Miracle-dz/UniFAR-FTUs huggingface dataset:
Bounded distortion tetrahedral metric interpolation

We present a method for volumetric shape interpolation with unique shape preserving features. The input to our algorithm are two or more 3-manifolds, immersed into R3 and discretized as tetrahedral meshes with shared connectivity. The output is a continuum of shapes that naturally blends the input shapes, while striving to preserve the geometric character of the input. The basis of our approach relies on the fact that the space of metrics with bounded isometric and angular distortion is convex [Chien et al. 2016b]. We show that for high dimensional manifolds, the bounded distortion metrics form a positive semidefinite cone product space. Our method can be seen as a generalization of the bounded distortion interpolation technique of [Chen et al. 2013] from planar shapes immersed in R2 to solids in R3. The convexity of the space implies that a linear blend of the (squared) edge lengths of the input tetrahedral meshes is a simple yet powerful-and-natural choice. Linearly blending flat metrics results in a new metric which is, in general, not flat, and cannot be immersed into three-dimensional space. Nonetheless, the amount of curvature that is introduced in the process tends to be very low in practical settings. We further design an extremely robust nonconvex optimization procedure that efficiently flattens the metric. The flattening procedure strives to preserve the low distortion exhibited in the blended metric while guaranteeing the validity of the metric, resulting in a locally injective map with bounded distortion. Our method leads to volumetric interpolation with superb quality, demonstrating significant improvement over the state-of-the-art and qualitative properties which were obtained so far only in interpolating manifolds of lower dimensions.
Fluid carving

We present a method for intelligently resizing fluid simulation data using seam carving methods. While advances in post-processing techniques have allowed artists greater control over content late in the production process, this technology has largely remained confined to image processing. Our fluid carving system allows fluid simulation post-processing by performing content-aware non-uniform scaling on baked-out fluid simulation data. Specifically, we extend video seam carving techniques to 4-dimensional animated fluid volume data with a graph cut energy function based on mean curvature and kinetic energy. To reduce the complexity of performing graph cuts on 4D data, we provide a new graph construction formulation that greatly reduces the run-time and memory consumption, which are otherwise prohibitively expensive. We demonstrate that our system is useful for post-production fluid simulation changes and editable fluid FX libraries.
IMPEDANCE SPECTROSCOPY ON POLYMER ELECTROLYTES CONTAINING LITHIUM AND MAGNESIUM IONS

A detailed impedance spectroscopy study, together with thermal analysis, was carried out on polymer electrolytes composed of low molecular weight poly(ethylene oxide) 400 with added lithium or magnesium triflate salts. Glass transition temperatures were always far below room temperature. The ion conductivity exhibits a maximum at intermediate salt concentrations and is significantly higher in the case of Li triflate addition. When the ion conductivity contribution was subtracted, a prominent dielectric loss peak in the MHz region was observed. Its relaxation strength scales with ion concentration, as appropriate for an ion pair relaxation in systems above the glass transition. We present evidence that this relaxation is due to the same species that give rise to the ion conductivity. The complex impedance due to the composite ion conductivity – ion pair relaxation process was found to exhibit good agreement with the Davidson-Cole [D.V. Davidson and R.H. Cole, J. Chem. Phys., 19 (1951) 14841490] relaxation function. The relaxation process is characterized by a power-law exponent below 0.5, which signifies an anomalous diffusion process at high frequencies crossing over to a constant conductivity at low frequencies.
Resistivity profiling of the graphite bricks in an Advanced Gas-Cooled Reactor core using a non-linear inverse eddy current method

This paper presents reconstructed resistivity profiles for the cylindrical fuel channel graphite bricks that make up the cores of Advanced Gas-Cooled Reactors (AGR). This study was carried out using an algorithm known as Regularised Levenberg Marquardt (RLM), along with a Finite Element (FE) based forward model. Multi-frequency (MF) Eddy Current (EC) measurements from real AGR cores were used to reconstruct the resistivity profiles as a function of depth from the bores of different graphite bricks. The results in this study were compared with measurements from trepanned graphite samples taken out of the reactor cores, and showed reasonable agreement in multiple cases, suggesting that this method could be a viable tool for assessing the condition of the graphite bricks in AGR cores.
A Novel Framework for User Intent Detect

