Miracle-dz/UniFAR-FTUs huggingface dataset:
A Dictyostelium discoideum mutant that missorts and oversecretes lysosomal enzyme precursors is defective in endocytosis

A mutant strain of Dictyostelium discoideum, HMW570, oversecretes several lysosomal enzyme activities during growth. Using a radiolabel pulse-chase protocol, we followed the synthesis and secretion of two of these enzymes, alpha-mannosidase and beta-glucosidase. A few hours into the chase period, HMW570 had secreted 95% of its radiolabeled alpha- mannosidase and 86% of its radiolabeled beta-glucosidase as precursor polypeptides compared to the secretion of less than 10% of these forms from wild-type cells. Neither alpha-mannosidase nor beta-glucosidase in HMW570 were ever found in the lysosomal fractions of sucrose gradients consistent with HMW570 being defective in lysosomal enzyme targeting. Also, both alpha-mannosidase and beta-glucosidase precursors in the mutant strain were membrane associated as previously observed for wild- type precursors, indicating membrane association is not sufficient for lysosomal enzyme targeting. Hypersecretion of the alpha-mannosidase precursor by HMW570 was not accompanied by major alterations in N- linked oligosaccharides such as size, charge, and ratio of sulfate and phosphate esters. However, HMW570 was defective in endocytosis. A fluid phase marker, [3H]dextran, accumulated in the mutant at one-half of the rate of wild-type cells and to only one-half the normal concentration. Fractionation of cellular organelles on self-forming Percoll gradients revealed that the majority of the fluid-phase marker resided in compartments in mutant cells with a density characteristic of endosomes. In contrast, in wild-type cells [3H]dextran was predominantly located in vesicles with a density identical to secondary lysosomes. Furthermore, the residual lysosomal enzyme activity in the mutant accumulated in endosomal-like vesicles. Thus, the mutation in HMW570 may be in a gene required for both the generation of dense secondary lysosomes and the sorting of lysosomal hydrolases.
Kinect image classification using LLC

In this paper we introduce locality-constrained linear coding (LLC) for Kinect image classification. First we extract visual features from the RGB-D (RGB + depth) images. Then we conduct LLC feature representations on RGB and depth visual features separately, and the two representations are concatenated for achieving better discriminative capability. The PCA dimensionality reduction method is used for eliminating data redundancy between RGB image and depth image. Finally support vector machine (SVM) is applied for classification. Experiments on scene and object classification using two recent publicly available datasets ([9], [15]) demonstrate that our proposed approach has achieved superior performance comparing with state-of-the-art methods.
Sexual assault prevention in the military: Key issues and recommendations

ABSTRACT Data suggests that sexual assault and harassment continue to be significant concerns within the U.S. military. Given such findings, the Department of Defense and the component military services have recently developed several initiatives aimed at preventing sexual violence within their ranks. A number of these programming efforts are modeled after prevention initiatives in other communities such as college campuses. In this article, the authors discuss major issues that are important for the military as they move forward to augment their sexual assault prevention efforts. Previous prevention work both within and outside of the military will be discussed in the context of the reviewed issues. The article concludes with a list of recommendations.
Long-term survival following traumatic brain injury

Purpose. The study used a retrospective cohort design to establish long-term mortality rates and predictors of mortality for persons after moderate to severe traumatic brain injury (TBI). Method. Consecutive records of persons with moderate to severe TBI who were discharged from a large rehabilitation hospital in Pittsburgh, Pennsylvania in the years 1974 – 1984, 1988 and 1989 were reviewed. Results. Six hundred and forty-two eligible individuals were identified and mortality was ascertained up to 24 years post injury. One hundred and twenty-eight of these individuals were found to be deceased. Poisson regression analyses revealed at least a 2-fold increased risk for mortality compared to the general population. Pre-injury characteristics and levels of disability at discharge from in-patient rehabilitation were among the strongest predictors of mortality. Conclusions. These data constitute evidence for premature death in the post-acute TBI population following a moderate to severe head injury and are discussed in relation to other research in the area.
A tight bound for the joint covariance of two random vectors with unknown but constrained cross-correlation

This paper derives a fundamental result for processing two correlated random vectors with unknown cross-correlation, where constraints on the maximum absolute correlation coefficient are given. A tight upper bound for the joint covariance matrix is derived on the basis of the individual covariances and the correlation constraint. For symmetric constraints, the bounding covariance matrix naturally possesses zero cross covariances, which further increases their usefulness in applications. Performance is demonstrated by recursively propagating a state through a linear dynamical system suffering from stochastic noise correlated with the system state.
Time aware location recommendations in location based social networks

