Emerging bacterial resistance patterns in febrile neutropenic patients: experience at a tertiary care hospital in Pakistan

Objective: To look at the clinical presentations, spectrum and site of isolation of the organisms, sensitivity patterns of the organisms and the antibiotic prescribing practices for the treatment of febrile neutropenic patients at our hospital.Methods: The data were collected retrospectively from the records of all neutropenic patients with an absolute neutrophil count (ANC) of less than 500/ml admitted during the period of 3 years from August 1999 to July 2002 at AKUH.Results: Out of the total of 404 patients, 65% had hematological malignancies and around half of them had leukaemia, 86% of the patients presented with fever. A total of 124 bacterial organisms were isolated from 96 patients among which 47% were gram positive and 53% were gram negative organisms; 16.1% of the patients had septicaemia. Coagulase Negative Staphylococci (CoNS) were the most common gram positive and E. coli was the most commonly isolated gram negative organism. Most of the gram positive organisms were isolated from blood (67%). There was emerging resistance to all commonly used antibiotics including imipenem, cloxacillin, vancomycin and amikacin. The average duration of neutropenia was 6.4 days. The mortality rate was 6%.CONCLUSION: There is increasing trend of gram negative organisms developing resistance to commonly used antibiotics. Gram positive bacteria including Enterococcus spp. and CoNS are also showing emerging resistance to vancomycin

Energy Efficient Service Distribution in Internet of Things

The Internet of Things (IoT) networks are expected to involve myriad of devices, ranging from simple sensors to powerful single board computers and smart phones. The great advancement in computational power of embedded technologies have enabled the integration of these devices into the IoT network, allowing for cloud functionalities to be extended near to the source of data. In this paper we study a multi-layer distributed IoT architecture supported by fog and cloud. We optimize the placement of the IoT services in this architecture so that the total power consumption is minimized. Our results show that, introducing local computation at the IoT layer can bring up to 90% power savings compared with general purpose servers in a central cloud

Energy Efficient Service Distribution in Internet of Things

The Internet of Things (IoT) networks are expected to involve myriad of devices, ranging from simple sensors to powerful single board computers and smart phones. The great advancement in computational power of embedded technologies have enabled the integration of these devices into the IoT network, allowing for cloud functionalities to be extended near to the source of data. In this paper we study a multi-layer distributed IoT architecture supported by fog and cloud. We optimize the placement of the IoT services in this architecture so that the total power consumption is minimized. Our results show that, introducing local computation at the IoT layer can bring up to 90% power savings compared with general purpose servers in a central cloud

Energy Minimized Federated Fog Computing over Passive Optical Networks

The rapid growth of time-sensitive applications and services has driven enhancements to computing infrastructures. The main challenge that needs addressing for these applications is the optimal placement of the end-users’ demands to reduce the total power consumption and delay. One of the widely adopted paradigms to address such a challenge is fog computing. Placing fog units close to end-users at the edge of the network can help mitigate some of the latency and energy efficiency issues. Compared to the traditional hyperscale cloud data centres, fog computing units are constrained by computational power, hence, the capacity of fog units plays a critical role in meeting the stringent demands of the end-users due to intensive processing workloads. In this paper, we first propose a federated fog computing architecture where multiple distributed fog cells collaborate in serving users. These fog cells are connected through dedicated Passive Optical Network (PON) connections. We then aim to optimize the placement of virtual machines (VMs) demands originating from the end-users by formulating a Mixed Integer Linear Programming (MILP) model to minimize the total power consumption. The results show an increase in processing capacity and a reduction in the power consumption by up to 26% compared to a Non-Federated fogs computing architecture

Energy Efficient Resource Allocation in Federated Fog Computing Networks

There is a continuous growth in demand for time sensitive applications which has shifted the cloud paradigm from a centralized computing architecture towards distributed heterogeneous computing platforms where resources located at the edge of the network are used to provide cloud-like services. This paradigm is widely known as fog computing. Virtual machines (VMs) have been widely utilized in both paradigms to enhance the network scalability, improve resource utilization, and energy efficiency. Moreover, Passive Optical Networks (PON s) are a technology suited to handling the enormous volumes of data generated in the access network due to their energy efficiency and large bandwidth. In this paper, we utilize a PON to provide the connectivity between multiple distributed fog units to achieve federated (i.e., cooperative) computing units in the access network to serve intensive demands. We propose a mixed integer linear program (MILP) to optimize the VM placement in the federated fog computing units with the objective of minimizing the total power consumption while considering inter- Vmtraffic. The results show a significant power saving as a result of the proposed optimization model by up to 52%, in the VM -allocation compared to a baseline approach that allocates the VM requests while neglecting the power consumption and inter-VMs traffic in the optimization framework

Термодинамический метод расчета теплоты парообразования бинарных смесей

In article results and calculations of heat of binary mixes on the basis of the developed thermodynamic analysis of process of transition a liquid- vapor are presented.В статье приводятся результаты расчета теплоты бинарных смесей на основе разработанного термодинамического анализа процесса перехода жидкость-пар

Температурная зависимость теплоты парообразования чистых углеводородов и их бинарных смесей

In this article the results of experimental data for heats of steam formation depending on temperature (density) for individual organic substances and mixtures are presentedВ статье приводятся результаты в приведенной форме представления экспериментальных данных теплоты парообразования в зависимости от приведенной температуры (плотности) для индивидуальных органических веществ и их смесей

Common Breast Cancer Susceptibility Alleles and the Risk of Breast Cancer for BRCA1 and BRCA2 Mutation Carriers: Implications for Risk Prediction

The known breast cancer (BC) susceptibility polymorphisms in FGFR2, TNRC9/TOX3, MAP3K1,LSP1 and 2q35 confer increased risks of BC for BRCA1 or BRCA2 mutation carriers. We evaluated the associations of three additional SNPs, rs4973768 in SLC4A7/NEK10, rs6504950 in STXBP4/COX11 and rs10941679 at 5p12 and reanalyzed the previous associations using additional carriers in a sample of 12,525 BRCA1 and 7,409 BRCA2 carriers. Additionally, we investigated potential interactions between SNPs and assessed the implications for risk prediction. The minor alleles of rs4973768 and rs10941679 were associated with increased BC risk for BRCA2 carriers (per-allele Hazard Ratio (HR)=1.10, 95%CI:1.03-1.18, p=0.006 and HR=1.09, 95%CI:1.01-1.19, p=0.03, respectively). Neither SNP was associated with BC risk for BRCA1 carriers and rs6504950 was not associated with BC for either BRCA1 or BRCA2 carriers. Of the nine polymorphisms investigated, seven were associated with BC for BRCA2 carriers (FGFR2, TOX3, MAP3K1, LSP1, 2q35, SLC4A7, 5p12, p-values:7×10−11-0.03), but only TOX3 and 2q35 were associated with the risk for BRCA1 carriers (p=0.0049, 0.03 respectively). All risk associated polymorphisms appear to interact multiplicatively on BC risk for mutation carriers. Based on the joint genotype distribution of the seven risk associated SNPs in BRCA2 mutation carriers, the 5% of BRCA2 carriers at highest risk (i.e. between 95th and 100th percentiles) were predicted to have a probability between 80% and 96% of developing BC by age 80, compared with 42-50% for the 5% of carriers at lowest risk. Our findings indicated that these risk differences may be sufficient to influence the clinical management of mutation carriers

Thermodynamic method of calculation of heat of steam formation for binary mixes

In article results and calculations of heat of binary mixes on the basis of the developed thermodynamic analysis of process of transition a liquid- vapor are presented