Miracle-dz/UniFAR-FTUs huggingface dataset:
A multiplexed marker-based algorithm for diagnosis of carcinoma of unknown primary using circulating tumor cells

Real-time, single-cell multiplex immunophenotyping of circulating tumor cells (CTCs) is hypothesized to inform diagnosis of tissue of origin in patients with carcinoma of unknown primary (CUP). In 20 to 50% of CUP patients, the primary site remains unidentified, presenting a challenge for clinicians in diagnosis and treatment. We developed a post-CellSearch CTC assay using multiplexed Q-dot or DyLight conjugated antibodies with the goal of detecting multiple markers in single cells within a CTC population. We adapted our approach to size-based CTC enrichment protocols for capturing CTCs and subsequent immunofluorescence (IF) using a minimal set of markers to predict the primary sites for common metastatic tumors. The carcinomas are characterized with cytokeratin 7 (CK7), cytokeratin 20 (CK20), thyroid transcription factor 1 (TTF-1), estrogen receptor (ER) or prostate-specific antigen (PSA. IF has been optimized in cultured tumor cells with individual antibodies, then with conjugated antibodies to form a multiplex antibody set. With IF, we evaluated antibodies specific to these 5 markers in lung, breast, colorectal, and prostate cancer cell lines and blood from metastatic prostate and breast cancer patients. This advanced technology provides a noninvasive, diagnostic blood test as an adjunct to routine tissue biopsy. Its further implementation requires prospective clinical testing.
Interpersonal processes and self-injury

Most interventions in health and social care settings reside within a therapeutic relationship. However if the staff member is experiencing difficult emotional reactions or thoughts this can interfere with the process of caring or helping. Staff and client perspectives are split into different articles by different authors, or within different chapters of a book. This has reinforced the difference between clients and staff. Arguably professionals are increasingly viewed as human beings with their own reactions to events, rather than detached unemotional helpers. However, the reactions of staff are often not linked to clients. Within the literature on self-injury this has not been clearly described. This thesis makes an original contribution to recognising the interpersonal processes involved when a person self-injures. Three pairs of clients and staff were interviewed about a specific incident of self-injury, with a focus on thoughts feelings and behaviours before during and after the self-injury. They were all also asked about helpful and unhelpful interventions. The data from the interviews was thematically analysed and then synthesised. This resulted in specific and common client perspectives and specific and common staff perspectives. Then each of the client and staff dyads were analysed together with a focus on the interpersonal process. This then produced an account of a synthesised process of these two experiences. Themes included description of self-injury as a cycle of shame, which begins as shame avoidance and then becomes a shame eliciting behaviour, based on other peoples' reactions. Staff and clients described similar emotional reactions, thoughts and psychological defences. Projective identification was used as a method of demonstrating the interpersonal processes between the dyads, with some similar and some contrasting internal experiences. These themeswere discussed in depth linking to relevant literature and key implications for practice were then produced.
Demixed Principal Component Analysis

In many experiments, the data points collected live in high-dimensional observation spaces, yet can be assigned a set of labels or parameters. In electrophysiological recordings, for instance, the responses of populations of neurons generally depend on mixtures of experimentally controlled parameters. The heterogeneity and diversity of these parameter dependencies can make visualization and interpretation of such data extremely difficult. Standard dimensionality reduction techniques such as principal component analysis (PCA) can provide a succinct and complete description of the data, but the description is constructed independent of the relevant task variables and is often hard to interpret. Here, we start with the assumption that a particularly informative description is one that reveals the dependency of the high-dimensional data on the individual parameters. We show how to modify the loss function of PCA so that the principal components seek to capture both the maximum amount of variance about the data, while also depending on a minimum number of parameters. We call this method demixed principal component analysis (dPCA) as the principal components here segregate the parameter dependencies. We phrase the problem as a probabilistic graphical model, and present a fast Expectation-Maximization (EM) algorithm. We demonstrate the use of this algorithm for electrophysiological data and show that it serves to demix the parameter-dependence of a neural population response.
New MicroRNAs in Drosophila—Birth, Death and Cycles of Adaptive Evolution

The origin and evolution of new microRNAs (miRNAs) is important because they can impact the transcriptome broadly. As miRNAs can potentially emerge constantly and rapidly, their rates of birth and evolution have been extensively debated. However, most new miRNAs identified appear not to be biologically significant. After an extensive search, we identified 12 new miRNAs that emerged de novo in Drosophila melanogaster in the last 4 million years (Myrs) and have been evolving adaptively. Unexpectedly, even though they are adaptively evolving at birth, more than 94% of such new miRNAs disappear over time. They provide selective advantages, but only for a transient evolutionary period. After 30 Myrs, all surviving miRNAs make the transition from the adaptive phase of rapid evolution to the conservative phase of slow evolution, apparently becoming integrated into the transcriptional network. During this transition, the expression shifts from being tissue-specific, predominantly in testes and larval brain/gonads/imaginal discs, to a broader distribution in many other tissues. Interestingly, a measurable fraction (20–30%) of these conservatively evolving miRNAs experience “evolutionary rejuvenation” and begin to evolve rapidly again. These rejuvenated miRNAs then start another cycle of adaptive – conservative evolution. In conclusion, the selective advantages driving evolution of miRNAs are themselves evolving, and sometimes changing direction, which highlights the regulatory roles of miRNAs.
Medial temporal lobe contributions to visuospatial memory and cognition

The contributions of human medial temporal lobe (MTL) structures to perceiving and remembering visuospatial features of the environment were investigated from the perspective of human cognitive neuropsychology. The experimental chapters focussed on three main issues: the contribution of the right-sided MTL to spatial awareness the roles of the right MTL and hippocampus in spatial and non-spatial scene perception and memory and the role of the hippocampus in anterograde memory for different types of memoranda. Visual neglect (a failure of spatial awareness), was investigated after lesions of the right medial occipitotemporal lobe. Lesion analyses and diffusion tensor imaging demonstrated that the lesions associated with neglect interrupted a white matter pathway connecting the parahippocampal gyrus with the parietal lobe. The interaction of these areas may be critical to subserve normal spatial awareness. Perception and short-term retention of spatial and non-spatial aspects of visual scenes were investigated using a new task - the 4 Mountains Test. Right MTL damage impaired both spatial perception and memory. Hippocampal damage impaired spatial memory but had little impact on scene perception. Damage to these areas did not affect non-spatial perception or memory, suggesting a role for the hippocampus in the short-term retention of allocentric spatial information. A rather similar pattern of performance was documented in patients with possible Alzheimer's disease. The role of the hippocampus in anterograde memory was investigated in two patients using recognition tests for words, scenes and faces. Receiver operating characteristics analyses were used to assess the contribution of recollection and familiarity to performance. Hippocampal damage impacted upon scene and word recognition but not face recognition. In terms of scene recognition, the hippocampus may be critical to make recognition judgements based on both recollection and highly confident feelings of familiarity.
Rapid Mobile Object Recognition Using Fisher Vector

We propose a real-time object recognition method for a smart phone, which consists of light-weight local features, Fisher Vector and linear SVM. As light local descriptors, we adopt a HOG Patch descriptor and a Color Patch descriptor, and sample them from an image densely. Then we encode them with Fisher Vector representation, which can save the number of visual words greatly. As a classifier, we use a liner SVM the computational cost of which is very low. In the experiments, we have achieved the 79.2% classification rate for the top 5 category candidates for a 100-category food dataset. It outperformed the results using a conventional bag-of-features representation with a chi-square-RBF-kernel-based SVM. Moreover, the processing time of food recognition takes only 0.065 seconds, which is four times as faster as the existing work.
Real-time detection of implant-associated neutrophil responses using a formyl peptide receptor-targeting NIR nanoprobe

Neutrophils play an important role in implant-mediated inflammation and infection. Unfortunately, current methods which monitor neutrophil activity, including enzyme measurements and histological evaluation, require many animals and cannot be used to accurately depict the dynamic cellular responses. To understand the neutrophil interactions around implant-mediated inflammation and infection it is critical to develop methods which can monitor in vivo cellular activity in real time. In this study, formyl peptide receptor (FPR)-targeting near-infrared nanoprobes were fabricated. This was accomplished by conjugating near-infrared dye with specific peptides having a high affinity to the FPRs present on activated neutrophils. The ability of FPR-targeting nanoprobes to detect and quantify activated neutrophils was assessed both in vitro and in vivo. As expected, FPR-targeting nanoprobes preferentially accumulated on activated neutrophils in vitro. Following transplantation, FPR-targeting nanoprobes preferentially accumulated at the biomaterial implantation site. Equally important, a strong relationship was observed between the extent of fluorescence intensity in vivo and the number of recruited neutrophils at the implantation site. Furthermore, FPR-targeting nanoprobes may be used to detect and quantify the number of neutrophils responding to a catheter-associated infection. The results show that FPR-targeting nanoprobes may serve as a powerful tool to monitor and measure the extent of neutrophil responses to biomaterial implants in vivo.
Identification of a Novel Jasmonate-Responsive Element in the AtJMT Promoter and Its Binding Protein for AtJMT Repression

