for mode management. Each node adapts its operation over time in response to the status and feedback of its neighboring nodes. Desirable global behavior results from the local interactions between nodes. We study the effectiveness of the ADRA scheme for a realistic application scenario; namely, the sensor mode management in an acoustic sensor network to track vehicle movement. We evaluated the scheme via simulations, and also prototyped it using the Crossbow MICA2 motes. Our simulation and hardware implementation results indicate that the ADRA scheme provides a good tradeoff between performance objectives such as coverage area, power consumption, and network lifetime.Singapore-MIT Alliance (SMA

Excess body weight and age associated with the carriage of fluoroquinolone and third-generation cephalosporin resistance genes in commensal Escherichia coli from a cohort of urban Vietnamese children.

PURPOSE: Antimicrobial-resistant bacterial infections in low- and middle-income countries (LMICs) are a well-established global health issue. We aimed to assess the prevalence of and epidemiological factors associated with the carriage of ciprofloxacin- and ceftriaxone-resistant Escherichia coli and associated resistance genes in a cohort of 498 healthy children residing in urban Vietnam. METHODOLOGY: We cultured rectal swabs onto MacConkey agar supplemented with resistant concentrations of ciprofloxacin and ceftriaxone. Additionally, we screened meta-E. coli populations by conventional PCR to detect plasmid-mediated quinolone resistance (PMQR)- and extended-spectrum β-lactamase (ESBL)-encoding genes. We measured the associations between phenotypic/genotypic resistance and demographic characteristics using logistic regression.Results/Key findings. Ciprofloxacin- and ceftriaxone-resistant E. coli were cultured from the faecal samples of 67.7 % (337/498) and 80.3 % (400/498) of children, respectively. The prevalence of any associated resistance marker in the individual samples was 86.7 % (432/498) for PMQR genes and 90.6 % (451/498) for β-lactamase genes. Overweight children were significantly more likely to carry qnr genes than children with lower weight-for-height z-scores [odds ratios (OR): 1.24; 95 % confidence interval (CI): 10.5-1.48 for each unit increase in weight for height; P=0.01]. Additionally, younger children were significantly more likely to carry ESBL CTX-M genes than older children (OR: 0.97, 95 % CI: 0.94-0.99 for each additional year, P=0.01). CONCLUSION: The carriage of genotypic and phenotypic antimicrobial resistance is highly prevalent among E. coli in healthy children in the community in Vietnam. Future investigations on the carriage of antimicrobial resistant organisms in LMICs should focus on the progression of carriage from birth and structure of the microbiome in obesity

A modified Sequential Organ Failure Assessment score for dengue: development, evaluation and proposal for use in clinical trials

Background Dengue is a neglected tropical disease, for which no therapeutic agents have shown clinical efficacy to date. Clinical trials have used strikingly variable clinical endpoints, which hampers reproducibility and comparability of findings. We investigated a delta modified Sequential Organ Failure Assessment (delta mSOFA) score as a uniform composite clinical endpoint for use in clinical trials investigating therapeutics for moderate and severe dengue. Methods We developed a modified SOFA score for dengue, measured and evaluated its performance at baseline and 48 h after enrolment in a prospective observational cohort of 124 adults admitted to a tertiary referral hospital in Vietnam with dengue shock. The modified SOFA score included pulse pressure in the cardiovascular component. Binary logistic regression, cox proportional hazard and linear regression models were used to estimate association between mSOFA, delta mSOFA and clinical outcomes. Results The analysis included 124 adults with dengue shock. 29 (23.4%) patients required ICU admission for organ support or due to persistent haemodynamic instability: 9/124 (7.3%) required mechanical ventilation, 8/124 (6.5%) required vasopressors, 6/124 (4.8%) required haemofiltration and 5/124 (4.0%) patients died. In univariate analyses, higher baseline and delta (48 h) mSOFA score for dengue were associated with admission to ICU, requirement for organ support and mortality, duration of ICU and hospital admission and IV fluid use. Conclusions The baseline and delta mSOFA scores for dengue performed well to discriminate patients with dengue shock by clinical outcomes, including duration of ICU and hospital admission, requirement for organ support and death. We plan to use delta mSOFA as the primary endpoint in an upcoming host-directed therapeutic trial and investigate the performance of this score in other phenotypes of severe dengue in adults and children

Awareness and preparedness of healthcare workers against the first wave of the COVID-19 pandemic: A cross-sectional survey across 57 countries.

BACKGROUND: Since the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave. METHODS: This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected COVID-19 patients and prior COVID-19 case-management training. RESULTS: We surveyed 24,653 HCWs from 371 hospitals across 57 countries and received 17,302 responses from 70.2% HCWs overall. The median COVID-19 preparedness score was 11.0 (interquartile range [IQR] = 6.0-14.0) and the median awareness score was 29.6 (IQR = 26.6-32.6). HCWs at COVID-19 designated facilities with previous outbreak experience, or HCWs who were trained for dealing with the SARS-CoV-2 outbreak, had significantly higher levels of preparedness and awareness (p<0.001). Association rule mining suggests that nurses and doctors who had a 'great-extent-of-confidence' in handling suspected COVID-19 patients had participated in COVID-19 training courses. Male participants (mean difference = 0.34; 95% CI = 0.22, 0.46; p<0.001) and nurses (mean difference = 0.67; 95% CI = 0.53, 0.81; p<0.001) had higher preparedness scores compared to women participants and doctors. INTERPRETATION: There was an unsurprising high level of awareness and preparedness among HCWs who participated in COVID-19 training courses. However, disparity existed along the lines of gender and type of HCW. It is unknown whether the difference in COVID-19 preparedness that we detected early in the pandemic may have translated into disproportionate SARS-CoV-2 burden of disease by gender or HCW type

Spatiotemporal evolution of SARS-CoV-2 Alpha and Delta variants during large nationwide outbreak of COVID-19, Vietnam, 2021

We analyzed 1,303 SARS-CoV-2 whole-genome sequences from Vietnam, and found the Alpha and Delta variants were responsible for a large nationwide outbreak of COVID-19 in 2021. The Delta variant was confined to the AY.57 lineage and caused >1.7 million infections and >32,000 deaths. Viral transmission was strongly affected by nonpharmaceutical interventions

Scalable Traffic Management for Data Centers and Logging Devices

Traditional network resource allocation is not scalable because it requires per-flow state, large amount of memory in switches and routers, and control overhead. In this dissertation, we propose innovative and scalable mechanisms for network traffic management in three emerging contexts: network event loggers, network load balancing, and cloud services in data centers. First, we describe a probabilistic event logger called Carousel to collect unique items in a large stream of online events. By theoretical analysis, we prove that Carousel can collect almost all items with high probability. Our simulation and implementation prototype show an improvement factor of ten in event collection time. Second, we design a new load balancing algorithm called Flame that is implementable in high speed switches with small memory usage. Flame achieves fine granularity of load balancing at sub-flow level and binds flows to hash functions. Through trace simulation, we show that Flame can improve our load balancing performance metrics by an order of magnitude. Furthermore, Flame allows graceful degradation to the standard ECMP in the worst case. Lastly, we propose a mechanism called NetShare to provide predictable network resource allocation for cloud services based on simple administrative weights. We describe mechanisms to implement and scale NetShare to a large number of services using a generalization of Stochastic Fair Queueing. We validate our NetShare design on a hardware testbed with MapReduce workload

SENSING COVERAGE AND RESOURCE ALLOCATION ALGORITHMS IN SENSOR NETWORKS

Master'sMASTER OF SCIENCE IN COMPUTER SCIENC