Miracle-dz/UniFAR-FTUs huggingface dataset:
Distance metric learning and feature combination for shape-based 3D model retrieval

This paper proposes a 3D model retrieval algorithm that employs an unsupervised distance metric learning with a combination of appearance-based features; two sets of local visual features and a set of global features. These visual features are extracted from range images rendered from multiple viewpoints about the 3D model to be compared. The local visual features are bag-of-features histograms of a set of Scale Invariant Feature Transform (SIFT) features by Lowe [7] sampled at either salient or dense and random points. The global visual feature is also a SIFT feature sampled at an image center. The proposed method then uses an unsupervised distance metric learning based on the Manifold Ranking (MR) [15] to compute distances between these features. However, the original MR may not be effective when applied to a set of features having certain distance distribution. We propose an empirical method to adjust the distance profile so that the MR becomes effective. Experiments showed that the retrieval algorithm using a linear combination of distances computed from the proposed set of features by using the modified MR performed well across multiple benchmarks having different characteristics.
Multi-sensor and Information-Based Event Triggered Distributed Estimation

The paper is motivated by recent surge of interest in utilization of a large number of sensor nodes in cyber-physical systems (CPSs) and the critical importance of managing sensor's restricted resources. In this regard, we propose a multi-sensor and open-loop estimation algorithm with an information-based triggering mechanism. In the open-loop topology considered in this paper, each sensor transfers its measurements to the fusion centre (FC) only in occurrence of specific events (asynchronously). Events are identified using the information-based triggering mechanism without incorporation of a feedback from the FC and/or implementation of a local filter at the sensor level. We propose a multi-sensor triggering approach based on the projection of each local observation into the state-space which corresponds to the achievable gain in the sensor's information state vector. The simulation results show that the proposed multi-sensor information-based triggering mechanism closely follows its full-rate estimation counterpart.
Microfluidic “thin chips” for chemical separations

This paper describes the design, development and application of microfluidic “thin chips” fabricated from PDMS. Thin chips consist of multiple layers of PDMS chemically bonded onto each other. Unlike thicker PDMS chips that suffer from lack of sensitivity due to PDMS absorption in the VIS and UV range, the thinness of these chips allows for the detection of chromophoric species within the microchannel via an external fiber optics detection system. C18‐modified reversed‐phase silica particles are packed into the microchannel using a temporary taper created by a magnetic valve and separations using both pressure‐ and electrochromatographic‐driven methods are detailed.
Intrinsic Manifold SLIC: A Simple and Efficient Method for Computing Content-Sensitive Superpixels