Jasmonates (JAs) are important regulators of plant biotic and abiotic stress responses and development. AtJMT in Arabidopsis thaliana and BcNTR1 in Brassica campestris encode jasmonic acid carboxyl methyltransferases, which catalyze methyl jasmonate (MeJA) biosynthesis and are involved in JA signaling. Their expression is induced by MeJA application. To understand its regulatory mechanism, here we define a novel JA-responsive cis-element (JARE), G(C)TCCTGA, in the AtJMT and BcNTR1 promoters, by promoter deletion analysis and Yeast 1-Hybrid (Y1H) assays; the JARE is distinct from other JA-responsive cis-elements previously reported. We also used Y1H screening to identify a trans-acting factor, AtBBD1, which binds to the JARE and interacts with AtJAZ1 and AtJAZ4. Knockout and overexpression analyses showed that AtBBD1 and its close homologue AtBBD2 are functionally redundant and act as negative regulators of AtJMT expression. However, AtBBD1 positively regulated the JA-responsive expression of JR2. Chromatin immunoprecipitation from knockout and overexpression plants revealed that repression of AtJMT is associated with reduced histone acetylation in the promoter region containing the JARE. These results show that AtBBD1 interacts with JAZ proteins, binds to the JARE and represses AtJMT expression.
Circular BIST with partial scan

A BIST (built-in self test) methodology that uses the circular BIST technique to perform a random test of sequential logic circuits is presented. The fault coverage obtained using this technique is supplemented by deterministic tests that are presented to the CUT (circuit under test) by configuring the circular path as a partial scan chain. A CAD (computer-aided-design) tool for automating this methodology is described, a variety of heuristics for picking which flip-flops should be included in the circular path are evaluated, and experimental results are presented. <<ETX>>
Cognitive Correlates of Functional Abilities in Individuals with Mild Cognitive Impairment: Comparison of Questionnaire, Direct Observation, and Performance-Based Measures

The relationship between, and the cognitive correlates of, several proxy measures of functional status were studied in a population with mild cognitive impairment (MCI). Participants were 51 individuals diagnosed with MCI and 51 cognitively healthy older adults (OA). Participants completed performance-based functional status tests and standardized neuropsychological tests, and performed eight activities of daily living (e.g., watered plants, filled medication dispenser) while under direct observation in a campus apartment. An informant interview about everyday functioning was also conducted. Compared to the OA control group, the MCI group performed more poorly on all proxy measures of everyday functioning. The informant report of instrumental activities of daily living (IADL) did not correlate with the two performance-based measures; however, both the informant-report IADL and the performance-based everyday problem-solving test correlated with the direct observation measure. After controlling for age and education, cognitive predictors did not explain a significant amount of variance in the performance-based measures; however, performance on a delayed memory task was a unique predictor for the informant-report IADL, and processing speed predicted unique variance for the direct observation score. These findings indicate that differing methods for evaluating functional status are not assessing completely overlapping aspects of everyday functioning in the MCI population.
KEC@DPIL-FIRE2016: Detection of Paraphrases in Indian Languages (Tamil)

This paper presents a report on Detecting Paraphrases in Indian Languages (DPIL), in particular the Tamil language, by the team NLP@KEC of Kongu Engineering College. Automatic paraphrase detection is an intellectual task which has immense applications like plagiarism detection, new event detection, etc. Paraphrase is defined as the expression of a given fact in more than one way by means of different phrases. Paraphrase identification is a classic natural language processing task which is of classification type. Though there are several algorithms for paraphrase identification, reflecting the semantic relations between the constituent parts of a sentence plays a very important role. In this paper we utilize sixteen different features to best represent the similarity between sentences. The proposed approach utilizes machine learning algorithms like Support Vector Machine and Maximum Entropy for classification of given sentence pair. They have been classified into Paraphrase and Not-a-Paraphrase for task1 and Paraphrase, Not-a-Paraphrase and Semi-Paraphrase for task2. The accuracy and performance of these methods are measured on the basis of evaluation parameters like accuracy, precision, recall, f-measure and macro f-measure. Our methodology got 2 place in DPIL evaluation track.
Cooperative information forwarding in vehicular networks subject to channel randomness

This paper investigates the information dissemination process in wireless communication networks formed by vehicles. As vehicles are moving constantly, a vehicular ad-hoc network exhibits a highly-dynamic network topology and a fast-changing radio environment. These distinguishing characteristics result in random and unreliable wireless connections between vehicles. Consequently, vehicles need to work cooperatively to disseminate a piece of information to the destination. This paper analyses cooperative information forwarding schemes where each vehicle determines whether or not to forward a received packet in a decentralized manner, without the costly or even impractical demand for the knowledge of network topology. Considering a generic wireless connection model incorporating wireless channel randomness, analytical results are derived for the probability of successful delivery and the expected number of packet forwardings. Moreover, analysis is conducted on the optimal information forwarding scheme that meets a pre-designated probability of successful delivery objective using the minimum number of packet forwardings.
Active Appearance Models for Gaze Estimation Masters Thesis