One of the main modules of Spoken Language Understanding is the user intent detection, which allows pragmatic meaning of users’ utterances to be classified into a Dialogue Act class. Our study proposes a novel framework for detecting users’ intent more articulately without any sophisticated techniques. For purpose of our research, we collected a set of Korean dialogues on the topics of schedule management and manually annotated the utterances with economical and practical dialogue acts. We preprocessed the basic units of Korean version of Global vector (GloVe) corpus by utilizing the technique of WordPiece Model (WPM) to segment the spaced-word units into sub-word units. It is observed that the method of segmenting words by WPM is effective to deal with Korean data, an agglutinative language with various suffixes. Our Convolutional Neural Network classifier has the accuracy of 85.2% in detecting the user’s intention, which is higher than its counterpart without the WPM.
Halophytes for bio-saline agro-forestry and phyto-remediation of coastal saline lands

The article discusses the importance of halophytes and some salt tolerant plants in remediation of saline soils. Many crops cannot be grown on a salt affected land but nature has provided us with a unique group of plants that is, halophytes. Halophytes, plants that survive to reproduce in environments where the salt concentration is around 200 mM NaCl or more, constitute about 1% of the world’s flora. Some halophytes show optimal growth in saline conditions; others grow optimally in the absence of salt. However, the tolerance of all halophytes to salinity relies on controlled uptake and compartmentalization of Na+, K+ and Cl” and the synthesis of organic ‘compatible’ solutes, even where salt glands are operative. The cultivation of economically useful halophytes have potential to remediate saline wastelands and to meet the demands for fodder, fuel, etc from saline lands and thereby helping the faming community to improve livelihood.
The BDNF Loop 4 Dipeptide Mimetic Bis(N-monosuccinyl-L-seryl-L-lysine)hexamethylenediamide Is Active in a Depression Model in Mice after Acute Oral Administration

Low-molecular mimetic BDNF GSB-106, which is a substituted dimeric dipeptide, bis(N-monosuccinyl-L-seryl-L-lysine) hexamethylenediamide, was designed and synthesized in the V. V. Zakusov Research Institute of Pharmacology. The dipeptide activates TrkB, PI3K/AKT, and MAPK/ ERK. GSB-106 is being developed as a potential antidepressant. Its antidepressant activity was detected in a number of rodent tests (0.1–1.0 mg/kg, ip; 0.5–5.0 mg/kg, po). In the present study, GSB-106 was shown to completely eliminate the manifestation of anhedonia in the sucrose preference test and to increase disturbed hippocampal synaptogenesis at acute oral administration (0.1 mg/kg) after 10-day social defeat stress in C57Bl/6 mice.
Integration of multiagent crossing controllers for measure-oriented traffic control

In this paper we will present an integration of multiagent crossing controllers for measureoriented traffic control. It is the basis for the future multiagent traffic control system which uses measure oriented approach to control traffic. This integrated architecture gives us the possibility to react to the dynamic changes of traffic thanks to the data it can gather with its sensors.
Weakly Supervised Object Detection

Detecting objects in images is important for robots because it provides them with rich knowledge about the parts of the environment with which they may interact. Accurate localisation of these objects is especially important if a robot intends to grasp or manipulate the item. While state-of-the-art object detection methods have achieved impressive results for classifying, localising and even precisely segmenting multiple objects in individual images [1], a significant drawback is that they rely on large training datasets containing detailed annotations. Even for bounding boxes, the annotation task is tedious and prevents a robot from quickly learning new objects in new environments. To alleviate this requirement, weakly supervised methods learn tasks without explicit annotation. That is, annotation is only required at the image level instead of the pixel level. For object detection, it has been shown that just a list of object categories per image, without segmentation masks, bounding boxes or centroids, is sufficient for learning [2]. The aim of this project is to develop a pipeline to enable a robot to quickly learn object detection by leveraging weak supervision. Specifically, a method will be developed to acquire data from a hand-held RGB camera and with a robot to train a state-of-the-art weakly supervised object detector. Tasks
Grieving in the digital age: using Facebook profile pages to maintain relationships with the deceased

Advancements in technology, particularly the introduction of online social networking sites, have expanded the modes available when handling the death of a loved one. This study examines how individuals use the Facebook profile pages of deceased persons to cope with loss and maintain relationships with them. An extensive content analysis of Facebook profiles of ten deceased individuals was conducted to investigate what the living discuss in their messages to the deceased in the semi-public setting of a Facebook profile page and if this content changes over the course of time. This analysis revealed that messages to the deceased reflect three themes: 1) processing the death, 2) remembering the deceased, and 3) maintaining the relationship. In addition to these dominant themes, the data also indicated that the content of messages shifted over time. Messages that contained the processing of death remained consistent over time, while posts that reflected remembrance of the deceased decreased, and messages that demonstrated relationship maintenance increased with time. This study utilizes the theoretical frameworks of continuing bonds and social information processing to draw implications of these findings. By examining the content written and how messages change over time, this study provides insight into how people cope with loss and maintain relationships with their deceased loved ones in the digital age. Key terms: Facebook profile, relationships, deceased, grieving, virtual memorial, social information processing theory, continuing bonds
Detecting Task-Based Query Sessions Using Collaborative Knowledge