Superpixels are perceptually meaningful atomic regions that can effectively capture image features. Among various methods for computing uniform superpixels, simple linear iterative clustering (SLIC) is popular due to its simplicity and high performance. In this paper, we extend SLIC to compute content-sensitive superpixels, i.e., small superpixels in content-dense regions with high intensity or colour variation and large superpixels in content-sparse regions. Rather than using the conventional SLIC method that clusters pixels in <inline-formula><tex-math notation="LaTeX"> $\mathbb {R}^5$</tex-math><alternatives><inline-graphic xlink:href="liu-ieq1-2686857.gif"/></alternatives> </inline-formula>, we map the input image <inline-formula><tex-math notation="LaTeX">$I$</tex-math><alternatives> <inline-graphic xlink:href="liu-ieq2-2686857.gif"/></alternatives></inline-formula> to a 2-dimensional manifold <inline-formula><tex-math notation="LaTeX">$\mathcal {M}\subset \mathbb {R}^5$</tex-math><alternatives> <inline-graphic xlink:href="liu-ieq3-2686857.gif"/></alternatives></inline-formula>, whose area elements are a good measure of the content density in <inline-formula><tex-math notation="LaTeX">$I$</tex-math><alternatives> <inline-graphic xlink:href="liu-ieq4-2686857.gif"/></alternatives></inline-formula>. We propose a simple method, called <italic>intrinsic manifold SLIC</italic> (IMSLIC), for computing a geodesic centroidal Voronoi tessellation (GCVT)—a uniform tessellation—on <inline-formula><tex-math notation="LaTeX">$\mathcal {M}$</tex-math> <alternatives><inline-graphic xlink:href="liu-ieq5-2686857.gif"/></alternatives></inline-formula>, which induces the content-sensitive superpixels in <inline-formula><tex-math notation="LaTeX">$I$</tex-math><alternatives> <inline-graphic xlink:href="liu-ieq6-2686857.gif"/></alternatives></inline-formula>. In contrast to the existing algorithms, IMSLIC characterizes the content sensitivity by measuring areas of Voronoi cells on <inline-formula> <tex-math notation="LaTeX">$\mathcal {M}$</tex-math><alternatives><inline-graphic xlink:href="liu-ieq7-2686857.gif"/> </alternatives></inline-formula>. Using a simple and fast approximation to a closed-form solution, the method can compute the GCVT at a very low cost and guarantees that all Voronoi cells are simply connected. We thoroughly evaluate IMSLIC and compare it with eleven representative methods on the BSDS500 dataset and seven representative methods on the NYUV2 dataset. Computational results show that IMSLIC outperforms existing methods in terms of commonly used quality measures pertaining to superpixels such as compactness, adherence to boundaries, and achievable segmentation accuracy. We also evaluate IMSLIC and seven representative methods in an image contour closure application, and the results on two datasets, WHD and WSD, show that IMSLIC achieves the best foreground segmentation performance.
Computational model of idiosyncratic perception of others' emotions

This paper deals with computational modelling for predicting the idiosyncratic perception of others' emotions, namely how individual external observers will score the emotional states of others interacting with each other. We separately model the observer effect (or individual differences of observers), and the conversational-scene effect or the video-clip effect (how interlocutors are interacting), based on Bayes' theorem with the assumption of their conditional independence. The observer term describes the observer's cognitive tendency, including bias, in a probabilistic form, and does not include any clip information. In contrast, the clip term describes how a target clip is recognized by an unspecified observer. The perceived emotion is predicted to be the state that maximizes the conditional probability given the observer and target clip. An experiment with 100 observers and 97 clips demonstrated, in a leave-one-out cross-validation scenario, that 1) there is in fact no statistically and practically significant interaction between observer and clip, and 2) our Bayesian modelling achieves a 97 percent accuracy as a reference of test-retest reliability. Furthermore, when combined with existing observer and clip models that can handle unknown observers and clips, our model yielded an accuracy of around 50 percent in a more challenging leave-one-subject-and-clip-out cross-validation scenario.
A layered detect-compress-and-forward coding scheme for the relay channel

We develop a practical layered detect-compress-and-forward (LDCF) coding framework for a three-node relay network. Assuming all transmissions to be mapped to Quadrature Amplitude Modulation (QAM) constellations, the LDCF framework at the relay utilizes maximum-likelihood detection, followed by a multi-level convolutional coding structure to achieve distributed joint source-channel coding of the detected indices. The layering is achieved by mapping the more important detection bit-planes to the more significant bit-planes of the QAM constellation, thus providing them a higher level of protection. As a result, the proposed strategy adapts to heterogeneous channel conditions by letting the destination extract as many CF cooperation layers as the channel conditions allow. At the destination, we propose an iterative message passing algorithm to achieve joint decoding of the relay's detection layers before recovering the original source information. Simulations results with off-the-shelf convolution codes indicate a performance gain of approximately 3 dB over the traditional unlayered CF strategy.
Key solutions for a massive MIMO FDD system

