Miracle-dz/UniFAR-FTUs huggingface dataset:
Reinforcement learning in mobile robot navigation Literature review

Robotics is gaining popularity in military operations to facilitate soldier tasks and decrease their exposure to dangerous situations. Researchers are currently working on autonomous and semi-autonomous robots to provide soldiers with more intelligent robotic vehicles. At DRDC Suffield, the Autonomous Intelligent Systems Section is building an expertise in intelligent mobility for unmanned ground vehicles by developing robotic platforms that autonomously generate useful locomotive behaviours. One objective of the group is to solve the problem of navigability of shape-shifting mobile robot platforms. Learning to choose the appropriate geometric configuration with respect to the environment is a promising solution. This document presents a literature review emphasizing reinforcement learning in mobile robot navigation. A variety of algorithms are examined in detail such as Q-learning, HEDGER, SRV, RL-LSTM, CQ-L, HQ-L and W-learning. Finally, the applicability of those algorithms to the problem of shape-shifting mobile robot navigation is discussed.
Personality schemata and attitude change : self-schema matching can increase elaboration of persuasive messages /

Previous research has indicated that matching persuasive appeals to recipients’ self-schemata increases attitude change. Although this finding has been consistently dupUcated, little is known about how or why self-schema matching leads to increased persuasion. The present paper sheds some light on these processes by providing evidence for both moderators and mediators o f the effect. In experiment 1, participants read persuasive messages with introductory fixâmes that were matched to either the recipients’ extraversion or introversion. Manipulated orthogonally to the self-schema appeal was argument quality. Following the persuasive messages, participants completed the attitude measures and a measure o f extraversion. Results indicated that participants tended to discriminate more between strong and weak arguments when the message frame matched, rather than mismatched, their self­ schemata. Thus, participants were more persuaded by strong than weak arguments when reading matched messages, but this effect was attenuated under mismatched conditions. This pattern is indicative of different levels o f elaboration across matched and
Lobe and Serrate are required for cell survival during early eye development in Drosophila

Organogenesis involves an initial surge of cell proliferation, leading to differentiation. This is followed by cell death in order to remove extra cells. During early development, there is little or no cell death. However, there is a lack of information concerning the genes required for survival during the early cell-proliferation phase. Here, we show that Lobe (L) and the Notch (N) ligand Serrate (Ser), which are both involved in ventral eye growth, are required for cell survival in the early eye disc. We observed that the loss-of-ventral-eye phenotype in L or Ser mutants is due to the induction of cell death and the upregulation of secreted Wingless (Wg). This loss-of-ventral-eye phenotype can be rescued by (i) increasing the levels of cell death inhibitors, (ii) reducing the levels of Hid-Reaper-Grim complex, or (iii) reducing canonical Wg signaling components. Blocking Jun-N-terminal kinase (JNK) signaling, which can induce caspase-independent cell death, significantly rescued ventral eye loss in L or Ser mutants. However, blocking both caspase-dependent cell death and JNK signaling together showed stronger rescues of the L- or Ser-mutant eye at a 1.5-fold higher frequency. This suggests that L or Ser loss-of-function triggers both caspase-dependent and -independent cell death. Our studies thus identify a mechanism responsible for cell survival in the early eye.
“It’s just horny fun…” Grindr and its influence on young gay men’s attitudes towards HIV and risky sexual behaviour

This research study explores the gay dating smartphone app Grindr and the role it plays in influencing young gay men’s attitudes towards HIV and risky sexual behaviour, looking closely at the social norms within the app itself. Grindr was specifically chosen as the focus of this research project as it is the largest gay dating app in Europe, and has begun to be considered an important communications tool for public health and communications professionals looking to tackle the spread of HIV. The study used qualitative research methods, implementing semi-structured interviews to gain a rich and in-depth insight into the knowledge and attitudes of young gay men who use Grindr, aged between 18-25 years old. The research findings identified that while Grindr users perceive the app to be highly sexualised and crude, they do not perceive the social norms of the app to directly influence their attitudes towards risky sexual behaviour and that pressure to engage in risky sexual behaviour is more prevalent in real life scenarios, with Grindr allowing users to easily end conversations or block other users.
The Influence of the Characteristics of CEOs on Open Innovation Performance in SMEs : The Case of Korea PAPER IN PROGRESS

