Miracle-dz/UniFAR-FTUs huggingface dataset:
Yearbook Age Prediction ( CS 395 T )

We tackle the yearbook ’Face To Age’ challenge to predict the year that a given yearbook photo was taken in. We experiment with three variants of the VGG19 architecture [4], the AlexNet architecture [2], as well as different loss functions and an extensive effort to reduce overfitting. A variant of the AlexNet architecture, that has 2048 neurons in the fully connected layers and is ensembled over 5 models, gives us the best results, with a mean L1 norm distance of 5.54.
That's Not My Question: Learning to Weight Unmatched Terms in CQA Vertical Search

A fundamental task in Information Retrieval (IR) is term weighting. Early IR theory considered both the presence or absence of all terms in the lexicon for ranking and needed to weight them all. Yet, as the size of lexicons grew and models became too complex, common weighting models preferred to aggregate only the weights of the query terms that are matched in candidate documents. Thus, unmatched term contribution in these models is only considered indirectly, such as in probability smoothing with corpus distribution, or in weight normalization by document length. In this work we propose a novel term weighting model that directly assesses the weights of unmatched terms, and show its benefits. Specifically, we propose a Learning To Rank framework, in which features corresponding to matched terms are also "mirrored" in similar features that account only for unmatched terms. The relative importance of each feature is learned via a click-through query log. As a test case, we consider vertical search in Community-based Question Answering(CQA) sites from Web queries. Queries that result in viewing CQA content often contain fine grained information needs and benefit more from unmatched term weighting. We assess our model both via manual evaluation and via automatic evaluation over a clickthrough log. Our results show consistent improvement in retrieval when unmatched information is taken into account. This holds both when only identical terms are considered matched, and when related terms are matched via distributional similarity.
ATOM- A Low-Cost Mobile Manipulator for Research and Testing

This paper represents the technique of developing a ROS (Robot Operating System) based low cost mobile manipulator. Additionally, the contemporary commercial and custom ROSbased mobile manipulators have been discussed. In this paper, we have discussed how the performance of the high-end mobile manipulation platforms can be partially achieved by a low-cost custom made module implementing the basic packages of ROS. The architecture and till to date development on the platform-ATOM (Autonomous Testbed of Mobile Manipulation) has been also shown.
A Survey on Underwater Image Enhancement Techniques

This review paper deals with the methods to improve underwater image enhancement techniques, the processing of underwater image captured is necessary because the quality of underwater images affect and these image leads some serious problems when compared to images from a clearer environment. A lot of noise occurs due to low contrast, poor visibility conditions (absorption of natural light), non uniform lighting and little color variations, pepper noise and blur effect in the underwater images because of all these reasons number of methods are existing to cure these underwater images different filtering techniques are also available in the literature for processing and enhancement of underwater images one of them is image enhancement using median filter which enhances the image and help to estimate the depth map and improve quality by removing noise particles with the help of different techniques, and the other is RGB Color Level Stretching have used. Forward USM technique can also be used for image enhancement.
Guided Image Filter and Adaptive Histogram Specification based DBLA for Enhancing Remotely Sensed Images

The fundamental reason of contrast enhancement is to bring out detail that is hidden in an image that is covered up in a picture or to expand contrast in a low contrast picture. This paper presents a literature survey on some of the image Enhancement techniques for improving images like histogram equalization, global histogram equalization, bi-histogram equalization, dualistic sub-image histogram equalization, Spatial Domain Method and Frequency Domain Method etc. The overall objective of this paper is to evaluate the short comings in earlier techniques of image enhancement.
Estimating HIV evolutionary pathways and the genetic barrier to drug resistance.