Smartphones have fundamentally changed how people make choices about the products and services they consume and the way they interact with each other. The spread and extensive usage of mobile applications has led to the rise of Location-based Social Network (LBSN) services like Foursquare, Yelp etc, that aim to aim to provide new and novel places of interest to people based on their interests and habits. A Recommendation system helps users to discover places they may like and also enable them to narrow down their choices. In particular, providing relevant location recommendations to users is essential to drive customer engagement with the mobile application and is also an important research topic. Multiple studies on human mobility patterns and my analysis on different LBSN datasets have shown that the preference of users for different locations changes with time, i.e., type of locations visited in the afternoon are different from those visited in the evening. Majority of recommendation systems in LBSN do not take into account the temporal aspect of recommendation. A recommendation system must be able to provide locations to users by taking into account their 1) stationary preferences that don’t change with time and 2) temporal preference that differ with time and recommended locations that are relevant in time to the user. This thesis first presents a feature based location recommendation model, REGULA that exploits the regular mobility behavior of people and incorporates temporal information to provide better location recommendations. REGULA outperforms other feature and graph-based location recommendation models. Further, this thesis presents the first model to recommend interesting areas to people based on their Call Detail Records. Finally, this thesis presents two deep neural network based location recommendation models ( DEEPREC and DEEPTREC ) that are used to learn the stationary and temporal preferences of users. The combined model ( JOINTDEEPREC ) can be used to provide time-aware location recommendations to people. The model was evaluated on one of the largest checkin dataset collected at Microsoft Research Asia and outperforms state-of-the-art model by a factor of 10. v
Development of an FPGA-based real-time P300 speller

A Brain Computer Interface (BCI) is a system that allows direct communication between a computer and the human brain. Though the main application for BCIs is in rehabilitation of disabled patients, they are increasingly being used in other application scenarios as well. Most of the current BCI systems are based on personal computers. However, there is an increased interest in implementing BCIs for portable platforms as well, such as mobile phones and Field Programmable Gate Arrays (FPGAs) owing to low cost, power and portability. This paper proposes a low-cost FPGA based BCI speller application. The proposed system combines a stimulation panel, data acquisition and FPGA based real-time signal processing. The BCI system demonstrated here is a speller, which allows the user to use his/her brain signals to communicate directly with the application and spell out words by merely looking at the screen. The system achieves an accuracy of 65.37% when utilizing 2 rounds of data per character and an accuracy of 100% when utilizing 20 rounds of data per character.
Coggle: SWOT Analysis in Lifelong Learning Education Using Online Collaborative Mind-Mapping

Presently, lifelong learning culture has become a phenomenon in education for sustainable development. In fact, lifelong education offers the society a second chance in changing the standard of living. Therefore, this study is conducted to determine the strengths, weaknesses, opportunities and adversities to a lifelong learning programme. This study adopts Online Collaborative Mind-Mapping, Coggle as a data collection and analysis tool applying qualitative approaches. A total of 239 research participants consisting of executive postgraduate students from the Faculty of Education, Universiti Kebangsaan Malaysia were recruited. The analysis used to obtain the findings is based on SWOT analysis which consisted of techniques used to identify the strengths, advantages, opportunities and threats that exist in this lifetime education program. Findings in this research found that technology, systematic management and experienced instructors contribute to the strengths of the programme, whereas broadband access issues, inconducive classrooms and pedagogical problems result in its weaknesses. Furthermore, findings on difficulties to this lifelong learning programme show students acquire external limitations such as time constraints and personal factors. However, this programme provides opportunities and advantages to all the students as it is conducted during school holidays. Hence, this study suggests that future research will develop a suitable module and approach for lifelong learning students.
Sparse sources are separated sources

Sparse representations are being used to solve problems previously thought insolvable. For example, we can separate more sources than sensors using an appropriate transformation of the mixtures into a domain where the sources are sparse. But what do we mean by sparse? What attributes should a sparse measure have? And how can we use this sparsity to separate sources? We investigate these questions and, as a result, conclude that sparse sources are separated sources, as long as you use the correct measure.
Age- and Experience-Related Distribution of Parvalbumin-Expressing GABAergic Interneurons within the Hippocampus & Surrounding Cortices