The ongoing standardization within 3GPP for the so called new radio (NR) system has identified massive multiple-input multiple output (MIMO) transmission, also called full dimension MIMO, as one of the main contributors to higher spectral efficiency for the mobile broadband case. In particular for radio frequencies below 6 GHz, channel estimation has to be supported in frequency division duplex (FDD) as well as time division duplex (TDD) operation. In TDD we may obtain downlink channels by estimating uplink channels, assuming reciprocity. For FDD, codebook based design as well as some type of explicit feedback is under discussion. Separately, there are also ongoing discussions of the question if massive MIMO in combination with FDD is a reasonable choice at all. Here we highlight some of our recent results obtained within several 5G research projects. To our understanding they overcome some of the inherent limitations of massive MIMO for FDD. As indicated by simulations, the resulting concept enables a grid of beam (GoB) and reference signal design with a reasonable downlink reference signal overhead of around 10 percent, together with reasonable feedback overhead of several hundred kbit/s per UE. Such a design attains around 90 percent of the massive MIMO system performance with ideal channel state information.
Effects of matte coating on the paper surface and print density

Abstract In this work, standard laboratory printing applications with IGT (ISO 12647-2) were applied on uncoated and matte-coated papers using offset inks (DIN ISO 2846-1). Surface roughnesses of uncoated and coated sheets were recorded to be 195 and 13 ml/min, respectively. Air permanence values of uncoated and coated papers were found to be 5.6 and 0.103 μm/Pa·s, respectively. Changes in the print densities were recorded up to 48 h. Print density changes for uncoated and matte-coated papers were surprisingly found to be in similar paths (8% in the first 4 h), although significant differences between surface roughnesses were recorded. Furthermore, paper samples showed similar behaviors for the percent volume changes, where drop volume disappeared within 6 min. It is concluded that matte coating did not have any significant effects on print density change and drop volume change.
Discovering hot topics using Twitter streaming data social topic detection and geographic clustering

There has been an increasing interest in analyzing social network services data. However, detecting social topics in the era of information explosion requires state-of-the-art analytics techniques. The geographic clustering analysis based on social topics across provinces, i.e., states, has rarely been studied. Using the Twitter data collected in the United States (US), we detected the social hot topic by using the ratio of word frequency. Also, we found geographic communities by correlating the time series for a set of topic words across US states. The result of the geographic clustering was visualized using the Google Fusion Table. In conclusion, the ratio of word frequency properly detects social topics or breaking news while suppressing daily tweeted small talks or emotional words such as lol, like, and love. We have also demonstrated that a clustering algorithm based on a social topic can be useful in classifying social communities.
Fusion of thermal and depth images for occlusion handling for human detection from mobile robot

In this paper we present a vision-based approach to detect multiple persons from a mobile robot in real world scenarios using thermal and depth images. First, human upper-body is detected from thermal image to obtain the bounding box coordinates (BBC). This is used as an initial estimate of the position of a person. Then, depth image is fused with the region of interest obtained from the thermal image. Occlusion detection is then performed using the BBC to obtain the actual position of detected persons. The proposed method is able to detect persons and is able to resolve occlusions during the detection process to correctly obtain all the persons in the view.
Utilizing Audiovisual and Gain-Framed Messages to Attenuate Psychological Reactance Toward Weight Management Health Messages

ABSTRACT Guided by the psychological reactance theory, this study predicted that gain-framed messages and audiovisual content could counteract state reactance and increase the persuasiveness of weight management health messages. Data from a 2 (message frame: gain/loss) × 2 (modality: audiovisual/text) × 2 (message repetition) within-subjects experiment (N = 82) indicated that in the context of weight management messages for college students, gain-framed messages indeed mitigate psychological reactance. Furthermore, the modality and the frame of the health message interacted in such a way that gain-framed messages in an audiovisual modality generated the highest motivations to comply with the recommendations in the persuasive health messages.
Alteration of GABAergic neurotransmission in Huntington's disease

