Secure Hardware Performance Analysis in Virtualized Cloud Environment

The main obstacle in mass adoption of cloud computing for database operations is the data security issue. In this paper, it is shown that IT services particularly in hardware performance evaluation in virtual machine can be accomplished effectively without IT personnel gaining access to real data for diagnostic and remediation purposes. The proposed mechanisms utilized TPC-H benchmark to achieve 2 objectives. First, the underlying hardware performance and consistency is supervised via a control system, which is constructed using a combination of TPC-H queries, linear regression, and machine learning techniques. Second, linear programming techniques are employed to provide input to the algorithms that construct stress-testing scenarios in the virtual machine, using the combination of TPC-H queries. These stress-testing scenarios serve 2 purposes. They provide the boundary resource threshold verification to the first control system, so that periodic training of the synthetic data sets for performance evaluation is not constrained by hardware inadequacy, particularly when the resources in the virtual machine are scaled up or down which results in the change of the utilization threshold. Secondly, they provide a platform for response time verification on critical transactions, so that the expected Quality of Service (QoS) from these transactions is assured

TOA-based indoor localization and tracking with inaccurate floor plan map via MRMSC-PHD filter

This paper proposes a novel indoor localization scheme to jointly track a mobile device (MD) and update an inaccurate floor plan map using the time-of-arrival measured at multiple reference devices (RDs). By modeling the floor plan map as a collection of map features, the map and MD position can be jointly estimated via a multi-RD single-cluster probability hypothesis density (MSC-PHD) filter. Conventional MSC-PHD filters assume that each map feature generates at most one measurement for each RD. If single reflections of the detected signal are considered as measurements generated by map features, then higher-order reflections, which also carry information on the MD and map features, must be treated as clutter. The proposed scheme incorporates multiple reflections by treating them as virtual single reflections reflected from inaccurate map features and traces them to the corresponding virtual RDs (VRDs), referred to as a multi-reflection-incorporating MSC-PHD (MRMSC-PHD) filter. The complexity of using multiple reflection paths arises from the inaccuracy of the VRD location due to inaccuracy in the map features. Numerical results show that these multiple reflection paths can be modeled statistically as a Gaussian distribution. A computationally tractable implementation combining a new greedy partitioning scheme and a particle-Gaussian mixture filter is presented. A novel mapping error metric is then proposed to evaluate the estimated map's accuracy for plane surfaces. Simulation and experimental results show that our proposed MRMSC-PHD filter outperforms the existing MSC-PHD filters by up to 95% in terms of average localization and by up to 90% in terms of mapping accuracy

Localization in GPS denied environment

No abstract available

Applying System Safety Methodology and Related Tools for a Public Private Partnership Programme

Abstract Governmental agencies, including the Armed Forces, may require services that are available and ably provided by the private sector. Such collaborations between the public and private entities, commonly known as Public Private Partnerships (PPP), bring benefits to both parties and are well documented. This includes the ability to tap on the private sectors' facilities and resources without the need for the governmental agencies to make a similar high investment, while providing added revenue to the private sector. This paper shares how the Defence Science and Technology Agency (DSTA), a statutory board under Singapore's Ministry of Defence (MINDEF), applied the System Safety process for a PPP programme. The programme entails the acquisition of the services of a vertical wind tunnel as a simulator to provide a safe, realistic and costeffective free-fall training environment for the Singapore Armed Forces (SAF). The vertical wind tunnel facility is also open to the general public as a sporting and leisure facility. The paper discusses the challenges faced, the strategies implemented, and introduces two atypical tools that were utilised to good effect. One of the tools used is the Goal Structuring Notation (GSN) tool. The authors used the GSN tool as a graphical notation to communicate the structure of safety arguments. This approach facilitated the visualisation of how the safety integrity of the PPP Programme was ascertained

Health-related quality of life of patients with inflammatory bowel disease in Singapore

Background/Aims Inflammatory bowel disease (IBD) is associated with considerable impairment of patients’ health-related quality of life (HRQoL). Knowledge of factors that significantly affect IBD patients’ HRQoL can contribute to better patient care. However, the HRQoL of IBD patients in non-Western countries are limited. Hence, we assessed the HRQoL of Singaporean IBD patients and identified its determinants. Methods A prospective, cross-sectional study was conducted at Singapore General Hospital outpatient IBD Centre. The HRQoL of IBD patients was assessed using the short IBD questionnaire (SIBDQ), Short Form-36 physical and mental component summary (SF-36 PCS/MCS) and EuroQol 5-dimensions 3-levels (EQ-5D-3L) and visual analogue scale (VAS). Independent samples t-test was used to compare HRQoL between Crohn’s disease (CD) and ulcerative colitis (UC). Determinants of HRQoL were identified through multiple linear regression. Results A total of 195 IBD patients (103 UC, 92 CD) with a mean disease duration of 11.2 years were included. There was no significant difference in HRQoL between patients with UC and CD. Factors that significantly worsened HRQoL were presence of active disease (b=−6.293 [SIBDQ], −9.409 [PCS], −9.743 [MCS], −7.254 [VAS]), corticosteroids use (b=−7.392 [SIBDQ], −10.390 [PCS], −8.827 [MCS]), poor medication adherence (b=−4.049 [SIBDQ], −1.320 [MCS], −8.961 [VAS]), presence of extraintestinal manifestations (b=−13.381 [PCS]), comorbidities (b=−4.531 [PCS]), non-employment (b=−9.738 [MCS], −0.104 [EQ-5D-3L]) and public housing (b=−8.070 [PCS], −9.207 [VAS]). Conclusions The HRQoL is impaired in this Asian cohort of IBD. The magnitude of HRQoL impairment was similar in UC and CD. Clinical characteristics were better determinants of patients’ HRQoL than socio-demographic factors. Recognizing the factors that impact patients’ HRQoL would improve the holistic management of IBD patients