Parvalbumin (PV)-expressing inhibitory interneurons are the most numerous GABAergic interneuron type in the neocortex and hippocampus (HPC). Selective reductions in PV interneurons are observed in cortical and limbic regions in postmortem human schizophrenic brain tissue. Reductions in PV expression are also observed in rodents following acute and/or chronic treatment with NMDAantagonists (e.g. ketamine). There are inconsistencies in the literature regarding age-related changes in PV expression in the HPC; some stating age-related decreases, no observed changes, and even increases in PV-immunoreactivity. These inconsistencies make it difficult to qualitatively and quantitatively evaluate changes observed in rodent models following NMDA-antagonist treatment. In order to provide a better baseline understanding of putative developmental changes in normal PV expression, the current study quantified 1) age-related changes in HPC and cortical PV expression in rats; 2) whether PV varied along the septotemporal axis of the HPC; and 3) regional changes in HPC PV expression. PV immunohistochemical methods were used to examine PV expression in hippocampal and adjacent neocortical regions in 1 and 6 month old naive, as well as 24 month old behaviorally trained (radial water maze training), male Sprague-Dawley rats. Our main findings include: 1) specific regional differences (CA1, CA3, DG) across the septotemporal axis that varied by developmental age; 2) age-related decreases in PV expression in CA1 and DG (50-68% and 88-89% decrease from 1 – 6 months, respectively) in naive rats; 12 and 3) A prominent increase in PV expression in the 24 month old rats that may be related to age or behavioral experience. These findings demonstrate developmental differences in the regional expression of PV, as well as potential behavioral and experiential increases in PV expression. Importantly, these baseline data provide key information for future work examining age-related differences in PV as a consequence of acute or chronic NMDA-antagonist
Security and privacy of electric vehicles in the smart grid context: problem and solution

The technology, security and privacy requirements of the electric vehicle (EV) in the smart grid (SG) context, especially when the EV acts as mobile power storage, have gained much attention from the research community and market recently. This role of the EV is motivated by the increase in capacity of the power storages in the EV. In this paper, first we present different situations that an EV can be in the SG context and their privacy issues. Then, we provide two authentication schemes, first one between the EV and a trusted SG server directly, and second one via a non-trusted third party entity with a robust privacy-preserving agenda. Our analysis shows that our mechanisms are secure and robust enough to make sure the privacy of the customers is fully preserved, and at the same time, are efficient since they consume very limited resources.
Parameterized Approximability of Influence in Social Networks

In this paper, we consider the problem of maximizing the spread of influence through a social network. This optimization problem is formally defined as follows. We are given a graph G = (V,E), a positive integer k and a threshold value thr(v) attached to each vertex v ∈ V . The objective is then to find a subset of k vertices to “activate” such that the number of activated vertices at the end of a propagation process is maximum. A vertex v gets activated if at least thr(v) of its neighbors are. We show that this problem is strongly inapproximable in fpt-time with respect to (w.r.t.) parameter k even for very restrictive thresholds. For unanimity thresholds, we prove that the problem is inapproximable in polynomial time and the decision version is W[1]-hard w.r. t. parameter k. On the positive side, it becomes r(n)-approximable in fpt-time w.r. t. parameter k for any strictly increasing function r. Moreover, we give an fpt-time algorithm to solve the decision version for bounded degree graphs.
TomuDB: multi-resolution queries in heterogeneous sensor networks through overlay network

Querying in heterogeneous sensor networks is a challenging research issue due to a variety of real-world queries depending on users' preferences. Examples of queries are weather, nearby restaurants, navigation, etc. Users may ask for a breezy path starting from distinct points to distinct train stations. Sensing data collected from wide areas (city or country level) are needed to provide the real-world search as a service for users. Therefore, another challenge is a collaboration of heterogenous sensor networks because deploying sensors in wide areas is impractical. SensorMap [1] collects sensing data from independent sensor networks by allowing data owners to publish their data on the web. Sensing data from all owners are sent to a centric storage in SensorMap. However, distributed data storage is likely to be an efficient solution comparing to a centric storage in which bottleneck always occurs.
A Hierarchical Protocol for Decentralising Information Dissemination in Distributed Systems

Systems of distributed processors connected by a physical network may have a virtual structure imposed on them to facilitate parallel cooperative system actions. This paper describes the Multiple Virtual Rings organization which is an instance of this approach. System processors are partitioned into groups, structured as virtual rings, which operate in parallel to accumulate local information and make decisions. A hierarchy of rings is formed, at the pinnacle of which is one ring which joins the system together and enables overall cooperation. The configuration of the virtual ring hierarchy is explained and issues which are independent of the ring topology are discussed. A simulation study of a large distributed system is presented which investigates the operation of load balancing algorithms in a hierarchical processor organization.
Agent-based design of fault tolerant manipulators for satellite docking

A rapidly deployable fault tolerant manipulator system consists of modular hardware and support software that allow the user to quickly configure and deploy a fault tolerant manipulator that is custom-tailored for a given task. The main focus of this paper is on the task based design component of such a system, that is, the determination of the optimal manipulator configuration, its base position and the corresponding joint space trajectory for a given task. We introduce a novel agent-based solution approach to task based design and illustrate it with a fault tolerant manipulator design for a satellite docking operation aboard the space shuttle.
Application for Party Based on Cloud Platform

