Secure Key Generation from OFDM Subcarriers’ Channel Response

The ability to exchange keys between users is vital in any wireless based security system. A key generation technique exploits the randomness of the wireless channel is a promising alternative to existing key distribution techniques, e.g., public key cryptography. In this paper a secure key generation scheme based on the subcarriers’ channel responses in orthogonal frequencydivision multiplexing (OFDM) systems is proposed. We first implement a time-variant multipath channel with its channel impulse response modelled as a wide sense stationary (WSS) uncorrelated scattering random process and demonstrate that each subcarrier’s channel response is also a WSS random process. We then define the X% coherence time as the time required to produce an X% correlation coefficient in the autocorrelation function (ACF) of each channel tap, and find that when all the channel taps have the same Doppler power spectrum, all subcarriers’ channel responses has the same ACF as the channel taps. The subcarrier’s channel response is then sampled every X% coherence time and quantized into key bits. All the key sequences’ randomness is tested using National Institute of Standards and Technology (NIST) statistical test suite and the results indicate that the commonly used sampling interval as 50% coherence time cannot guarantee the randomness of the key sequence.

Spindle assembly checkpoint protein expression correlates with cellular proliferation and shorter time to recurrence in ovarian cancer.

Ovarian carcinoma (OC) is the most lethal of the gynecological malignancies, often presenting at an advanced stage. Treatment is hampered by high levels of drug resistance. The taxanes are microtubule stabilizing agents, used as first-line agents in the treatment of OC that exert their apoptotic effects through the spindle assembly checkpoint. BUB1-related protein kinase (BUBR1) and mitotic arrest deficient 2 (MAD2), essential spindle assembly checkpoint components, play a key role in response to taxanes. BUBR1, MAD2, and Ki-67 were assessed on an OC tissue microarray platform representing 72 OC tumors of varying histologic subtypes. Sixty-one of these patients received paclitaxel and platinum agents combined; 11 received platinum alone. Overall survival was available for all 72 patients, whereas recurrence-free survival (RFS) was available for 66 patients. Increased BUBR1 expression was seen in serous carcinomas, compared with other histologies (P = .03). Increased BUBR1 was significantly associated with tumors of advanced stage (P = .05). Increased MAD2 and BUBR1 expression also correlated with increased cellular proliferation (P < .0002 and P = .02, respectively). Reduced MAD2 nuclear intensity was associated with a shorter RFS (P = .03), in ovarian tumors of differing histologic subtype (n = 66). In this subgroup, for those women who received paclitaxel and platinum agents combined (n = 57), reduced MAD2 intensity also identified women with a shorter RFS (P < .007). For the entire cohort of patients, irrespective of histologic subtype or treatment, MAD2 nuclear intensity retained independent significance in a multivariate model, with tumors showing reduced nuclear MAD2 intensity identifying patients with a poorer RFS (P = .05).

MIR-433 Predicts poor response to chemotherapy in ovarian cancer patients by the induction of cellular senescence

Annually, ovarian cancer (OC) affects 240,000 women worldwide and is the most lethal gynaecological malignancy. Such mortality is predominantly associated with the development of an intrinsic and acquired resistance to chemotherapy, the lack of targeted therapies and the lack of biomarkers predicting response to standard treatment.

Our clinical data demonstrates that increased miR-433 expression in primary high grade serous OC (HGSOCs) is significantly associated with poor PFS (n=46, p=0.024). Interestingly, the IHC analysis of two miR-433 targets: MAD2 [1] and HDAC6 shows that low IHC levels of both proteins is also significantly associated with worse outcome (p=0.002 and 0.002 respectively; n=43). Additionally, the analysis of miR 433 in the publicly available TCGA dataset corroborates that high miR-433 is significantly correlated with worse OS for patients presenting with OC (n=558 and p=0.027). In vito, in a panel of OC cell lines, higher miR-433 and lower MAD2 and HDAC6 levels were associated with resistance to paclitaxel.

To further investigate the role of miR-433 in the cellular response to chemotherapy, we generated an OC cell line stably expressing miR-433 or miR-control. MTT viability assays and Western Blot analyses established that miR-433 cells were more resistant to paclitaxel treatment (50nM) compared to miR-controls. Importantly, we have shown for the first time that miR 433 induced senescence resulting in a chracteristic flattened morphology and down-regulation of phosphorylated Retinoblastoma (p Rb), a molecular marker of senescence. Surprisingly, miR 433 induced senescence was independent from two well recognised senescent drivers: namely p53/p21 and p16. To explore this further we performed an in silico analysis of seven microRNA platforms which indicated that miR 433 potentially targets Cyclin-dependent kinase CDK6, which promotes sustained phosphorylation of Rb and thus cell cycle progression. In vitro, the overexpression of pre-miR-433 resulted in diminished CDK6 expression demonstrating a novel interaction between miR-433 and CDK6.

