- Giveaway: Leo Hollis’s ‘The Stones of London’
- Microwave-assisted Extraction for Bioactive Compounds
In the healthy human stomach, slow wave activity is highly organized. Gastric motility disorders are associated with dysrhythmias. While ablation is widely used to treat cardiac dysrhythmias, this approach has yet to be trialed in the stomach. In this study, radiofrequency RF ablation was applied in pig stomachs in vivo to create targeted electrical conduction blocks.
Termination of slow wave propagation at ablation sites was confirmed by a decrease in extracellular slow wave amplitude from 1. The use of high-resolution electrical mapping can now be employed to investigate ablation as a potential therapy for gastric dysrhythmias in motility disorders. Keywords: Ablation systems and technologies , Image-guided devices - RF and microwave ablation , Computer modeling for treatment planning Abstract: Abstract—This paper introduces a novel technology for treating early-stage NSCL cancer using an endobronchial approach via a flexible radiofrequency ablation RFA catheter.
Methods — The RFA system consisted of an ablation catheter, radiofrequency generator, irrigation pump for infusion of hypertonic saline HS and a laptop.
Giveaway: Leo Hollis’s ‘The Stones of London’
The catheter carried an occlusion balloon, a 5 mm long RF electrode, with irrigation holes, and a 1 mm long electrode for bipolar impedance measurements. The OD was 1. Two swine were then treated at 60 W for 15 min per bronchus. Several bronchi were involved. Animals were survived for six weeks. Results — Bench studies showed that 60 W, 7 — 15 min ablations can produce large ablation volumes, in excess of 3 — 4 cm diameter. In the chronic animal study, no clinically adverse events occurred.
There was no evidence of hemorrhage. Animals vital signs, breathing patterns and their behavior were normal throughout the six-week period.
The dimensions of coagulative necrotic sequestra met expectations, as at six weeks they exceeded volumes corresponding to 2 cm nodules, the size of tumors normally addressed in the peripheral lung by localized therapy. Conclusion — This therapy showed promise.
Appropriate energy settings combined with suitable treatment locations safely produced large ablation volumes of uniform thermal coagulative necrosis. Further studies may develop it into a mainstream therapy for NSCL cancer. Keywords: Ablation, Cancer, Catheter. Keywords: Magnetic resonance imaging - Cardiac imaging , Image segmentation , Cardiac imaging and image analysis Abstract: Machine learning algorithms enable automatic analysis of multidimensional data from medical imaging examinations and other clinical information.
These methods can be combined with atlas-based analysis of heart geometry and function to give morphometric indices which are optimally associated with clinical factors.
We describe methods which can be used to characterize patients with heart failure according to a rich set of morphological features which may give insight into the underlying pathological processes. Keywords: Coronary blood flow , Coronary artery disease , Cardiac catheterization Abstract: Percutaneous coronary intervention PCI guidance has evolved from a subjective, visually-guided approach to a more objective, physiology-guided one.
Invasive guidewire-based physiological measurements have become on-the-spot, table-side tools for clinical decision making. It follows that the technology involved has progressed to allow more robust, high fidelity measurements to be made. A systematic review of the literature was conducted and landmark papers in coronary physiology identified. Major landmark trials in the last 2 decades have confirmed the utility of coronary blood flow and pressure measurements in assessing the functional importance of coronary artery stenoses, and in predicting the clinical outcomes of patients with and without PCI.
Further refinements in coronary physiology assessment include resting indices such as the instantaneous wave free ratio iFR , which negate the use of hyperaemic agents, thus reducing procedure time and improving patient comfort.
The success and global uptake of iFR has led to the proliferation of a host of other resting indices with similar performance and outcomes. Invasive coronary physiology assessment provides objective, reliable, reproducible assessments of coronary artery disease severity. Having a simple bedside tool that aids decision making helps physicians make the correct clinical decisions for each patient. Refinements in guidewire technology will improve ease of use for the interventional cardiologist, whilst reducing the potential of harm to the patient.