Open innovation has been defined as ? the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and to expand the markets for external use of innovation, respectively? (Chesbrough, 2003). With the emergence of the knowledge-based society, open innovation has become an important research theme for both academia and industry. However, most studies related to open innovation have focused on large firms especially high technology or multinational firms. In addition, there have been few attempts to understand how SMEs (small and medium size enterprises) build up their knowledge network and strategy in terms of implementation of open innovation. Recent studies have revealed how the characteristics of internal members in an organization can affect the patterns of knowledge capability building. The CEO (chief executive officer) in particular can affect the performance of collaborations with external partners. This paper aims to investigate the relationship between the characteristics of SME CEOs and open innovation performance. In this paper we explore three key characteristics of a CEO: disciplinary fitness, operational background, and the degree of entrepreneurship. This paper draws upon a survey of CEOs in SMEs in information technology (IT) and biotechnology industries in Korea. Our sample was limited to SMEs that had their own R&D department. We use the results of this survey to test a series of hypotheses. Firstly, for a disciplinary background, we assumed that the matches between the educational major of a CEO and business area would present positive relation. We also assumed that the close relation with CEO? s supervisor (e.g. whether CEO was a student of the supervisor or a CEO hired the students who were under his/her supervision) would play an important role in trust building and collaborating with the university as an open innovation partner. Secondly, we hypothesized that that working experience of a CEO in a Chaebol (a large conglomerate, usually family-owned business group in South Korea) would make it easy for the SME to enter and exploit the business network that the Chaebol has formulated. Lastly, for the degree of entrepreneurship, it was postulated that higher the entrepreneurial characteristic of a CEO, more open innovation implementation were carried out actively. Our analysis found that 1) Open innovation activities of SMEs affect the performance of a firm and 2) the impact of three key characteristics of CEOs varies in different sectors and in the size of SMEs. Joonmo Ahn University of Cambridge 1st year 30th, June, 2014 ja494@cam.ac. uk
Wavelet domain image restoration using edge preserving prior models

We consider a wavelet-based edge preserving regularization scheme for use in linear image restoration problems. Our efforts build on a collection of mathematical results indicating that wavelets are especially useful for representing functions that contain discontinuities (i.e. edges in two dimensions or jumps in 1D). We interpret the resulting theory in a statistical signal processing framework and obtain a highly flexible framework for adapting the degree of regularization to the scale based structure of the underlying image. We demonstrate an efficient algorithm for obtaining the reconstructions from observed data and for choosing the multiple regularization parameters governing the priors.
The utility of the Pittsburgh Sleep Quality Index in US military personnel

ABSTRACT Sleep disturbances are endemic in military personnel with nonclinical populations averaging 6 hours of sleep. The Pittsburgh Sleep Quality Index (PSQI), however, has not been validated in this population. It is thus unknown if the PSQI can differentiate clinically significant sleep disorders from sleep disturbances resulting from military duties with restricted sleep periods. After a clinical evaluation and polysomnogram, participants (N = 148) were classified as having insomnia only, obstructive sleep apnea (OSA) only, comorbid insomnia and OSA (CIO), service-related illnesses only (SRI–; pain, depression, posttraumatic stress disorder, traumatic brain injury), and controls. Military personnel in the insomnia only, and the CIO groups had higher PSQI scores (13.5 ± 2.8 and 14.7 ± 3.5, respectively) compared to the controls (8.9 ± 3.9). A cut-off score of ≥10 was optimal (90% sensitivity and 69% specificity) for determining clinically significant insomnia (≥12 for CIO; 84% sensitivity, 77% specificity). In military personnel, a PSQI score >5 is not necessarily indicative of a clinically significant sleep disorder. The use of elevated cut-off PSQI scores are likely better suited to differentiate military personnel who require further clinical evaluation versus a more conservative sleep improvement protocol.
Integrating mitosis, toxicity, and transgene expression in a telecommunications packet‐switched network model of lipoplex‐mediated gene delivery