In the past few years, party has played a more and more important role in people's daily life. However, it is not that easy to organize a satisfying party, for the reason that the organizer must consider many details and every member's personal need. In order to help people with this kind of problem, a new and effective tool is needed and we think that an application can be a perfect solution. In this paper, we develop a new Android application, which simplifies the organizing of parties. We also design a specific recommendation algorithm, which helps to offer the organizer some suitable party places, based on people's previous choice, the position of the user, and the evaluations from some review sites. Moreover, using the database deployed on the cloud, our application provides convenience for party members to vote for time or places and for organizers to collect the voting information. The friendly user interface and the use of specific map API make the application more applicable.
Challenges and Perspectives in Big Eye-Movement Data Visual Analytics

Eye tracking has become an important technology to understand where and when people pay visual attention to a scene. Nowadays, eye tracking technology is moving from the laboratory to the real-world, producing more data at higher rates with extensive amounts of different data types. If this trend continues, eye tracking moves into the direction of big data. This requires developing new evaluation approaches beyond statistical analysis and visual inspection to find patterns in the data. As in big data analysis, visual analytics is one possible direction for eye movement data analysis. We look at current visual analytics methods and discuss how they can be applied to big eye-movement data. In this position paper we describe challenges for big eye-movement data visual analytics and discuss which techniques may be useful to address these challenges. Finally, we describe a number of potential scenarios for big eye-movement data.
Torque Setpoint Tracking for Parallel Hybrid Electric Vehicles Using Dynamic Input Allocation

This paper addresses the coordinated control of the internal combustion engine and the electric motor in a parallel hybrid electric vehicle, when both of them are running. In deciding how much torque each motor contributes, both long term energy oriented and short term drivability goals must be considered. The first contribution in this paper consists of proposing an architecture in which three main functional blocks are present, namely a steady-state performance generator, providing an energy oriented torque contribution, a transient performance generator providing a drivability oriented torque contribution, and a dynamic input allocator blending the outputs of the other two blocks in such a way as to satisfy both the short and the long term goals. The second contribution consists in showing how the input allocator must be designed. The other two blocks can be designed following any of several recipes already described in the literature. Experimental validation of the proposed approach confirms the relevance of accounting for the different motor dynamics in the allocator design.
Recovery Trends of Commercial Fish: The Case of an Underperforming Mediterranean Marine Protected Area

Temporal trends in the recovery of exploited species in marine protected areas (MPAs) are useful for a proper assessment of the efficacy of protection measures. The effects of protection on the fish assemblages of the sublittoral rocky reefs in the “Penisola del Sinis-Isola di Mal di Ventre” MPA (W. Sardinia, Italy) were evaluated using a multi-year series of data. Four surveys, conducted 7, 10, 13 and 15 years after the area was designated as an MPA and carried out in the period spanning June and July, were used to estimate the abundance and biomass of commercial species. The surveys were carried out in zones with decreasing levels of fishing restrictions within the MPA (zones A, B, C) and in unprotected zones (OUT1 and OUT2), and underwater video visual census techniques were used. Protected zones only occasionally showed higher levels of abundance or biomass, and the trajectories of those metrics were not consistent across the years. In addition, the zone with the highest level of protection (zone A) never presented levels of abundance and biomass higher than those in zones B and C. This study shows that even 15 years after designation, protection has had no appreciable effect in the MPA studied. It is argued that this is emblematic of several shortcomings in the planning, regulation and enforcement frameworks of the MPA.
Auditory Priming within and across Modalities: Evidence from Positron Emission Tomography

Previous neuroimaging studies of perceptual priming have reported priming-related decreases in the extrastriate cortex. However, because these experiments have used visual stimuli, it is unclear whether the observed decreases are associated specifically with some aspect of visual perceptual processing or with more general aspects of priming. We studied within-and cross-modality priming using an auditory word stem completion paradigm. Positron emission tomography (PET) images were obtained during stem completion and a fixation task. Within-modality auditory priming was associated with blood flow decreases in the extrastriate cortex (bilateral), medial/ right anterior prefrontal cortex, right angular gyrus, and precuneus. In cross-modality priming, the study list was presented visually, and subjects completed auditory word stems. Cross-modality priming was associated with trends for blood flow decreases in the left angular gyrus and increases in the medial/right anterior prefrontal cortex. Results thus indicate that reduced activity in the extrastriate cortex accompanies within-modality priming in both visual and auditory modalities.