Keywords: Vascular mechanics and hemodynamics - Vascular Hemodynamics , Vascular mechanics and hemodynamics - Vascular mechanics , Vascular mechanics and hemodynamics - Vascular Disease Abstract: We developed a vessel length-based fractional flow reserve FFR simulation method in patient-specific models and compared the results with clinical results. In this method, vessel lengths are used to identify simulation parameters. Then, we evaluate its clinical diagnostic performance in multi-center study. Keywords: Coronary blood flow , Coronary artery disease , Vascular mechanics and hemodynamics - Vascular Hemodynamics Abstract: Coronary artery fractional flow reserve FFR , the ratio of distal to proximal pressures in a stenotic lesion, has been shown to confer clear benefit for guiding percutaneous coronary intervention PCI.
However, FFR requires pressure to be measured invasively, which is a barrier to wider use of the method. A noninvasive method to quantify FFR is needed. We described methods which can be used to characterize the coronary plaque morphology and to derive FFR from computed tomography coronary angiography CTCA with reduced-order computational fluid dynamic CFD algorithm. We studied the diagnostic performance of the method for diagnosing ischemic lesion with reference to the gold standard of invasive FFR in human subjects.
The results demonstrated better accuracy than anatomical assessment. Coronary plaque morphology with reduced order computational fluid dynamics-based FFR improved diagnostic accuracy and can reduce the risks associated with invasive coronary angiography. Keywords: Magnetic resonance imaging - Cardiac imaging , Magnetic resonance imaging - Diffusion tensor, diffusion weighted and diffusion spectrum imaging , Cardiac imaging and image analysis Abstract: Cardiac microstructure critically underlies normal cardiac performance. Herein, we describe recent advances in cDTI that enable evaluation of myocardial microstructure and microstructural dynamics in vivo.
Keywords: Magnetic resonance imaging - Cardiac imaging , Cardiac imaging and image analysis , Functional image analysis Abstract: Heart failure is a chronic disease that causes repeat hospitalizations, reduced quality of life and increased mortality, and is a major global healthcare burden. Cardiac imaging facilitates heart failure diagnosis, elucidation of the etiology, monitoring of progression and prognostication.
Comprehensive assessment of myocardial tissue characteristics as well as systolic and diastolic functional parameters in the ventricles and atria are needed to diagnose heart failure, especially in heart failure with preserved ejection. Cardiac magnetic resonance CMR is an imaging modality that yields high-quality images of all heart chambers, and is the reference standard for measurement of left ventricular ejection fraction. However, conventional CMR analyses fail to exploit the rich 4D spatiotemporal information contained in the CMR image dataset, which we believe can be unlocked using the appropriate methods for comprehensive quantitation of left and right ventricular, as well as atrial systolic and diastolic functions.
We pioneered computational post-processing techniques that can quantitate regional ventricular function as well as measure phasic atrial strains and their corresponding strain rates. The proof-of-concept and validation of these novel parameters, as well as relevant clinical applications, will be discussed. Our results show concordance between the resultant activation maps and consistent HRF shapes for most of the subjects, suggesting that CSC can be used as a tool for the detection of reliable events in the EEG. Exploring the structural and functional connections and interactions between brain regions is beneficial to detect MCI.
For this reason, we propose a new model for automatic MCI diagnosis based on this information. Firstly, a new functional brain network estimation method is proposed. Self-calibration is introduced using quality indicators, and functional brain network estimation is performed at the same time. Then we integrate the functional and structural connected neuroimaging patterns into our multi-task learning model to select informative feature. By identifying synergies and differences between different tasks, the most discriminative features are determined.
Finally, the most relevant features are sent to the support vector machine classifier for diagnosis and identification of MCI. At the same time, compared with the existing classification methods, the proposed method achieves relatively high classification accuracy. In addition, it can identify the most discriminative brain regions.
These findings suggest that our approach not only improves classification performance, but also successfully identifies important biomarkers associated with disease. Keywords: Multimodal imaging , Brain imaging and image analysis , Functional image analysis Abstract: Perceptual choice is affected not only by the stimulus evidence present in the decision alternatives, but also by the propensity to choose one alternative over another.
In the drift-diffusion model DDM , such bias can be expressed either as a change in drift rate or a change in starting point of the decision process.
Microwave-assisted Extraction for Bioactive Compounds
Car vs. House visual categorization task. We spatially and temporally dissociated the neural correlates underlying the face decision bias as a function of stimulus evidence. Firstly, by fitting the DDM, we quantitatively showed that the change in drift rate best accounted for the decision bias towards faces when sensory evidence was abundant, whereas the shift in starting point best explained the bias effect when inadequate sensory evidence was present. Secondly, we used the EEG single-trial variability to temporally identify brain regions modulated by the two sets of subject-wise bias parameters in the fMRI analysis.
Imaging results showed a double dissociation of the bias effects in space and in time as the level of sensory evidence changed: bias in drift rate correlated only with an early sensory network while bias in starting point activated a distributed late decision-related network. Keywords: Brain imaging and image analysis , Functional image analysis , Multivariate image analysis Abstract: Independent component analysis ICA , as a data driven method, has shown to be a powerful tool for functional magnetic resonance imaging fMRI data analysis.
One drawback of this multivariate approach is, that it is naturally not convenient for analysis of group studies. Therefore various techniques have been proposed in order to overcome this limitation of ICA. An empirical mode decomposition EMD is used to generate reference signals in a data driven manner, which can be incorporated into a constrained version of ICA cICA , what helps to overcome the inherent ambiguities. The results of the proposed workflow are then compared to those obtained by a widely used group ICA approach. It is demonstrated that intrinsic modes, extracted by EMD, are suitable to serve as references for cICA to obtain typical resting state patterns, which are consistent over subjects.
This novel processing pipeline makes it transparent for the user, how comparable activity patterns across subjects emerge, and also the trade-off between similarity across subjects and preserving individual features can be well adjusted and adapted for different requirements in the new work-flow. Keywords: Magnetic resonance imaging - Diffusion tensor, diffusion weighted and diffusion spectrum imaging , Magnetic resonance imaging - MR neuroimaging , Brain imaging and image analysis Abstract: Cerebral microbleeds CMBs , a common manifestation of mild traumatic brain injury mTBI , have been sporadically implicated in the neurocognitive deficits of mTBI victims but their clinical significance has not been established adequately.
CMBs were segmented automatically from susceptibility-weighted imaging SWI by leveraging the intensity gradient properties of SWI to identify CMB-related hypointensities using gradient-based edge detection. A detailed diffusion magnetic resonance imaging dMRI atlas of WM was used to segment and cluster tractography streamlines whose prototypes were then identified. The correlation coefficient was calculated between A FA values at vertices along streamline prototypes and B topological along-streamline distances between these vertices and the nearest CMB.
Across subjects, the CMB identification approach achieved a sensitivity of The correlation coefficient was found to be negative and, additionally, statistically significant for Multi-shell diffusion MRI is able to greatly increase specificity by concomitantly exploring multiple diffusion timescales.
If multi-shell acquisition is combined with an exploration of different diffusion times, diffusion data allows the estimation of sophisticated compartmental models, which provide greatly enhanced specificity to the presence of different tissue sub-compartments, as well as estimates of intra-voxel axonal diameter distributions. In this paper, we apply a multiple-b-value, high angular resolution multi-shell diffusion MRI protocol with varying diffusion times to a cohort of multiple sclerosis MS patients and compare them to a population of healthy controls.
By fitting the AxCaliber model, we are able to extract indices for axonal diameter across the whole brain. We show that MS is associated with widespread increases of axonal diameter and that our axonal diameter estimation provides the highest discrimination power for local alterations in normal-appearing white matter in MS compared to controls. AxCaliber has the potential to disentangle microstructural alterations in MS and holds great promises to become a sensitive and specific non-invasive biomarker of irreversible disease progression.
Keywords: Vascular mechanics and hemodynamics - Arterial pressure in cardiovascular disease , Vascular mechanics and hemodynamics - Vascular Hemodynamics , Cardiovascular, respiratory, and sleep devices - Nearables Abstract: We developed an iPhone X application for cuff-less and calibration-free measurement of systolic and diastolic blood pressure. We tested the application, along with a FDA-cleared finger cuff device, against an arm cuff device in human subjects.
The application was almost as accurate as the finger cuff device. Keywords: Cardiovascular and respiratory signal processing - Blood pressure measurement , Cardiovascular, respiratory, and sleep devices - Wearables , Vascular mechanics and hemodynamics - Pulse wave velocity Abstract: The performance of the Aktiia OBPM algorithms to measure blood pressure at the wrist was investigated in this study.
For two months, six volunteers recorded blood pressure values at the arm using a brachial cuff. Simultaneously, optical signals at the wrist were recorded using off-the-shelf PPG sensors. At the end of the study, the optical signals were processed by the Aktiia OBPM algorithms to generate blood pressure estimations. The algorithms were initialized using the first brachial blood pressure value recorded at the inclusion day. Keywords: Cardiovascular and respiratory signal processing - Blood pressure measurement , Cardiovascular and respiratory signal processing - Heart Rate and Blood Pressure Variability , Cardiovascular and respiratory system modeling - Cardiac models Abstract: Based on pulse wave analysis, we have developed a new technique to monitor the changes in blood pressure using a photoplethysmography PPG sensor.
This technique extracts physiologically motivated features from the PPG waveform and combines the features to estimate systolic blood pressure SBP and diastolic blood pressure DBP individually. The proposed technology has been validated in accordance with IEEE standard This technology performs a local assessment of incremental pulse wave velocity PWV and arterial wall dynamics in a simultaneous fashion, for direct evaluation of BP without any calibration.
Methodological considerations concerning this technique were identified and addressed for achieving reliable measurements of BP parameters and waveform from the carotid artery. As part of a small clinical study, we discuss the effects of hypertensive medication, a commonly overlooked factor which may affect diagnostic results. We conclude that the proposed GMM-HMM estimation method is a very promising method improving the accuracy of automated non-invasive measurement of blood pressure.
Keywords: Signal pattern classification , Data mining and processing in biosignals Abstract: This study aimed at evaluating whether people with a normal cognitive function can be discriminated from subjects with a mild impairment of cognitive function based on a set of acoustic features derived from spontaneous speech. Linear mixed model analyses were performed to select the features able to significantly distinguish between groups.
The leave-one-out cross validation was used for testing and the classifier accuracy was computed. When the voice features were used alone, an overall classification accuracy of 0. When age and years of education were additionally used, the overall accuracy increased up to 0. These performances were lower than the accuracy of 0. However, in that study the classification was based on several tasks, including more cognitive demanding tasks. Our results are encouraging because acoustic features, derived for the first time only from an ecologic continuous speech task, were able to discriminate people with a normal cognitive function from people with a mild cognitive decline.
This study poses the basis for the development of a mobile application performing automatic voice analysis on-the-fly during phone calls, which might potentially support the detection of early signs of functional cognitive decline. Keywords: Signal pattern classification , Time-frequency and time-scale analysis - Empirical mode decomposition in biosignal analysis Abstract: Cough is a common symptom of numerous respiratory diseases. In certain cases, such as asthma and COPD, early identification of coughs is useful for the management of these diseases.
This paper presents an algorithm for automatic identification of cough events from acoustic signals. The algorithm is based on only four features of the acoustic signals including LPC coefficient, tonality index, spectral flatness and spectral centroid with a logistic regression model to label sound segments into cough and non-cough events. The algorithm achieves sensitivity of of Its high performance despite its small size of feature-space demonstrate its potential for use in remote patient monitoring systems for automatic cough detection using acoustic signals.
Keywords: Nonlinear dynamic analysis - Biomedical signals , Physiological systems modeling - Multivariate signal processing , Physiological systems modeling - Signal processing in physiological systems Abstract: One of the primary difference of mankind from other species is his ability to communicate verbally. Our brain upon framing a sentence, coordinates with the oro-pharyngeal-laryngeal muscle groups to produce the speech with the help of vocal cord and mouth aperture.
However, some individuals due to congenital or illness, may loose their ability to speak in spite of their brain framing speech. Research on speech restoration through brain computer interface BCI is still at an early stage. Through this study, we have explored the regression between the chaos parameters of acoustic signal and electroencephalography EEG signal for different vowels chosen from International Phonetic Alphabets IPA. The vowels were categorised into two categories, namely, soft vowels and diphthongs. We have selected the EEG channels based on their higher contribution towards the first principle component.
Goodness of fit parameters were evaluated for the regression analysis to explore the most suitable chaos parameter. Keywords: Signal pattern classification , Data mining and processing in biosignals , Data mining and processing - Pattern recognition Abstract: Schizophrenia and depression are the two most common mental disorders associated with negative symptoms that contribute to poor functioning and quality of life for millions of patients globally. This study is part of a larger research project. The overall aim of the project is to develop an automated objective pipeline that aids clinical diagnosis and provides more insights into symptoms of mental illnesses.
In our previous work, We have analyzed non-verbal cues and linguistic cues of schizophrenic patients. In this study, we extend our work to include depressive patients. Using Natural Language Processing techniques, we extract verbal features, both dictionary-based and vector-based, from participants' interviews that were automatically transcribed.
We also extracted conversational, phonatory, articulatory and prosodic features from the interviews to understand the conversational and acoustic characteristics of schizophrenia and depression. Our analysis also revealed significant linguistic and non-verbal vocal-based differences that are potentially symptomatic of schizophrenia and depression respectively. Keywords: Physiological systems modeling - Signal processing in physiological systems , Signal pattern classification Abstract: Current research in the emotion recognition field is exploring the possibility of merging the information from physiological signals, behavioral data, and speech.
Electrodermal activity EDA is amongst the main psychophysiological arousal indicators. Nonetheless, it is quite difficult to be analyzed in ecological scenarios, like, for instance, when the subject is speaking. On the other hand, speech carries relevant information of subject emotional state and its potential in the field of affective computing is still to be fully exploited.
In this work, we aim at exploring the possibility of merging the information from electrodermal activity EDA and speech to improve the recognition of human arousal level during the pronunciation of single affective words. Unlike the majority of studies in the literature, we focus on speakers' arousal rather than the emotion conveyed by the spoken word.
Specifically, a support vector machine with recursive feature elimination strategy SVM-RFE is trained and tested on three datasets, i. The six selected features by the RFE procedure will be used for the development of a future multivariate model of emotions. These are segmented into squiggle representations of the molecule. It has been suggested that applying dynamic time warp Barycentre Averaging DBA to multiple noisy squiggles can generate a lower noise, less-distorted, consensus signal that retains the key squiggle characteristics that would be distorted by other averaging approaches.
We discuss experimental results obtained when developing DBA consensus signals from squiggles produced by an Oxford MinION nano-sequencer squiggle convertor during an Enolase study. Metrics are proposed to identify differences between the known gold standard and consensus signals, and the level of self-consistency between consensus signals developed from noisy squiggles with different length distortions.
A number of location-specific differences between the gold and consensus squiggles were identified. Keywords: Bioinformatics - Bioinformatics for health monitoring , Bioinformatics - Computational modeling and simulations in biology, physiology and medicine , General and theoretical informatics - Algorithms Abstract: This paper develops a patient-specific model for the Debye parameters of human blood based on hemoglobin content.
Blood samples were collected from patients visiting the University Hospital, with both permittivity measurements and standard hematological analysis performed on each blood draw. The complete blood count of each sample provided information on the hemoglobin concentration of each sample; in total there were 73 distinct hemoglobin concentrations reported. An iterative process was used to find patient-specific, based on hemoglobin content, Debye parameters.
First, a two-stage genetic algorithm was used to solve for the parameters of a two-pole Debye model based on the mean-blood properties. Then, a modified two-pole Debye model incorporating hemoglobin information was developed, and those parameters were solved for using the same two-stage genetic algorithm. The patient-specific model has a mean-fractional error across all 73 samples of 3. This work demonstrates the range in the dielectric properties of human blood samples and highlights the need for incorporating patient-specific information when using the Debye parameters to model the dielectric properties of human blood.
Keywords: Bioinformatics - Integration of multi-modality omic data , Bioinformatics - High throughput —omic genomics, proteomics, metabolomics, lipidomics, and metagenomics data analytics for precision health , Bioinformatics - Computational systems biology Abstract: Recent advancement of omic technologies provides researchers with opportunities to search for disease biomarkers at the systems level.
However, selection of biomarker candidates from a large number of molecules involved at various layers of the biological system is challenging. In this paper, we propose multi-omic integrative analysis MOTA , a network-based method that uses information from multi-omic data to identify candidate disease biomarkers. We evaluated the performance of MOTA in selecting disease-associated molecules from four sets of multi-omic data representing three cohorts of hepatocellular carcinoma HCC cases and patients with liver cirrhosis.
The results demonstrate that MOTA leads to selection of more biomarker candidates that shared by two different cohorts compared to traditional statistical methods. Also, the networks constructed by MOTA allow users to investigate biological significance of the selected biomarker candidates. The introduction of the neuro-robotics field allows a mix of different disciplines to inter-collate and produce actual results that could be considered outputs of a science-fiction novel 20 twenty years ago. In the present work, we attempt to present an example of how a robotic entity can move in an environment full of obstacles, by regulating its behavior so as to allow a decision based on rewards and penalties experiences.
Examples of the robotic behavior, running on a virtual environment are presented, along with a discussion of its different possibilities expressed as a penalty function for the behavior of the robot. Keywords: Bioinformatics - Gene expression pattern recognition , Bioinformatics - High throughput —omic genomics, proteomics, metabolomics, lipidomics, and metagenomics data analytics for precision health Abstract: Colorectal cancer is one of the most common cancers with the second highest mortality rate in the world.
The microarray can be used to collect gene expression alteration information from many tissue samples that will be useful to understand colorectal cancer from the molecular level. However, the mechanism behind the progression from normal to cancer is not fully understood.
Here, a cross-platform comparison among three common microarray platforms Affymetrix, Agilent, and Illumina was applied. As results, we found a significant correlation of purine metabolism and p53 signaling pathway role in colorectal cancer progression. Purine metabolism can control the regulation of cell proliferation which involve hydro-lyase activity on organelle lumen.
Meanwhile, genetic alterations in p53 signaling pathways could control some hallmarks of cancer. These two terms might play important roles in inducing normal colorectal cells into cancer. Keywords: General and theoretical informatics - Graph-theoretical applications , Bioinformatics - Bioinformatics databases , Imaging Informatics - Image rendering, reconstruction and enhancement Abstract: We construct a graph representation for the topology and geometry of the vasculature presenting across the whole mouse brain dataset: Knife-Edge Scanning Microscope Brain Atlas India Ink.
We use our graph representation to calculate preliminary estimates of the average radius as 2. We then isolate a posterior cerebral region, derive its graph representation, and then import that representation to a Neo4j graph database. We then detail how researchers can query this database online to isolate specific vascular networks for further analysis and reconstruction. Keywords: Data-driven modeling , Models of organ physiology Abstract: We have created a model of systemic burn pathophysiology by incorporating a mathematical model of acute inflammation within the BioGears Engine.
This model produces outputs consistent with burns of varying severities and leverages existing BioGears functionality to simulate the effect of treatment on virtual patient outcome. The model performs well for standard resuscitation scenarios and we thus expect it to be useful for educational and training purposes.
Keywords: Data-driven modeling , Systems biology and systems medicine - Modeling of metabolic networks , Model building - Algorithms and techniques for systems modeling Abstract: Modelling of the gluco-regulatory system in response to an oral glucose tolerance test OGTT has been the subject of research for decades.
This paper presents an adaptation to the well-established oral minimal model that is identifiable from glucose data only and is able to capture the dynamics of glucose following both OGTT and mixed meal consumption. The model is in the form of low-dimensional differential equations with a recently introduced input function consisting of Gaussian shaped components. It was identified from glucose data recorded from six subjects with prediabetes, type 2 diabetes and without diabetes under controlled conditions.
The inferred parameters of the model are shown to have physiological meaning and produce realistic steady state behavior. This model may be useful in the development of clinical advisory tools for the treatment and prevention of type 2 diabetes mellitus. Keywords: Translational biomedical informatics - Decision making , Translational biomedical informatics - Mining clinical data , Data-driven modeling Abstract: Severe Disorders of Consciousness DoC are generally caused by brain trauma, anoxia or stroke, and result in conditions ranging from coma to the confused-agitated state.
Prognostic decision is difficult to achieve during the first year after injury, especially in the pediatric cases. Nevertheless, prognosis crucially informs rehabilitation decision and family expectations. We compared four multi-class machine learning classification approaches for the prognostic decision in pediatric DoC. We identified domains of a neurobehavioral assessment tool, Level of Cognitive Functioning Assessment Scale, mostly contributing to decision in a cohort of cases. We showed the possibility to generalize to new admitted pediatric cases, thus paving the way for real employment of machine learning classifiers as an assistive tool to prognostic decision in clinics.