Awareness of venous thromboembolism among patients with cancer: Preliminary findings from a global initiative for World Thrombosis Day

BACKGROUND Cancer-associated venous thromboembolism (CAT) has detrimental impact on patients' clinical outcomes and quality of life. Data on CAT education, communication, and awareness among the general cancer population are scanty. METHODS We present the preliminary results of an ongoing patient-centered survey including 27 items covering major spheres of CAT. The survey, available in 14 languages, was promoted and disseminated online through social networks, email newsletters, websites, and media. RESULTS As of September 20, 2022, 749 participants from 27 countries completed the survey. Overall, 61.8% (n = 460) of responders were not aware of their risk of CAT. Among those who received information on CAT, 26.2% (n = 56) were informed only at the time of CAT diagnosis. Over two thirds (69.1%, n = 501) of participants received no education on signs and symptoms of venous thromboembolism (VTE); among those who were educated about the possible clinical manifestations, 58.9% (n = 119) were given instructions to seek consultation in case of VTE suspicion. Two hundred twenty-four respondents (30.9%) had a chance to discuss the potential use of primary thromboprophylaxis with health-care providers. Just over half (58.7%, n = 309) were unaware of the risks of bleeding associated with anticoagulation, despite being involved in anticoagulant-related discussions or exposed to anticoagulants. Most responders (85%, n = 612) valued receiving CAT education as highly relevant; however, 51.7% (n = 375) expressed concerns about insufficient time spent and clarity of education received. CONCLUSIONS This ongoing survey involving cancer patients with diverse ethnic, cultural, and geographical backgrounds highlights important patient knowledge gaps. These findings warrant urgent interventions to improve education and awareness, and reduce CAT burden

Recurrent Fusion Genes in Gastric Cancer: CLDN18-ARHGAP26 Induces Loss of Epithelial Integrity.

Genome rearrangements, a hallmark of cancer, can result in gene fusions with oncogenic properties. Using DNA paired-end-tag (DNA-PET) whole-genome sequencing, we analyzed 15 gastric cancers (GCs) from Southeast Asians. Rearrangements were enriched in open chromatin and shaped by chromatin structure. We identified seven rearrangement hot spots and 136 gene fusions. In three out of 100 GC cases, we found recurrent fusions between CLDN18, a tight junction gene, and ARHGAP26, a gene encoding a RHOA inhibitor. Epithelial cell lines expressing CLDN18-ARHGAP26 displayed a dramatic loss of epithelial phenotype and long protrusions indicative of epithelial-mesenchymal transition (EMT). Fusion-positive cell lines showed impaired barrier properties, reduced cell-cell and cell-extracellular matrix adhesion, retarded wound healing, and inhibition of RHOA. Gain of invasion was seen in cancer cell lines expressing the fusion. Thus, CLDN18-ARHGAP26 mediates epithelial disintegration, possibly leading to stomach H(+) leakage, and the fusion might contribute to invasiveness once a cell is transformed. Cell Rep 2015 Jul 14; 12(2):272-285

Rapamycin synergizes cisplatin sensitivity in basal-like breast cancer cells through up-regulation of p73.

Recent gene expression profiling studies have identified five breast cancer subtypes, of which the basal-like subtype is the most aggressive. Basal-like breast cancer poses serious clinical challenges as there are currently no targeted therapies available to treat it. Although there is increasing evidence that these tumors possess specific sensitivity to cisplatin, its success is often compromised due to its dose-limiting nephrotoxicity and the development of drug resistance. To overcome this limitation, our goal was to maximize the benefits associated with cisplatin therapy through drug combination strategies. Using a validated kinase inhibitor library, we showed that inhibition of the mTOR, TGFβRI, NFκB, PI3K/AKT, and MAPK pathways sensitized basal-like MDA-MB-468 cells to cisplatin treatment. Further analysis demonstrated that the combination of the mTOR inhibitor rapamycin and cisplatin generated significant drug synergism in basal-like MDA-MB-468, MDA-MB-231, and HCC1937 cells but not in luminal-like T47D or MCF-7 cells. We further showed that the synergistic effect of rapamycin plus cisplatin on basal-like breast cancer cells was mediated through the induction of p73. Depletion of endogenous p73 in basal-like cells abolished these synergistic effects. In conclusion, combination therapy with mTOR inhibitors and cisplatin may be a useful therapeutic strategy in the treatment of basal-like breast cancers

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing