Current-induced transition in atomic-sized contacts of metallic alloys

We have measured conductance histograms of atomic point contacts made from the noble-transition-metal alloys CuNi, AgPd, and AuPt for a concentration ratio of 1:1. For all alloys these histograms at low-bias voltage (below 300 mV) resemble those of the noble metals, whereas at high bias (above 300 mV) they resemble those of the transition metals. We interpret this effect as a change in the composition of the point contact with bias voltage. We discuss possible explanations in terms of electromigration and differential diffusion induced by current heating.

Potential improvements in the therapeutic ratio of prostate cancer irradiation: dose escalation of pathologically identified tumour nodules using intensity modulated radiotherapy.

The potential of intensity modulated radiotherapy (IMRT) to improve the therapeutic ratio in prostate cancer by dose escalation of intraprostatic tumour nodules (IPTNs) was investigated using a simultaneous integrated boost technique. The prostate and organs-at-risk were outlined on CT images from six prostate cancer patients. Positions of IPTNs were transferred onto the CT images from prostate maps derived from sequential large block sections of whole prostatectomy specimens. Inverse planned IMRT dose distributions were created to irradiate the prostate to 70 Gy and all the IPTNs to 90 Gy. A second plan was produced to escalate only the dominant IPTN (DIPTN) to 90 Gy, mimicking current imaging techniques. These plans were compared with homogeneous prostate irradiation to 70 Gy using dose–volume histograms, tumour control probability (TCP) and normal tissue complication probability (NTCP) for the rectum. The mean dose to IPTNs was increased from 69.8 Gy to 89.1 Gy if all the IPTNs were dose escalated (p=0.0003). This corresponded to a mean increase in TCP of 8.7–31.2% depending on the /ß ratio of prostate cancer (p

A comparison of conformal and intensity-modulated techniques for oesophageal radiotherapy.

Background and purpose: To investigate the potential of intensity-modulated radiotherapy (IMRT) to reduce lung irradiation in the treatment of oesophageal carcinoma with radical radiotherapy.Materials and methods: A treatment planning study was performed to compare two-phase conformal radiotherapy (CFRT) with IMRT in five patients. The CFRT plans consisted of anterior, posterior and bilateral posterior oblique fields, while the IMRT plans consisted of either nine equispaced fields (9F), or four fields (4F) with orientations equal to the CFRT plans. IMRT plans with seven, five or three equispaced fields were also investigated in one patient. Treatment plans were compared using dose-volume histograms and normal tissue complication probabilities.Results: The 9F IMRT plan was unable to improve on the homogeneity of dose to the planning target volume (PTV), compared with the CFRT plan (dose range, 16.9+/-4.5 (1 SD) vs. 12.4+/-3.9%; P=0.06). Similarly, the 9F IMRT plan was unable to reduce the mean lung dose (11.7+/-3.2 vs. 11.0+/-2.9 Gy; P=0.2). Similar results were obtained for seven, five and three equispaced fields in the single patient studied. The 4F IMRT plan provided comparable PTV dose homogeneity with the CFRT plan (11.8+/-3.3 vs. 12.4+/-3.9%; P=0.6), with reduced mean lung dose (9.5+/-2.3 vs 11.0+/-2.9 Gy; P=0.001).Conclusions: IMRT using nine equispaced fields provided no improvement over CFRT. This was because the larger number of fields in the IMRT plan distributed a low dose over the entire lung. In contrast, IMRT using four fields equal to the CFRT fields offered an improvement in lung sparing. Thus, IMRT with a few carefully chosen field directions may lead to a modest reduction in pneumonitis, or allow tumour dose escalation within the currently accepted lung toxicity.

Optimisation of radiotherapy for carcinoma of the parotid gland: a comparison of conventional, three-dimensional conformal, and intensity-modulated techniques

Background and purpose: To compare external beam radiotherapy techniques for parotid gland tumours using conventional radiotherapy (RT), three-dimensional conformal radiotherapy (3DCRT), and intensity-modulated radiotherapy (IMRT). To optimise the IMRT techniques, and to produce an IMRT class solution.Materials and methods: The planning target volume (PTV), contra-lateral parotid gland, oral cavity, brain-stem, brain and cochlea were outlined on CT planning scans of six patients with parotid gland tumours. Optimised conventional RT and 3DCRT plans were created and compared with inverse-planned IMRT dose distributions using dose-volume histograms. The aim was to reduce the radiation dose to organs at risk and improve the PTV dose distribution. A beam-direction optimisation algorithm was used to improve the dose distribution of the IMRT plans, and a class solution for parotid gland IMRT was investigated.Results: 3DCRT plans produced an equivalent PTV irradiation and reduced the dose to the cochlea, oral cavity, brain, and other normal tissues compared with conventional RT. IMRT further reduced the radiation dose to the cochlea and oral cavity compared with 3DCRT. For nine- and seven-field IMRT techniques, there was an increase in low-dose radiation to non-target tissue and the contra-lateral parotid gland. IMRT plans produced using three to five optimised intensity-modulated beam directions maintained the advantages of the more complex IMRT plans, and reduced the contra-lateral parotid gland dose to acceptable levels. Three- and four-field non-coplanar beam arrangements increased the volume of brain irradiated, and increased PTV dose inhomogeneity. A four-field class solution consisting of paired ipsilateral coplanar anterior and posterior oblique beams (15, 45, 145 and 170o from the anterior plane) was developed which maintained the benefits without the complexity of individual patient optimisation.Conclusions: For patients with parotid gland tumours, reduction in the radiation dose to critical normal tissues was demonstrated with 3DCRT compared with conventional RT. IMRT produced a further reduction in the dose to the cochlea and oral cavity. With nine and seven fields, the dose to the contra-lateral parotid gland was increased, but this was avoided by optimisation of the beam directions. The benefits of IMRT were maintained with three or four fields when the beam angles were optimised, but were also achieved using a four-field class solution. Clinical trials are required to confirm the clinical benefits of these improved dose distributions.

Object tracking using SIFT features and mean shift

A scale invariant feature transform (SIFT) based mean shift algorithm is presented for object tracking in real scenarios. SIFT features are used to correspond the region of interests across frames. Meanwhile, mean shift is applied to conduct similarity search via color histograms. The probability distributions from these two measurements are evaluated in an expectation–maximization scheme so as to achieve maximum likelihood estimation of similar regions. This mutual support mechanism can lead to consistent tracking performance if one of the two measurements becomes unstable. Experimental work demonstrates that the proposed mean shift/SIFT strategy improves the tracking performance of the classical mean shift and SIFT tracking algorithms in complicated real scenarios.

SVM Training Phase Reduction Using Dataset Feature Filtering for Malware Detection

N-gram analysis is an approach that investigates the structure of a program using bytes, characters, or text strings. A key issue with N-gram analysis is feature selection amidst the explosion of features that occurs when N is increased. The experiments within this paper represent programs as operational code (opcode) density histograms gained through dynamic analysis. A support vector machine is used to create a reference model, which is used to evaluate two methods of feature reduction, which are 'area of intersect' and 'subspace analysis using eigenvectors.' The findings show that the relationships between features are complex and simple statistics filtering approaches do not provide a viable approach. However, eigenvector subspace analysis produces a suitable filter.

Assessing modern ground survey methods and airborne laser scanning for digital terrain modelling:A case study from the Lake District, England

This paper compares the applicability of three ground survey methods for modelling terrain: one man electronic tachymetry (TPS), real time kinematic GPS (GPS), and terrestrial laser scanning (TLS). Vertical accuracy of digital terrain models (DTMs) derived from GPS, TLS and airborne laser scanning (ALS) data is assessed. Point elevations acquired by the four methods represent two sections of a mountainous area in Cumbria, England. They were chosen so that the presence of non-terrain features is constrained to the smallest amount. The vertical accuracy of the DTMs was addressed by subtracting each DTM from TPS point elevations. The error was assessed using exploratory measures including statistics, histograms, and normal probability plots. The results showed that the internal measurement accuracy of TPS, GPS, and TLS was below a centimetre. TPS and GPS can be considered equally applicable alternatives for sampling the terrain in areas accessible on foot. The highest DTM vertical accuracy was achieved with GPS data, both on sloped terrain (RMSE 0.16. m) and flat terrain (RMSE 0.02. m). TLS surveying was the most efficient overall but veracity of terrain representation was subject to dense vegetation cover. Therefore, the DTM accuracy was the lowest for the sloped area with dense bracken (RMSE 0.52. m) although it was the second highest on the flat unobscured terrain (RMSE 0.07. m). ALS data represented the sloped terrain more realistically (RMSE 0.23. m) than the TLS. However, due to a systematic bias identified on the flat terrain the DTM accuracy was the lowest (RMSE 0.29. m) which was above the level stated by the data provider. Error distribution models were more closely approximated by normal distribution defined using median and normalized median absolute deviation which supports the use of the robust measures in DEM error modelling and its propagation. © 2012 Elsevier Ltd.

Northern peatland initiation lagged abrupt increases in deglacial atmospheric CH4

Peatlands are a key component of the global carbon cycle. Chronologies of peatland initiation are typically based on compiled basal peat radiocarbon (14C) dates and frequency histograms of binned calibrated age ranges. However, such compilations are problematic because poor quality 14C dates are commonly included and because frequency histograms of binned age ranges introduce chronological artefacts that bias the record of peatland initiation. Using a published compilation of 274 basal 14C dates from Alaska as a case study, we show that nearly half the 14C dates are inappropriate for reconstructing peatland initiation, and that the temporal structure of peatland initiation is sensitive to sampling biases and treatment of calibrated14C dates. We present revised chronologies of peatland initiation for Alaska and the circumpolar Arctic based on summed probability distributions of calibrated 14C dates. These revised chronologies reveal that northern peatland initiation lagged abrupt increases in atmospheric CH4 concentration at the start of the Bølling–Allerød interstadial (Termination 1A) and the end of the Younger Dryas chronozone (Termination 1B), suggesting that northern peatlands were not the primary drivers of the rapid increases in atmospheric CH4. Our results demonstrate that subtle methodological changes in the synthesis of basal 14C ages lead to substantially different interpretations of temporal trends in peatland initiation, with direct implications for the role of peatlands in the global carbon cycle.

Implications of Intercellular Signaling for Radiation Therapy: A Theoretical Dose-Planning Study

Purpose
Recent in vitro results have shown significant contributions to cell killing from signaling effects at doses that are typically used in radiation therapy. This study investigates whether these in vitro observations can be reconciled with in vivo knowledge and how signaling may have an impact on future developments in radiation therapy.
Methods and Materials
Prostate cancer treatment plans were generated for a series of 10 patients using 3-dimensional conformal therapy, intensity modulated radiation therapy (IMRT), and volumetric modulated arc therapy techniques. These plans were evaluated using mathematical models of survival following modulated radiation exposures that were developed from in vitro observations and incorporate the effects of intercellular signaling. The impact on dose-volume histograms and mean doses were evaluated by converting these survival levels into "signaling-adjusted doses" for comparison.
Results
Inclusion of intercellular communication leads to significant differences between the signalling-adjusted and physical doses across a large volume. Organs in low-dose regions near target volumes see the largest increases, with mean signaling-adjusted bladder doses increasing from 23 to 33 Gy in IMRT plans. By contrast, in high-dose regions, there is a small decrease in signaling-adjusted dose due to reduced contributions from neighboring cells, with planning target volume mean doses falling from 74 to 71 Gy in IMRT. Overall, however, the dose distributions remain broadly similar, and comparisons between the treatment modalities are largely unchanged whether physical or signaling-adjusted dose is compared. Conclusions Although incorporating cellular signaling significantly affects cell killing in low-dose regions and suggests a different interpretation for many phenomena, their effect in high-dose regions for typical planning techniques is comparatively small. This indicates that the significant signaling effects observed in vitro are not contradicted by comparison with clinical observations. Future investigations are needed to validate these effects in vivo and to quantify their ranges and potential impact on more advanced radiation therapy techniques.

Investigating the Potential Impact of Four-dimensional Computed Tomography (4DCT) on Toxicity, Outcomes and Dose Escalation for Radical Lung Cancer Radiotherapy

AIMS: To investigate the potential dosimetric and clinical benefits predicted by using four-dimensional computed tomography (4DCT) compared with 3DCT in the planning of radical radiotherapy for non-small cell lung cancer.

MATERIALS AND METHODS:
Twenty patients were planned using free breathing 4DCT then retrospectively delineated on three-dimensional helical scan sets (3DCT). Beam arrangement and total dose (55 Gy in 20 fractions) were matched for 3D and 4D plans. Plans were compared for differences in planning target volume (PTV) geometrics and normal tissue complication probability (NTCP) for organs at risk using dose volume histograms. Tumour control probability and NTCP were modelled using the Lyman-Kutcher-Burman (LKB) model. This was compared with a predictive clinical algorithm (Maastro), which is based on patient characteristics, including: age, performance status, smoking history, lung function, tumour staging and concomitant chemotherapy, to predict survival and toxicity outcomes. Potential therapeutic gains were investigated by applying isotoxic dose escalation to both plans using constraints for mean lung dose (18 Gy), oesophageal maximum (70 Gy) and spinal cord maximum (48 Gy).

RESULTS:
4DCT based plans had lower PTV volumes, a lower dose to organs at risk and lower predicted NTCP rates on LKB modelling (P < 0.006). The clinical algorithm showed no difference for predicted 2-year survival and dyspnoea rates between the groups, but did predict for lower oesophageal toxicity with 4DCT plans (P = 0.001). There was no correlation between LKB modelling and the clinical algorithm for lung toxicity or survival. Dose escalation was possible in 15/20 cases, with a mean increase in dose by a factor of 1.19 (10.45 Gy) using 4DCT compared with 3DCT plans.

CONCLUSIONS:
4DCT can theoretically improve therapeutic ratio and dose escalation based on dosimetric parameters and mathematical modelling. However, when individual characteristics are incorporated, this gain may be less evident in terms of survival and dyspnoea rates. 4DCT allows potential for isotoxic dose escalation, which may lead to improved local control and better overall survival.

Adaptive Bacteria Colony Picking in Unstructured Environments Using Intensity Histogram and Unascertained LS-SVM Classifier

Features analysis is an important task which can significantly affect the performance of automatic bacteria colony picking. Unstructured environments also affect the automatic colony screening. This paper presents a novel approach for adaptive colony segmentation in unstructured environments by treating the detected peaks of intensity histograms as a morphological feature of images. In order to avoid disturbing peaks, an entropy based mean shift filter is introduced to smooth images as a preprocessing step. The relevance and importance of these features can be determined in an improved support vector machine classifier using unascertained least square estimation. Experimental results show that the proposed unascertained least square support vector machine (ULSSVM) has better recognition accuracy than the other state-of-the-art techniques, and its training process takes less time than most of the traditional approaches presented in this paper.

Malware detection: program run length against detection rate

N-gram analysis is an approach that investigates the structure of a program using bytes, characters or text strings. This research uses dynamic analysis to investigate malware detection using a classification approach based on N-gram analysis. A key issue with dynamic analysis is the length of time a program has to be run to ensure a correct classification. The motivation for this research is to find the optimum subset of operational codes (opcodes) that make the best indicators of malware and to determine how long a program has to be monitored to ensure an accurate support vector machine (SVM) classification of benign and malicious software. The experiments within this study represent programs as opcode density histograms gained through dynamic analysis for different program run periods. A SVM is used as the program classifier to determine the ability of different program run lengths to correctly determine the presence of malicious software. The findings show that malware can be detected with different program run lengths using a small number of opcodes

N-gram density based malware detection

N-gram analysis is an approach that investigates the structure of a program using bytes, characters or text strings. This research uses dynamic analysis to investigate malware detection using a classification approach based on N-gram analysis. The motivation for this research is to find a subset of Ngram features that makes a robust indicator of malware. The experiments within this paper represent programs as N-gram density histograms, gained through dynamic analysis. A Support Vector Machine (SVM) is used as the program classifier to determine the ability of N-grams to correctly determine the presence of malicious software. The preliminary findings show that an N-gram size N=3 and N=4 present the best avenues for further analysis.

Partial Palmprint Matching Using Invariant Local Minutiae Descriptors

In forensic investigations, it is common for forensic investigators to obtain a photograph of evidence left at the scene of crimes to aid them catch the culprit(s). Although, fingerprints are the most popular evidence that can be used, scene of crime officers claim that more than 30% of the evidence recovered from crime scenes originate from palms. Usually, palmprints evidence left at crime scenes are partial since very rarely full palmprints are obtained. In particular, partial palmprints do not exhibit a structured shape and often do not contain a reference point that can be used for their alignment to achieve efficient matching. This makes conventional matching methods based on alignment and minutiae pairing, as used in fingerprint recognition, to fail in partial palmprint recognition problems. In this paper a new partial-to-full palmprint recognition based on invariant minutiae descriptors is proposed where the partial palmprint’s minutiae are extracted and considered as the distinctive and discriminating features for each palmprint image. This is achieved by assigning to each minutiae a feature descriptor formed using the values of all the orientation histograms of the minutiae at hand. This allows for the descriptors to be rotation invariant and as such do not require any image alignment at the matching stage. The results obtained show that the proposed technique yields a recognition rate of 99.2%. The solution does give a high confidence to the judicial jury in their deliberations and decision.

Detecting obfuscated malware using reduced opcode set and optimised runtime trace

The research presented, investigates the optimal set of operational codes (opcodes) that create a robust indicator of malicious software (malware) and also determines a program’s execution duration for accurate classification of benign and malicious software. The features extracted from the dataset are opcode density histograms, extracted during the program execution. The classifier used is a support vector machine and is configured to select those features to produce the optimal classification of malware over different program run lengths. The findings demonstrate that malware can be detected using dynamic analysis with relatively few opcodes.