BACKGROUND The evolution of drug-resistant viruses challenges the management of human immunodeficiency virus (HIV) infections. Understanding this evolutionary process is important for the design of effective therapeutic strategies. METHODS We used mutagenetic trees, a family of probabilistic graphical models, to describe the accumulation of resistance-associated mutations in the viral genome. On the basis of these models, we defined the genetic barrier, a quantity that summarizes the difficulty for the virus to escape from the selective pressure of the drug by developing escape mutations. RESULTS From HIV reverse-transcriptase sequences that had been obtained from treated patients, we derived evolutionary models for zidovudine, zidovudine plus lamivudine, and zidovudine plus didanosine. The genetic barriers to resistance to zidovudine, stavudine, lamivudine, and didanosine, for the above 3 regimens, were computed and analyzed. We found both the mode and the rate of development of resistance to be heterogeneous. The genetic barrier to zidovudine resistance was increased if lamivudine was added to zidovudine but was decreased for didanosine. The barrier to lamivudine resistance was maintained with zidovudine plus didanosine, whereas the barrier to didanosine resistance was reduced most with zidovudine plus lamivudine. CONCLUSION Mutagenetic trees provide a quantitative picture of the evolution of drug resistance. The genetic barrier is a useful tool for design of effective treatment strategies.
Safety of 6000 intravitreal dexamethasone implants

Purpose To evaluate the real-life safety profile of intravitreal dexamethasone implant injection for various retinal conditions. Methods Retrospective multicenter analysis of intravitreal dexamethasone implant injections (700 µg) due to various retinal conditions including central retinal venous occlusion (1861 injections), diabetic macular oedema (3104 injections), post-surgical cystoid macular oedema (305 injections) and uveitis (381 injections). The eyes were evaluated mainly for the occurrence of adverse events such as glaucoma, cataract, retinal detachment and endophthalmitis along during the follow-up period. Results A total of 6015 injections in 2736 eyes of 1441 patients (mean age of 65.7±12.9 years) were in total analysed over an average period of 18 months (range 6 months to 102 months). A total of 576 eyes (32.5% of the phakic eyes) developed cataract requiring surgical intervention. However, visually insignificant cataract progression was observed in another 259 phakic eyes (14.6%) which did not require surgical removal. A total of 727 eyes (26.5%) experienced an intraocular pressure (IOP) rise of >25 mm Hg, with 155 eyes (5.67%) having a prior history of glaucoma and 572 eyes (20.9%) having new onset IOP rise. Overall, more than 90% of eyes with IOP rise were managed medically, and 0.5% eyes required filtering surgery. Endophthalmitis (0.07%), retinal detachment (0.03%) and vitreous haemorrhage (0.03%) were rare. There was no significant change in visual acuity (p=0.87) and central macular thickness (p=0.12) at the last follow-up. Conclusion This is the largest real-life study assessing the safety of intravitreal dexamethasone implant injections in various retinal conditions. Cataract progression and intraocular pressure rise are the most common side effects, but are often rather easily manageable.
Meta Model of e-Learning Materials Development

The multitude of software tools is available for the creation of learning resources. However the majority of these tools provided by different software producers do not have a unified mechanism by means of which it would be possible to search and reuse the existing learning resources or their elements. To solve this problem the structures of descriptive data can be used. The aim of this paper is to describe a meta-model of e-learning objects and e-learning formats that could be used in the creation of e-learning materials compatible with various e-learning standards. The meta-data models that are used in widely-known learning resourcesâ repositories and their structureâs metadata standards providing cross-system compatibility have been evaluated. The key metadata standards of learning objects were identified and their comparative analysis was performed. The e-learning material logical model was created and the essential demands for e-learning objectâs data repository were defined. The technologies and their provided electronic learning objectsâ classification systems were investigated for the future development of e-learning materials. The scheme of e-LM development process was obtained, which provides the transformation of different modules.
Improvements in speech perception with an experimental nonlinear frequency compression hearing device