Hereditary Huntington's disease (HD) is characterized by cell dysfunction and death in the brain, leading to progressive cognitive, psychiatric, and motor impairments. Despite molecular and cellular descriptions of the effects of the HD mutation, no effective pharmacological treatment is yet available. In addition to well‐established alterations of glutamatergic and dopaminergic neurotransmitter systems, it is becoming clear that the GABAergic systems are also impaired in HD. GABA is the major inhibitory neurotransmitter in the brain, and GABAergic neurotransmission has been postulated to be modified in many neurological and psychiatric diseases. In addition, GABAergic neurotransmission is the target of many drugs that are in wide clinical use. Here, we summarize data demonstrating the occurrence of alterations of GABAergic markers in the brain of HD carriers as well as in rodent models of the disease. In particular, we pinpoint HD‐related changes in the expression of GABAA receptors (GABAARs). On the basis that a novel GABA pharmacology of GABAARs established with more selective drugs is emerging, we argue that clinical treatments acting specifically on GABAergic neurotransmission may be an appropriate strategy for improving symptoms linked to the HD mutation.
Switching from Inadequate Adjunctive or Combination Treatment Options to Brexpiprazole Adjunctive to Antidepressant: An Open-Label Study on the Effects on Depressive Symptoms and Cognitive and Physical Functioning

Abstract Background: Approximately 50% of patients with major depressive disorder do not respond adequately to their antidepressant treatment, underscoring the need for more effective treatment options. The objective of this study was to investigate the effect of adjunctive brexpiprazole on depressive symptoms in patients with major depressive disorder who were not responding to adjunctive or combination therapy of their current antidepressant treatments with several different classes of agents (NCT02012218). Methods: In this 6-week, open-label, phase 3b study, patients with major depressive disorder who had an inadequate response to ≥1 adjunctive or combination therapy, in addition to history of ≥1 failure to monotherapy antidepressant treatment, were switched to adjunctive brexpiprazole. Efficacy was assessed by change from baseline to week 6 in Montgomery-Åsberg Depression Rating Scale total score. Patient functioning was assessed using the Sheehan Disability Scale and the Cognitive and Physical Functioning Questionnaire. Safety and tolerability were also assessed. Results: A total of 51/61 (83.6%) patients completed 6 weeks of treatment with adjunctive brexpiprazole. Improvements in depressive symptoms were observed (least squares mean change from baseline to week 6 in Montgomery-Åsberg Depression Rating Scale total score, −17.3 [P < .0001]) as well as improvements in general and cognitive functioning (mean changes from baseline to week 6: Sheehan Disability Scale, −3.1 [P < .0001]; Massachusetts General Hospital–Cognitive and Physical Functioning Questionnaire, −9.2 [P < .0001]). The most common adverse event was fatigue (14.8%); akathisia was reported by 8.2% of patients. Conclusions: In patients with major depressive disorder who had switched to open-label adjunctive brexpiprazole following inadequate response to previous adjunctive or combination therapy, improvements were observed in depressive symptoms, general functioning, cognitive function, and energy/alertness.
Location-specific tweet detection and topic summarization in Twitter

Automatic detection of tweets that provide Location-specific information will be extremely useful in conveying geo-location based knowledge to the users. However, there is a significant challenge in retrieving such tweets due to the sparsity of geo-tag information, the short textual nature of tweets, and the lack of pre-defined set of topics. In this paper, we develop a novel framework to identify and summarize tweets that are specific to a location. First, we propose a weighting scheme called Location Centric Word Co-occurrence (LCWC) that uses the content of the tweets and the network information of the twitterers to identify tweets that are location-specific. We evaluate the proposed model using a set of annotated tweets and compare the performance with other weighting schemes studied in the literature. This paper reports three key findings: (a) top trending tweets from a location are poor descriptors of location-specific tweets, (b) ranking tweets purely based on users' geo-location cannot ascertain the location specificity of tweets, and (c) users' network information plays an important role in determining the location-specific characteristics of the tweets. Finally, we train a topic model based on Latent Dirichlet Allocation (LDA) using a large collection of local news database and tweet-based Urls to predict the topics from the location-specific tweets and present them using an interactive web-based interface.
Government Programs Can Improve Local Labor Markets, But Do They? A Re-Analysis of Ham, Swenson, Imrohoroğlu, and Song (2011)