Engineering has supplemented this effort via the development of technology, e. In recent times, engineering and the physical sciences have positioned themselves as approaches on par with the traditional basic sciences to tackle the study of cancer. Mathematical modeling and computational simulation have become key elements of this engineering-focused effort, evaluating the growth of tumors and their response to therapy as problems that could benefit from a systems analysis perspective.
Building upon previous work in this field, here is developed a modeling framework to help evaluate the response of tumors to the combination of chemotherapy and immunotherapy, focusing on non-small cell lung cancer NSCLC. With system parameters set with patient tumor-specific parameters, the longer term goal of this work is to advance personalized cancer treatment. Keywords: Systems modeling - Decision making , Translational biomedical informatics - Decision making Abstract: While the benefits of glycemic control for critically ill patients are increasingly demonstrated, the ability to deliver safe, effective control to intermediate target ranges is widely debated due to the increased risk of hypoglycemia.
These interim results show the possibility to achieve safe, effective control for all patients using STAR, and suggest glycemic control to lower targets could be beneficial. It causes a high financial burden for patients and their families. For effective treatment of AD, it is important to identify the AD progression of clinical disease over time.
As the cognitive scores can effectively indicate the disease status, the prediction of the scores using the longitudinal magnetic resonance imaging MRI data is highly desirable. In this paper, we propose a joint learning and clinical scores prediction method for AD diagnosis via longitudinal MRI data. Thanks Meter : 1, By Patrick. Senior Member. Thanks Meter : Join Date: Joined: May Join Date: Joined: Jun Thanks Meter : 2, Join Date: Joined: Mar Join Date: Joined: Dec Join Date: Joined: Nov Just askin if multi dpi is possible?
Join Date: Joined: Jan Thanks Meter : 13, Join Date: Joined: Apr The UN3, does not need to apply all that fixes on second post? Does this rom support multi dpi? Subscribe to Thread Page of First Last. Posting Quick Reply - Please Wait. Galaxy Note 3 Android Development. Android Apps and Games. This point is part of the deeper logic of the entire debate: the relationship between two men or two women is equivalent anthropologically to a relationship between a man and woman precisely because the sexes are essentially the same anthropologically.
The sexes differ only in outward, biological aspects. As Perry concludes,. Again, extensive expert testimony was offered to support this proposition, while hardly any expert testimony was offered for the opposite viewpoint. According to Perry , the argument that having both a mother and father is optimal implies also a return to the legal differentiation between the roles of husband and wife under the universally rejected common law doctrine of coverture.
But the courts have rejected the idea that simple moral disapproval of the majority can suffice as a legitimate basis for state laws limiting fundamental rights. Rather, state laws must be rationally related to a legitimate state purpose, and mere moral disapproval cannot serve as such a purpose. This limitation allows them to say that they are not mandating a moral position, but only making a judgment about what the law requires.
The courts seem, therefore, to offer a kind of settlement of the issue, by means of the distinction between the public and the private. It would have us suppose that tolerance means governmental neutrality to two positions, a neutrality that would leave in place a kind of modus vivendi between irreconcilable worldviews.
The question then is whether tolerance really can be thought of in this way, or whether it does not slide into another sense of tolerance, one which is thoroughly moral. This latter would see tolerance not as an agreement to disagree for practical and political reasons, but as signifying an imperative for the acceptance of diverse views and ways as equally valid. This second version of tolerance, then, offers a standard for judgment concerning the proper disposition one has toward all others within society.
Anyone who does not accept this moral standard sets himself beyond the pale of legitimate public discourse. This is because tolerance in the first sense can only be an illusion in issues that involve beliefs about vital human matters. These are matters that necessarily involve our deepest convictions about what humanity is. Disagreement on such points cannot help but touch on the foundations of culture and society. In a moment we will see that an anthropological shift is underway.
But bigoted public arguments are in fact immoral public arguments, and this means that the private position will always be at least publically immoral. But can there be a position that is publically immoral and yet privately moral? In short, the tolerance that really is proffered is provisional and contingent, tailored to accommodate what is conceived as a significant but shrinking segment of society that holds a publically unacceptable private bigotry.
Where over time it emerges that this bigotry has not in fact disappeared, more aggressive measures will be needed, which will include more explicit legal and educational components, as well as simple ostracism. That would be only a positivistic and finally moralistic interpretation. Rather, Socrates suggests a deeper point, viz. Theories of law, legal systems, and particular laws, precisely in falling short of the fullness of the true or the just, nevertheless always express or mediate what a given culture or society thinks is true, even when the legal order outwardly rejects any such pretentions.