In conclusion, this study demonstrates that high miR-433 expression predicts poor outcome in OC patients by putatively rendering OC cells resistant to paclitaxel treatment through the induction of cellular senescence identifying this microRNA as a potential marker of chemoresponse.

Identification of systemic immune response markers through metabolomic profiling of plasma from calves given an intra-nasally delivered respiratory vaccine

Vaccination procedures within the cattle industry are important disease control tools to minimize economic and welfare burdens associated with respiratory pathogens. However, new vaccine, antigen and carrier technologies are required to combat emerging viral strains and enhance the efficacy of respiratory vaccines, particularly at the point of pathogen entry. New technologies, specifically metabolomic profiling, could be applied to identify metabolite immune-correlates representative of immune protection following vaccination aiding in the design and screening of vaccine candidates. This study for the first time demonstrates the ability of untargeted UPLC-MS metabolomic profiling to identify metabolite immune correlates characteristic of immune responses following mucosal vaccination in calves. Male Holstein Friesian calves were vaccinated with Pfizer Rispoval® PI3 + RSV intranasal vaccine and metabolomic profiling of post-vaccination plasma revealed 12 metabolites whose peak intensities differed significantly from controls. Plasma levels of glycocholic acid, N-[(3α,5β,12α)-3,12-Dihydroxy-7,24-dioxocholan-24-yl]glycine, uric acid and biliverdin were found to be significantly elevated in vaccinated animals following secondary vaccine administration, whereas hippuric acid significantly decreased. In contrast, significant upregulation of taurodeoxycholic acid and propionylcarnitine levels were confined to primary vaccine administration. Assessment of such metabolite markers may provide greater information on the immune pathways stimulated from vaccine formulations and benchmarking early metabolomic responses to highly immunogenic vaccine formulations could provide a means for rapidly assessing new vaccine formulations. Furthermore, the identification of metabolic systemic immune response markers which relate to specific cell signaling pathways of the immune system could allow for targeted vaccine design to stimulate key pathways which can be assessed at the metabolic level.

Blind Characterisation of Sensors with Second-Order Dynamic Response

Compensation for the dynamic response of a temperature sensor usually involves the estimation of its input on the basis of the measured output and model parameters. In the case of temperature measurement, the sensor dynamic response is strongly dependent on the measurement environment and fluid velocity. Estimation of time-varying sensor model parameters therefore requires continuous textit{in situ} identification. This can be achieved by employing two sensors with different dynamic properties, and exploiting structural redundancy to deduce the sensor models from the resulting data streams. Most existing approaches to this problem assume first-order sensor dynamics. In practice, however second-order models are more reflective of the dynamics of real temperature sensors, particularly when they are encased in a protective sheath. As such, this paper presents a novel difference equation approach to solving the blind identification problem for sensors with second-order models. The approach is based on estimating an auxiliary ARX model whose parameters are related to the desired sensor model parameters through a set of coupled non-linear algebraic equations. The ARX model can be estimated using conventional system identification techniques and the non-linear equations can be solved analytically to yield estimates of the sensor models. Simulation results are presented to demonstrate the efficiency of the proposed approach under various input and parameter conditions.

Game-­theoretic Resource Allocation with Real-­time Probabilistic Surveillance Information

Game-theoretic security resource allocation problems have generated significant interest in the area of designing and developing security systems. These approaches traditionally utilize the Stackelberg game model for security resource scheduling in order to improve the protection of critical assets. The basic assumption in Stackelberg games is that a defender will act first, then an attacker will choose their best response after observing the defender’s strategy commitment (e.g., protecting a specific asset). Thus, it requires an attacker’s full or partial observation of a defender’s strategy. This assumption is unrealistic in real-time threat recognition and prevention. In this paper, we propose a new solution concept (i.e., a method to predict how a game will be played) for deriving the defender’s optimal strategy based on the principle of acceptable costs of minimax regret. Moreover, we demonstrate the advantages of this solution concept by analyzing its properties.

Time and Cell Type Dependency of Survival Responses in Co-cultured Tumor and Fibroblast Cells after Exposure to Modulated Radiation Fields

Advanced radiotherapy techniques such as intensity-modulated radiation therapy (IMRT) achieve high levels of conformity to the target volume through the sequential delivery of highly spatially and temporally modulated radiation fields, which have been shown to impact radiobiological response. This study aimed to characterize the time and cell type dependency of survival responses to modulated fields using single cell type (SCT) and mixed cell type (MCT) co-culture models of transformed fibroblast (AG0-1522b) cells, and prostate (DU-145) and lung (H460) cancer cells. In SCT cultures, in-field responses showed no significant time dependency while out-of-field responses occurred early, and plateaued 6 h after irradiation in both DU-145 and H460 cells. Under modulated beam configurations MCT co-cultures showed cell-specific, differential out-of-field responses depending on the irradiated in-field and responding out-of-field cell type. The observed differential out-of-field responses may be due to the genetic background of the cells, in particular p53 status, which has been shown to mediate radiation-induced bystander effects (RIBEs). These data provide further insight into the radiobiological parameters that influence out-of-field responses, which have potential implications for advanced radiotherapy modalities and may provide opportunities for biophysical optimization in radiotherapy treatment planning.

High resolution monitoring of surface morphological change of building limestones in response to simulated salt weathering

A salt weathering simulation using a mix of sodium chloride (5%) and magnesium sulphate (5%) in a salt corrosion cabinet and five granular limestones is described. Progressive surface loss from vertical exposed faces was mapped using a high resolution (sub-millimetre) object scanner (Konica Minolta Vi9i). Patterns of loss are related to surface porosity/permeability measurements obtained using a hand-held gas permeameter. Introduction of this spatial dimension into damage assessment is seen as essential for understanding the initial conditions that allow surface loss to be triggered, and changes in surface characteristics as weathering proceeds which dictate subsequent decay in space and time. Preliminary observations suggest that scanning at this high resolution is particularly valuable in quantifying very subtle trends and distortions that are pre-cursors to material loss, including surface swelling and pore filling.

Hierarchical Demand Response for Peak Reduction using Dantzig‐Wolfe Decomposition

Demand Response (DR) algorithms manipulate the energy consumption schedules of controllable loads so as to satisfy grid objectives. Implementation of DR algorithms using a centralised agent can be problematic for scalability reasons, and there are issues related to the privacy of data and robustness to communication failures. Thus it is desirable to use a scalable decentralised algorithm for the implementation of DR. In this paper, a hierarchical DR scheme is proposed for Peak Minimisation (PM) based on Dantzig-Wolfe Decomposition (DWD). In addition, a Time Weighted Maximisation option is included in the cost function which improves the Quality of Service for devices seeking to receive their desired energy sooner rather than later. The paper also demonstrates how the DWD algorithm can be implemented more efficiently through the calculation of the upper and lower cost bounds after each DWD iteration.

Measuring a cell's response to stress:the p53 pathway.

Demand response to improved walking infrastructure: A study into the economics of walking and health behaviour change

Walking is the most common form of moderate‐intensity physical activity among adults, is widely accessible and especially appealing to obese people. Most often policy makers are interested in valuing the effect on walking of changes in some characteristics of a neighbourhood, the demand response for walking, of infrastructure changes. A positive demand response to improvements in the walking environment could help meet the public health target of 150 minutes of at least moderate‐intensity physical activity per week. We model walking in an individual’s local neighbourhood as a ‘weak complement’ to the characteristics of the neighbourhood itself. Walking is affected by neighbourhood
characteristics, substitutes, and individual’s characteristics, including their opportunity cost of time.  Using compensating variation, we assess the economic benefits of walking and how walking behaviour is affected by improvements to the neighbourhood.  Using a sample of 1,209 respondents surveyed over a 12 month period (Feb 2010‐Jan 2011) in East Belfast, United Kingdom, we find that a policy that increased walkability and people’s perception of access to shops and facilities  would lead to an increase in walking of about 36 minutes/person/week, valued at £13.65/person/week. When focusing on inactive residents, a policy that improved the walkability of the area would lead to guidelines for physical activity being reached by only 12.8% of the population who are currently inactive. Additional interventions would therefore be needed to encourage inactive residents to
achieve the recommended levels of physical activity, as it appears that interventions that improve the walkability of an area are particularly effective in increasing walking among already active citizens, and, among the inactive ones, the best response is found among healthier, younger and wealthier citizens.

Transcriptional response of T cells to IFN-alpha:changes induced in IFN-alpha-sensitive and resistant cutaneous T cell lymphoma

Interferon-alpha (IFN-alpha) therapy is commonly used in the treatment of neoplastic and autoimmune diseases, including cutaneous T cell lymphoma (CTCL). However, the IFN-alpha response is unpredictable, and the IFN-alpha cell targets and pathways are only partially understood. To delineate the molecular mechanisms of IFN-alpha activity, gene expression profiling was performed in a time-course experiment of both IFN-alpha sensitive and IFN-alpha-resistant variants of a CTCL cell line. These experiments revealed that IFN-alpha is responsible for the regulation of hundreds of genes in both variants and predominantly involves genes implicated in signal transduction, cell cycle control, apoptosis, and transcription regulation. Specifically, the IFN-alpha response of tumoral T cells is due to a combination of induction of apoptosis in which TNFSF10 and HSXIAPAF1 may play an important role and cell cycle arrest achieved by downregulation of CDK4 and CCNG2 and upregulation of CDKN2C and tumor suppressor genes (TSGs). Resistance to IFN-alpha appears to be associated with failure to induce IRF1 and IRF7 and deregulation of the apoptotic signals of HSXIAPAF1, TRADD, BAD, and BNIP3. Additionally, cell cycle progression is heralded by upregulation of CDC25A and CDC42. A critical role of NF-kappaB in promoting cell survival in IFN-alpha-resistant cells is indicated by the upregulation of RELB and LTB.