Our research challenge is to provide a mechanism for splitting into user task-based sessions a long-term log of queries submitted to a Web Search Engine (WSE). The hypothesis is that some query sessions entail the concept of user task. We present an approach that relies on a centroid-based and a density-based clustering algorithm, which consider queries inter-arrival times and use a novel distance function that takes care of query lexical content and exploits the collaborative knowledge collected by Wiktionary and Wikipedia.
Enhancing dynamic cloud-based services using network virtualization

It is envisaged that services and applications will migrate to a cloud-computing paradigm where thin-clients on user devices access, over the network, applications hosted in data centers by application service providers. Examples are cloud based gaming applications and cloud-supported virtual desktops. For good performance and efficiency, it is critical that these services are delivered from locations that are the best for the current (dynamically changing) set of users. To achieve this, we expect that services will be hosted on virtual machines in interconnected data centers and that these virtual machines will migrate dynamically to locations best suited for the current user population. A basic network infrastructure need then is the ability to migrate virtual machines across multiple networks without losing service continuity. In this paper, we develop mechanisms to accomplish this using a network-virtualization architecture that relies on a set of distributed forwarding elements with centralized control (borrowing on several recent proposals in a similar vein). We describe a preliminary prototype system, built using Openflow components, that demonstrates the feasibility of this architecture in enabling seamless migration of virtual machines and in enhancing delivery of cloud-based services.
Sickle Cell Anemia in Relation to Total Homocysteine Levels and the Role of Anticoagulant Proteins

Sickle cell disease (SCD) is a genetic disease characterized by hypercoagulable state and increased risk of thromboembolic events, a rare but significant complication of SCD. Protein C and S are natural anticoagulant proteins. Total homocysteine (tHcy) is an independent risk factor for venous thromboembolism and cardiovascular disease , and its level is therefore of interest in sickle cell disease. The aim of this study was to investigate the plasma levels of protein C and S levels and their relationship to homocysteine level in patients with sickle cell anemia compared to control subjects. In this study twenty patients (m=12, f=8) with sickle cell anemia, classified into sickle cell trait (Hb AS , n=15) and sickle cell disease (Hb SS, n=5), and twenty normal age-sex controls (m=12, f=8) were included. Protein C, S and homocysteine levels were measured using ELISA diagnostic kits technique. The data was statistically analysed by SPSS17 and p values less than 0.05 were considered significant. Our results showed that mean tHcy levels were found to be significantly higher in patients (SS and/or AS) than in control group. No significant correlation was observed between tHcy with protein C or S. The mean value of protein C and S within normal range and statistically not signi ficant in patients compared to controls, but significantly decreased in Hb SS patients. In conclusion, sickle cell anemia is associated with mild elevated tHcy level which may contribute to increased risk of hypercoagulability and thromboembolic complications.
Radar Signal Design for Single Target Detection

A novel design approach has been proposed to evaluate the detection ability of a target using polysemantic sequences (PSS) in the presence of high additive noise. The PSS are optimized by employing Hamming Backtrack algorithm with figure of merit as the measure of goodness. The simulation results show that the proposed sequences give improved robustness of noise for target detection.
PriSEMD-A Privacy-Friendly Approach to Analyze and Measure Smart Entertainment Devices

Smart Entertainment Devices (SED) are belonging to Consumer Electronics (CE) and can be found in many households nowadays. SEDs can be differentiated from CE devices with several aspects. The most important difference is that SEDs provide interfaces to connect to the local network/Internet. Internet-based functionalities like accessing TV programs in media libraries are new features of SEDs. These new features represent on the one hand benefits for the user, but on the other hand, it is possible to track user behavior. Device manufacturers and advertising companies are interested in this data for e.g. improving their products or adverts. In this work we present a concept which allows gathering data sent and received by SEDs. In a succeeding phase, the gathered data is evaluated based on a defined set of rules. The practical and technical feasibility of this concept is shown by a prototype implementation. Due to evaluation purposes, the prototype was tested in a realistic household. This test includes an exemplary analysis of a Smart TV. The results of this 7-day-test have proven that it is possible to measure data from SEDs and to find characteristics concerning user behavior. Characteristics that can be stated are for example the favorite TV programs of a user. In another part of this work, a concept is presented which shows how to forward PriSEMD measured data to third parties without violating the user’s privacy. The SED user has the opportunity to control the transferring process. It is possible to approve certain third parties or to prohibit data transferring at all.
Packet Momentum for Identificationof Anonymity Networks