In other words, law always implies indeed, cannot avoid implying a truth claim about the human person. Classical notions of law tend to be clear about this point. They begin with the basic human elements of inclination or desire and a primitive knowledge of the good. In part, this desire and primitive knowledge of the good is rooted in our embodiedness. Our desire for fully human life and love can only be for life and love as expressed and experienced by living, embodied beings. As such, this beginning point for law presupposes a robust anthropology. Not only is the body in part the source of desires that make reason practical, and on that basis a source of law, it also serves in its very visibility as a sign of human origins and destiny.
It therefore serves as support and guidance to help us to be human in the fullest sense, however infinitely varied the instantiation of our lives might be. According to this classical approach, then, the truth claims about ultimates — such as the natures of the person, the body and physicality generally, freedom, and society — are fairly manifest.
The legal developments we have been discussing also mediate a claim about what is, although the two courts would seem to believe they are doing no such thing. It is these tacit truth claims about the human person that nevertheless dictate the sort of rationality thought to be coherent for legal authority. Of course, these implicit truth claims do not come out of a void. Rather, they represent the general outlook of deep currents in modern thought and therefore tendencies whose roots are centuries old. Since we do not make the natural beings, they are, strictly speaking, unintelligible.
According to Hobbes, this fact is perfectly compatible with the possibility of natural science. But it leads to the consequence that natural science is and will always remain fundamentally hypothetical. Yet this is all we need in order to make ourselves masters and owners of nature. Still, however much man may succeed in his conquest of nature, he will never be able to understand nature. There is no natural harmony between the human mind and the universe. But wisdom cannot be free construction if the universe is intelligible. Man can guarantee the actualization of wisdom, not in spite of, but because of, the fact that the universe is unintelligible.
Man can be sovereign only because there is no cosmic support for his humanity. He can be sovereign only because he is absolutely a stranger in the universe. He can be sovereign only because he is forced to be sovereign. Since the universe is unintelligible and since control of nature does not require understanding of nature, there are no knowable limits to his conquest of nature.
This striking passage captures an important ambiguity at the heart of the modern project. The new form of knowing and reasoning Strauss describes tends by its very logic toward a constructive and technical approach to the world. The knowable is the makeable, according to the formula verum quia faciendum. But to be entirely free in this regard, the world must be drained of its inherent meaningfulness.
Knowledge and reason concern not things in themselves but their mechanical properties, their external relations, extension, mass, force, etc. The implication for freedom and intellect, then, is that they are something set apart from the physicality even of the body. But where freedom is set aside from reality as given, it becomes indifferent freedom, freedom without interior ordination, freedom without a given end; where intellect is set aside from material reality, it views the world as only an object with its mechanical functionality and exterior and purely efficient causality.
This exaltation of freedom is matched, however, by an angst concerning its possibility in a world thought of in mechanistic terms. Hence, we find an oscillation between absolute freedom as the radical source of human dignity and a despairing doubtfulness of the concrete possibility of that freedom in the real world. This oscillation is well represented in a passage from Canadian philosopher George Grant:. We assert 'scientifically' that human conduct can be absolutely predicted and therefore controlled; as individuals we believe ourselves to be free in the most absolute sense, as the makers of our own selves and our own values.
The body is unavoidably part of the cosmos and participates in its mechanical properties. Insofar as physicality is seen as a threat to freedom, no part of it could threaten more than the body itself, which not only operates beyond and outside our free acts but also — in its very visibility and personal recognizability — situates and determines personal identity.
The body is both part of the heteronomous world of mechanism, and is also the expression of personal identity to the human community as a whole. Progress would ultimately need both to liberate the body by technical means from its limitations and defects i. Legal Reasoning These developments of course have had profound implications for the deep structure of public and legal reason.
Statements of Benedict XVI in an address to the German Bundestag are helpful in pinpointing some of these implications. He begins by noting that unlike most great religions Christianity has never claimed that revelation is or should be a direct source of civil law. A positivist conception of nature as purely functional, as the natural sciences consider it to be, is incapable of producing any bridge to ethics and law, but once again yields only functional answers.