The performance of an experimental frequency compression hearing device was evaluated using tests of speech understanding in quiet. The device compressed frequencies above a programmable cut-off, resulting in those parts of the input signal being shifted to lower frequencies. Below the cut-off, signals were amplified without frequency shifting. Subjects were experienced hearing aid users with moderate-to-severe sensorineural hearing loss and sloping audiograms. Their recognition of monosyllabic words was tested using the experimental device in comparison with conventional hearing aids. Of the 17 subjects, eight showed a significant score improvement (p < 0.05), whereas one subject showed a significant score decrease. Some of the improvements may have resulted from the better audibility provided in the high frequencies by the experimental device in comparison with the conventional aids. However, a subsequent study found that increasing the high-frequency gain in the conventional aids did not produce equivalent perceptual benefits.
Game Metrics Without Players: Strategies for Understanding Game Artifacts

Game metrics are an approach to understanding games and gameplay by analyzing and visualizing information collected from players in playtests. This paper proposes that another source of metrics is the game itself, and that not all information needs to (or ought to) come from empirical playtests. I discuss seven strategies for extracting information from games, and discuss how the information retrieved in this manner relates to empirical playtest metrics---which it differs from but can often complement.
A WordNet-based Query Expansion Method for Geographical Information Retrieval

This report describes a query expansion method based on the expansion of geographical terms by means of WordNet synonyms and meronyms. We used this method for our participation to the GeoCLEF 2005 English monolingual task, while using the well-known Lucene search engine for indexing and retrieval. The obtained results show that the proposed method was not suitable for the GeoCLEF track, while WordNet can be used in a more eective way during the indexing phase, by adding synonyms and holonyms to the index terms.
A 2D Barcode Extraction Method Based on Texture Direction Analysis

Barcode extraction is an essential step in the 2D barcode reading architecture. This paper presents the development and evaluation of a new approach toward the design of 2D barcode extraction based on texture direction analysis. This new approach can be detailed as: i) threshold a gray-level image; ii) analyze the texture direction of a window which is selected within the barcode area in the image; iii) roughly locate the barcode using the proposed texture direction analysis; iv) precisely locate the barcode by applying Hough transform; iv) rectify the barcode using inverse perspective transformation and bilinear interpolation methods; v) apply various types of barcode decoder. The experimental result showed this approach is applicable to most of the 2D barcode decoders.
Molecular-genetic mechanisms of memory formation in mouse models of neurodevelopmental and neuropsychiatric disorders

Neurodevelopmental and neuropsychiatric disorders are a significant and expanding global health crisis. Many individuals affected by these disorders have social and cognitive symptoms represent significant sources of ongoing disability that are refractory to available treatment options. The search for cures and therapies for disorders fundamentally requires an understanding of the core neuropathology and insight into the underlying molecular mechanisms at work. In this dissertation, I describe experiments that we performed to explore molecular and genetic mechanisms underlying memory impairment and enhancement in mice. Synaptic structural proteins form a critical and adjustable framework that supports recruitment of neurotransmitter receptors and facilitates signal transduction. In Chapter 2, we explored a role for the autismrelated gene Protocadherin 10 (Pcdh10) as a key regulator of dendritic spine morphology and synapse elimination. We found that mice with reduced PCDH10 have deficits in amygdala function, including impairments in conditioned fear, social interactions and gamma synchrony, as well as increased density of immature filopodia-type spines. In the second part of this dissertation, we showed that the co-repressor SIN3A is a negative regulator of memory formation. In Chapter 3, we demonstrated that reducing levels of SIN3A enhances in long-term memory and hippocampal synaptic plasticity, and increases expression of Homer1, a gene encoding a post-synaptic density protein that regulates signaling through metabotropic glutamate receptors. In Chapter 4, we identified contextual fear deficits in transgenic mice expressing Cre recombinase in forebrain neurons. These results expand our understanding of molecular mechanisms of memory formation, and identify new therapeutic targets for improving cognitive function. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Cell & Molecular Biology First Advisor Ted Abel
Modelling Interaction of Sentence Pair with Coupled-LSTMs

Recently, there is rising interest in modelling the interactions of two sentences with deep neural networks. However, most of the existing methods encode two sequences with separate encoders, in which a sentence is encoded with little or no information from the other sentence. In this paper, we propose a deep architecture to model the strong interaction of sentence pair with two coupled-LSTMs. Specifically, we introduce two coupled ways to model the interdependences of two LSTMs, coupling the local contextualized interactions of two sentences. We then aggregate these interactions and use a dynamic pooling to select the most informative features. Experiments on two very large datasets demonstrate the efficacy of our proposed architecture and its superiority to state-of-the-art methods.
FK1706 enhances the recovery of erectile function following bilateral cavernous nerve crush injury in the rat.

INTRODUCTION Advances in neurobiology have led to a surge of clinical interest in the development of protective and regenerative neuromodulatory strategies, as surgical therapies for prostate cancer often result in neuronal damage and debilitating loss of sexual function. AIM To investigate the dose-dependent efficacy of FK1706, a nonimmunosuppressant immunophilin ligand, for the recovery of erectile function following bilateral cavernous nerve crush injury in the rat. MAIN OUTCOME MEASURES Recovery of erectile function was assessed by cavernous nerve electrostimulation and reported as maximal increase of intracavernous pressure (ICP) and area under the curve (AUC). Changes in animal weights, percentage completion of treatment course, and survival were compared between groups. METHODS; Thirty-five Sprague-Dawley male rats were randomly divided into five equal groups: seven animals received a sham operation, whereas 28 animals underwent bilateral cavernous nerve crush injury, followed by subcutaneous injection of vehicle alone (1.0 mL/kg), or low (0.1 mg/kg), medium (0.32 mg/kg), or high dose (1.0 mg/kg) FK1706 5 days per week for 8 weeks. RESULTS Erectile dysfunction did not occur in the sham group (mean maximal ICP increase of 100.8 +/- 6.3 cmH(2)O), whereas nerve injury and vehicle treatment produced a significant reduction in ICP response to 34.4 +/- 12.8 cmH(2)O. The mean ICP increase for high-dose FK106 treatment was 73.9 +/- 6.3 cmH(2)O (P < 0.01 vs. vehicle) compared with 58.3 +/- 7.4 cmH(2)O and 56.9 +/- 8.3 for low and medium doses (P > 0.05). Similar stepwise findings were observed using AUC data. No significant maximal aortic blood pressure or weight differences occurred between groups and all animals completed treatment. CONCLUSION High-dose subcutaneous FK1706 therapy promoted recovery of erectile function following bilateral cavernous nerve crush injury in the rat. No significant differences between groups were observed for changes in weight, and the 8-week treatment course was completed for all animals.
A general family of multivariable digital lattice filters

Lattice structures are developed for the realization of m -input p -output discrete-time all-pass transfer matrices H(z) , given in the form of a right matrix-fraction description (MFD): H(z)= N(z)D^{-l}(z) . The procedure is based on the generation of a sequence of all pass matrices of successively decreasing order, by matrix LBR two-pair extraction. Two cases are distinguished: the first case is when none of the intermediate allpass matrices is degenerate. For this case, the resulting structures are in the form of a cascade of matrix two-pairs separated by vector delays, with each two-pair being a multi-input multi-output digital filter structure characterized by an orthogonal transfer matrix of dimension (m + p) \times ( m + p) . The structures are in general either completely controllable or completely observable, depending upon the location of the delay elements. The synthesis technique also leads to a procedure for obtaining the greatest common right divisor between the polynomial matrices involved in the MFD. The results are extended to the cascaded-lattice synthesis of arbitrary stable transfer matrices by an embedding process. The developments of this paper automatically place in evidence a procedure for testing the stability of a transfer matrix. A special case of the resulting structures when p = m =1 gives rise to the well-known Gray-Markel digital lattice structures, whereas another special case with p = 2 and m = 1 leads to certain recently reported orthogonal digital filters. The second case, where some of the intermediate allpass matrices are degenerate, is handled separately, leading to a modified form of cascaded-multivariable lattice structures.
Podocyte-Specific Sialylation-Deficient Mice Serve as a Model for Human FSGS.

BACKGROUND The etiology of steroid-resistant nephrotic syndrome, which manifests as FSGS, is not completely understood. Aberrant glycosylation is an often underestimated factor for pathologic processes, and structural changes in the glomerular endothelial glycocalyx have been correlated with models of nephrotic syndrome. Glycans are frequently capped by sialic acid (Sia), and sialylation's crucial role for kidney function is well known. Human podocytes are highly sialylated; however, sialylation's role in podocyte homeostasis remains unclear. METHODS We generated a podocyte-specific sialylation-deficient mouse model (PCmas-/- ) by targeting CMP-Sia synthetase, and used histologic and ultrastructural analysis to decipher the phenotype. We applied CRISPR/Cas9 technology to generate immortalized sialylation-deficient podocytes (asialo-podocytes) for functional studies. RESULTS Progressive loss of sialylation in PCmas-/- mice resulted in onset of proteinuria around postnatal day 28, accompanied by foot process effacement and loss of slit diaphragms. Podocyte injury led to severe glomerular defects, including expanded capillary lumen, mesangial hypercellularity, synechiae formation, and podocyte loss. In vivo, loss of sialylation resulted in mislocalization of slit diaphragm components, whereas podocalyxin localization was preserved. In vitro, asialo-podocytes were viable, able to proliferate and differentiate, but showed impaired adhesion to collagen IV. CONCLUSIONS Loss of cell-surface sialylation in mice resulted in disturbance of podocyte homeostasis and FSGS development. Impaired podocyte adhesion to the glomerular basement membrane most likely contributed to disease development. Our data support the notion that loss of sialylation might be part of the complex process causing FSGS. Sialylation, such as through a Sia supplementation therapy, might provide a new therapeutic strategy to cure or delay FSGS and potentially other glomerulopathies.
Using Generic Corpora to Learn Domain-Specific Terminology

This paper describes a knowledge-weak technique for automatically learning terminology relevant to a given domain from a corpus of domain-specific documents. We used a generic corpus as a filter for scoring the relevance of terms to a domain. We tested this approach against three corpora from different domains and, in each case, high-scoring terms consistently represented concepts relevant to the domain from which they came.
Trail Records and Navigational Learning

An emerging wave of 'ambient' technologies has the potential to support learning in new and particular ways. In this paper we propose a 'trail model' of 'navigational learning' which links some particular learning needs to the potentialities of these technologies. In this context, we outline the design and use of an 'experience recorder', a technology to support learning in museums. In terms of policy for the e-society, these proposals are relevant to the need for personalised and individualised learning support.
Effects of Neural Stimuli on Blood Flow through Vasa Vasorum in Dogs

The purpose of this study was to determine whether neural stimuli alter blood flow through vasa vasorum in the thoracic aorta. We measured flow with microspheres in anesthetized dogs and observed responses to sympathetic stimulation and baroreceptor stimulation. During these interventions, changes in arterial pressure were prevented with propranolol or an arterial reservoir, to minimize indirect effects on vasa vasorum mediated through changes in aortic wall tension. Electrical stimulation of the stellate ganglion at 10 Hz reduced blood flow to vasa vasorum in the thoracic aorta from 11 ± 1.6 (mean ± SE to 6.8 ± 1.1 ml/min per 100 g (P < 0.05). Aortic diameter, measured with a sonomicrometer technique, did not change during sympathetic stimulation. Thus, the reduction in blood flow through vasa vasorum during sympathetic stimulation appears to be a direct effect, and not the result of constriction of the aorta and compression of vasa. To determine effects of physiological alterations in neurogenic vasoconstrictor activity, we examined responses to stimulation of carotid baroreceptors. When pressure in isolated, perfused carotid sinus baroreceptors was raised from 81 ± 3 to 198 ± 2 mm Hg, blood flow to vasa vasorum of the thoracic aorta increased from 3.7 ± 0.6 to 10 ± 2.2 ml/min per 100 g (P < 0.05). We conclude that vasa vasorum are responsive to neural stimuli, since they constrict during sympathetic stimulation and dilate in response to baroreceptor stimulation. Ore Res 45: 615-620, 1979