Multilayer-encryption anonymity networks provide privacy which has become a significant concern on today’s Internet due to many attacks and privacy breaches. The anonymity and privacy these networks provide is a double-edged knife. Increasing attacks, threats and misuse of such valuable anonymity services trigger the need to identify such anonymity networks. Moreover, the implementation of the obfuscation techniques hardens the identification of such networks. Consequently, this research proposes Packet Momentum approach to identify multilayer-encryption anonymity networks. Packet Momentum is a novel approach proposed to identify multilayer-encryption anonymity networks efficiently and accurately and the obfuscations techniques they use. The Packet Momentum aims to use a small number of features and a small number of packets to identify such networks.
Relationship between Ocular Surface Alterations and Concentrations of Aerial Particulate Matter

Abstract Purpose To evaluate ocular surface alterations in two populations at different exposure levels to particulate matter (PM) in their living and work environments. Methods A cross-sectional study was conducted, including 78 volunteers from Argentina who lived and worked under different pollution levels in an urban (U; n = 44) or industrial zone (I; n = 34). Mean exposure level to PM was evaluated. Responses to the Ocular Symptom Disease Index and McMonnies questionnaire were obtained from all subjects. Subsequently, an assessment through the Schirmer I test (ST), slit lamp microscopy, vital staining, and tear breakup time was conducted. Statistical analyses with Chi-square and Bartlett's tests, as well as Student's t-tests and principal component analysis (PCA), were performed. Results Particles of size < 2.5 μm (PM2.5) level was significantly higher in the I group than the U group (P = 0.04). Ocular surface parameters including bulbar redness, eyelid redness, and the degree of vital staining with fluorescein (SF) and lissamine green (SLG) exhibited difference between the groups. With regards to the tear film, statistically significant differences in the ST value and meibomian gland dysfunction between the groups were detected (P = 0.003 and P = 0.02, respectively). Conjunctival SF and SLG, and ST values were identified as factors which could distinguish groups exposed to different PM levels. Conclusion Subjects exposed to higher levels of PM in the outdoor air presented greater ocular surface alterations. Thus, ST, SF, and SLG values could be used as convenient indicators of adverse health effects due to exposure to air pollution.
Aalborg Universitet An Orbital Angular Momentum-Based Array for in-band full-duplex communications Zhang, Yiming; Li, Jia-Lin

A uniform circular array (UCA) with dual orbital angular momentum (OAM) modes is proposed for in-band full-duplex applications. The proposed scheme includes two concentric ring subarrays for transmitting and receiving, respectively, where all elements are operated under the same linear polarization. To suppress the self-interference resulting from the mutual coupling, an OAM mode-selection method related to the proposed configuration is discussed. Results indicate that good isolation performance between the transmitter and receiver can be achieved by using the proposed scheme. To validate the performance, a demonstrator with OAM modes of ‒1 and ‒2 at Ku-band is developed, fabricated, and measured. Measurements show a relative bandwidth of 21.3% from 13.5 to 16.7 GHz, referring to a 40-dB suppression level, is achieved and the desired radiations are found.
Relation Module for Non-Answerable Predictions on Reading Comprehension

Machine reading comprehension (MRC) has attracted significant amounts of research attention recently, due to an increase of challenging reading comprehension datasets. In this paper, we aim to improve a MRC model’s ability to determine whether a question has an answer in a given context (e.g. the recently proposed SQuAD 2.0 task). The relation module consists of both semantic extraction and relational information. We first extract high level semantics as objects from both question and context with multi-head self-attentive pooling. These semantic objects are then passed to a relation network, which generates relationship scores for each object pair in a sentence. These scores are used to determine whether a question is non-answerable. We test the relation module on the SQuAD 2.0 dataset using both the BiDAF and BERT models as baseline readers. We obtain 1.8% gain of F1 accuracy on top of the BiDAF reader, and 1.0% on top of the BERT base model. These results show the effectiveness of our relation module on MRC.