Research on the effects of enterprise zones – especially state programs – has generally failed to find evidence of beneficial effects such job growth or poverty reduction. In contrast, Ham, Swenson, Imrohoro? lu, and Song (2011, hereafter HSIS) present evidence that state and federal enterprise zones (EZs) established in the 1990s substantially reduced poverty. However, their estimates of the effects of EZs in reducing poverty are badly overstated for two reasons. First, HSIS have a substantial error in their data on poverty rates by Census tract, which accounts for most of the estimated impact of state EZs that they find. Second, their estimates of the effects of federal Empowerment Zones (EMPZs) and Enterprise Communities (ENTCs) appear to be strongly influenced by selection of areas that experienced negative shocks. An estimator based on comparing federally designated zones to more-comparable areas that applied for and were rejected as zones, or became zones in the future, yields much smaller estimates than those in HSIS. And the large poverty-reduction effects of ENTCs that HSIS found are largely spurious – not surprisingly, given that ENTCs received meager benefits and had no hiring credits.
Influence of environmental tobacco smoke on morphology and functions of cardiovascular system assessed using diagnostic imaging

Abstract Exposure to tobacco smoke is a significant problem of environmental medicine. Tobacco smoke contains over one thousand identified chemicals including numerous toxicants. Cardiovascular system diseases are the major cause of general mortality. The recent development of diagnostic imaging provided methods which enable faster and more precise diagnosis of numerous diseases, also those of cardiovascular system. This paper reviews the most significant scientific research concerning relationship between environmental exposure to tobacco smoke and the morphology and function of cardiovascular system carried out using diagnostic imaging methods, i.e. ultrasonography, angiography, computed tomography and magnetic resonance imaging. In the forthcoming future, the studies using current diagnostic imaging methods should contribute to the reliable documentation, followed by the wide-spreading knowledge of the harmful impact of the environmental tobacco smoke exposure on the cardiovascular system.
Effects of Different Sources of Water on Concrete Strength: A Case Study of Ile-Ife

This research investigated the effect of different types of mixing water on the compressive strength of concrete. It analysed the effect of impurities such as salts of sodium, manganese, tin, zinc, copper and lead on the compressive strength of concrete. The effects of the presence of some other impurities like silt and suspended particles on concrete strength were also investigated. Samples of water from six sources in Ile-Ife environ were chemically analysed to ascertain their chemical constituents. 100mm cube samples were cast with these water samples. Compressive strength test was carried out on the cubes and the findings were statistically processed. The results indicated that sources of water used in mixing concrete have a significant impact on the compressive strength of the resulting concrete. It concluded by suggesting that river water could be used for mixing where tap water is scarce. However, other properties such as durability and shrinkage should be considered before use. Keywords: compressive strength, concrete, mixing water
Neurological Neonatal Birth Injuries: A Literature Review

Birth injuries are a diverse set of traumas afflicting a newborn during labor and/or delivery. These range from temporary paralysis to hematomas. Herein, a comprehensive review of the birth injuries is presented, including the risk factors, classification of various paralyzes and nerve damage, as well as bleeding complications. The predicted outcomes and complications, as well as the treatment options for various birth injuries, are also discussed.
An Object-Based Visual Selection Model Combining Physical Features and Memory

In this paper, a new visual selection model is proposed, which combines both early visual features and object-based visual selection modulations. This model integrates three main mechanisms. The first is responsible for the segmentation of the scene allowing the identification of objects. In the second one, the average of saliency of each object is calculated for each feature considered in this work, which provides the modulation of the visual attention for one or more features. Finally, the third mechanism is responsible for building the object-saliency map, which highlights the salient objects in the scene. It will be shown that top-down modulation can overcome bottom-up saliency by selecting a known object instead of the most salient (bottom-up) and is even clear in the absence of any bottom-up clue. Several experiments with synthetic and real images are conducted and the obtained results demonstrate the effectiveness of the proposed approach for visual attention.