Gene delivery systems transport exogenous genetic information to cells or biological systems with the potential to directly alter endogenous gene expression and behavior with applications in functional genomics, tissue engineering, medical devices, and gene therapy. Nonviral systems offer advantages over viral systems because of their low immunogenicity, inexpensive synthesis, and easy modification but suffer from lower transfection levels. The representation of gene transfer using models offers perspective and interpretation of complex cellular mechanisms, including nonviral gene delivery where exact mechanisms are unknown. Here, we introduce a novel telecommunications model of the nonviral gene delivery process in which the delivery of the gene to a cell is synonymous with delivery of a packet of information to a destination computer within a packet‐switched computer network. Such a model uses nodes and layers to simplify the complexity of modeling the transfection process and to overcome several challenges of existing models. These challenges include a limited scope and limited time frame, which often does not incorporate biological effects known to affect transfection. The telecommunication model was constructed in MATLAB to model lipoplex delivery of the gene encoding the green fluorescent protein to HeLa cells. Mitosis and toxicity events were included in the model resulting in simulation outputs of nuclear internalization and transfection efficiency that correlated with experimental data. A priori predictions based on model sensitivity analysis suggest that increasing endosomal escape and decreasing lysosomal degradation, protein degradation, and GFP‐induced toxicity can improve transfection efficiency by three‐fold. Application of the telecommunications model to nonviral gene delivery offers insight into the development of new gene delivery systems with therapeutically relevant transfection levels. Biotechnol. Bioeng. 2014;111: 1659–1671. © 2014 Wiley Periodicals, Inc.
Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.
Predicting Contextual Sequences via Submodular Function Maximization

Sequence optimization, where the items in a list are ordered to maximize some reward has many applications such as web advertisement placement, search, and control libraries in robotics. Previous work in sequence optimization produces a static ordering that does not take any features of the item or context of the problem into account. In this work, we propose a general approach to order the items within the sequence based on the context (e.g., perceptual information, environment description, and goals). We take a simple, efficient, reduction-based approach where the choice and order of the items is established by repeatedly learning simple classifiers or regressors for each "slot" in the sequence. Our approach leverages recent work on submodular function maximization to provide a formal regret reduction from submodular sequence optimization to simple cost-sensitive prediction. We apply our contextual sequence prediction algorithm to optimize control libraries and demonstrate results on two robotics problems: manipulator trajectory prediction and mobile robot path planning.
Inverse Consistencies for Non-Binary Constraints

We present a detailed study of two inverse consistencies for non-binary constraints: relational path inverse consistency (rel PIC) and pairwise inverse consistency (PWIC). These are stronger than generalized arc consistency (GAC), even though they also only prune domain values. We propose algorithms to achieve rel PIC and PWIC, that have a time complexity better than the previous generic algorithm for inverse consistencies. One of our algorithms for PWIC has a complexity comparable to that for GAC despite doing more pruning. Our experiments demonstrate that inverse consistencies can be more efficient than GAC on a range of non-binary problems.
Testing Intonational Models by Computer Simulation

In this presentation (and demonstration) a research design is proposed in which prosodic modelling, prosodic labelling, prosodic (re)synthesis [and in the future prosodic recognition] are integrated within one computer simulation tool. The design has been implemented within the Entropic ESPS/xwaves environment and is being tested on several languages at labs workings on prosody and speech synthesis (Stuttgart, Lund, Konstanz, Saarbruecken, Kyoto, Umea).
Individual prey specialization in wasps : Predator size is a weak predictor of taxonomic niche width and niche overlap

Intuitively, larger predators in a population may be favoured in subduing, handling and carrying to the nest a wider range of prey compared to smaller ones. In absence of any individual chemical or behavioural bias in prey choice, and independently from size-biased preference, it may be predicted: (1) that smaller wasps would have both narrower niches and lower niche overlap than larger wasps, (2) a positive correlation between individual niche width and niche overlap, and (3) a positive correlation between predator size and prey size. We tested these predictions using available data in literature on individual prey spectrum for 10 populations/generations of apoid wasps (Hymenoptera: Crabronidae). The analysis showed that individual specialization is widespread. Smaller individuals were more specialized than larger ones, as we hypothesized, in only one population, while the opposite was found in two cases; on the other side, niche width correlated (positively) with wasp size only in one population. In five out of the 10 examined cases predator size Correspondence/Reprint request: Dr. Carlo Polidori, Dipartimento di Biologia, Sezione di Zoologia e Citologia, Università degli Studi di Milano, via Celoria 26, 20133 Milano, Italy E-mail: carlo.polidori@unimi.it Carlo Polidori et al. 102 correlated with prey size. Overall, the predictions were all true for just one population. In conclusion, different factors probably influence often more than predator size the dynamics of individual prey specialization in wasps. Circumstantial evidences suggest that individual-biased exploitation of different hunting areas, some behavioural traits of prey, and different ratios between prey and wasp size may partially account for the observed patterns.
Strategic human resource management practices and organizational resilience