This thesis describes the implementation of and the experimentation with a gaze estimation system based on an approach called the Active Appearance Model (AAM). Active Appearance Models are generative models of a certain visual phenomenon. They can be used to model specific patterns of variability in shape and grey-level appearance, which in turn can be used directly in image interpretation. Our goal for developing a gaze estimation system is a low-cost user friendly system. Therefore, we wish to design a system that can be used with normal off-the-shelf equipment, like a normal resolution webcam without infrared capabilities and infrared lighting. Our method uses separate modules for subtracting both the head pose and the eye angles from an image depicting a face. The head pose is necessary information, since we want to allow the user to move its head. We basically tested two different methods for calculating/estimating the gaze angle. The first one being a direct calculation method based on important positions of parts of the human eye, and a geometric gaze estimation model. The second method uses a Neural Network classifier to estimate the gaze direction based on a representation of the eyes of the user (we tested several representations). This second method proved to be most promising, where the best performing representation was a combination of the landmark vector and the appearance vector of our AAM (of an eye). We showed that is possible to obtain quite accurate results from our gaze estimation system, although these results are not as accurate as the results of other systems using a infrared camera and/or higher resolution images. Depending on the field of application (where only moderately accurate results are required), our method can be a cheap alternative to other more expensive systems.
A Reconfigurable Classifier Model of the Visual System

Neurons are costly for an organism to build and maintain, yet at the same time, there has apparently been strong selective pressure on organisms to incorporate additional functions into their nervous systems. Based on the known properties of dendritic trees and synapses (Koch, 2004), I propose a simple, biologically and evolutionary plausible architecture by which a neurons can be used for multiple different computations (time multiplexed). In such a model, signals extrinsic to an area selectively enable and disable parts of the dendritic trees of neurons within an area in a coordinated way. When this mechanism is extended to an entire pathway, like the ventral pathway, it gives rise to a notion of a reconfigurable pathway or a reconfigurable classifier, in which extrinsic signals can have the same pathway perform very different computations at different times (although some basic constraints remain due to overall connectivity; for example, V1 and V2 necessarily perform a kind of “feature extraction”, albeit tunable), and also route inputs and outputs from the pathway from and to different areas. In the rest of the paper, I explore the implications of such models.
Network (In)Security Through IP Packet Filtering

t for improving network security. Used properly, packet filtering is a useful tool for he security-conscious network administrator, but its effective use requires a e p thorough understanding of its capabilities and weaknesses, and of the quirks of th articular protocols that filters are being applied to. This paper examines the utility t fi of IP packet filtering as a network security measure, briefly contrasts IP packe ltering to alternative network security approaches such as application-level gate-
Dysphonia detection based on modulation spectral features and cepstral coefficients

In this paper, we combine modulation spectral features with mel-frequency cepstral coefficients for automatic detection of dysphonia. For classification purposes, dimensions of the original modulation spectra are reduced using higher order singular value decomposition (HOSVD). Most relevant features are selected based on their mutual information to discrimination between normophonic and dysphonic speakers made by experts. Features that highly correlate with voice alterations are associated then with a support vector machine (SVM) classifier to provide an automatic decision. Recognition experiments using two different databases suggest that the system provides complementary information to the standard mel-cepstral features.
On the detection of reset faults; in synchronous sequential circuits

We consider the problem of testing reset faults in synchronous sequential circuits with reset hardware. The reset hardware is assumed to consist of a reset input connected to all the flip-flops through a reset line. We propose a fault model that accommodates any routing of the reset line to the flip-flops. This is important since test generation is typically carried out without knowledge of the way in which the reset line is routed. We describe fault simulation procedures for the proposed reset fault model. The procedures use a given test sequence and generate appropriate reset sequences, if needed. It is shown that contrary to the common assumption that reset faults are easily detected by test sequences for other faults in the circuit some reset faults require special reset sequences and special test sequences. Thus, a complete test sequence must explicitly accommodate reset faults.
Asynchronous transmission of wireless multicast system with genetic joint antennas selection

Optimal antenna selection algorithm of multicast transmission can significantly reduce the number of antennas and can acquire lower complexity and high performance which is close to that of exhaustive search. An asynchronous multicast transmission mechanism based on genetic antenna selection is proposed. The computational complexity of genetic antenna selection algorithm remains moderate while the total number of antennas increases comparing with optimum searching algorithm. Symbol error rate (SER) and capacity of our mechanism are analyzed and simulated, and the simulation results demonstrate that our proposed mechanism can achieve better SER and sub-maximum channel capacity in wireless multicast systems.