Purpose The purpose of this paper is to investigate the relationship between strategic human resource management (SHRM) practices and organizational resilience in a Tunisian democratic transition context. It is hypothesized that five SHRM practices influence three organizational resilience dimensions. Design/methodology/approach The research design is based on a deductive approach. The relations were checked over two periods by using quantitative methods. Questionnaires were addressed to top managers of resilient Tunisian companies. The hypotheses were verified after. Findings Results showed that SHRM practices affect the resilience dimensions. Analysis showed that SHRM practices enhance the robustness of firms, especially in the second period, and significantly influence agility and integrity. Practical implications Managers can use these findings to develop targeted actions in HRM to enhance a specific resilience dimension. They can make better decisions based on knowledge surrounding the precise effects of SHRM practices on resilience dimensions. Originality/value The authors highlighted the role of SHRM in developing organizational resilience. Gaps were noticed in the organizational resilience literature. This research is among the rare studies that have investigated the linkage between SHRM practices and organizational resilience. By using quantitative methods and adopting a longitudinal perspective for analyzing data, it leads to better identify the evolution of the influence of SHRM practices on each resilience dimension over time.
Development of robot soccer strategies by genetic programming util-ising a simulated environment

Motivation Robot soccer captures the fickle attention of the masses of the great unwashed long enough for money to be filched from their pockets. That is to say, the public finds great interest in the idea of robots playing soccer. In fact, humanoid robots or robots with human-like intelligence generally obtain much attention; the star of the movie Bicentennial Man, or the robotic companions in the cartoon The Jetsons, or 'Data' in the Star Trek series are all examples of this attraction. But the added interest of soccer (especially in Europe) makes this topic unbelievably exciting. At least, it is that excitement which the organisers of the robot soccer competitions hope to generate. The two main competitions (very independent, but similar) are RoboCup and MiroSot. Their current objectives have lower expectations than to see a team of humanoid robots running around after a soccer ball leading 2-1 over the humans after halftime. Nonetheless, [Kitano et al, 1998] makes it clear this is their final, albeit distant, goal. The authors also compare RoboCup with chess—a game 'conquered' by programmers when Deep Blue beat world-champion Kasparov in 1997. While the environment for chess is static, RoboCup is dynamic; Chess is turn-taking while RoboCup is real-time; in soccer, one player cannot see the entire field as a chess player can see their board and finally control is central in chess, whereas RoboCup demands a, more difficult, team effort. The soccer-playing domain is significantly more complex than that of chess and as such makes an excellent challenge. It can be said that much was promised, but very little delivered, in the early stages (circa 1970) of Artificial Intelligence (AI). This lack significantly reduced funding, and hence the work, in the field of AI. The Tokyo workshop in 1992 on Grand Challenges in Artificial Intelligence looked not only for interesting academic work to restore AI's status, but also work that could produce intermediate results that would be of interest outside academia. Perhaps the grand challenge of how to produce funding was solved when the workshop led to the development of RoboCup! Excluding funding issues, the realisation of humanoid soccer-playing robots has some interesting effects. The applicable techniques, to create such a marvel, are anything but obvious and so must be developed. The development will be done in stages—much like a river is not crossed in one big jump, but rather by hopping from stone to …
In Silico and In Vivo Anti-Malarial Studies of 18β Glycyrrhetinic Acid from Glycyrrhiza glabra

Malaria is one of the most prevailing fatal diseases causing between 1.2 and 2.7 million deaths all over the world each year. Further, development of resistance against the frontline anti-malarial drugs has created an alarming situation, which requires intensive drug discovery to develop new, more effective, affordable and accessible anti-malarial agents possessing novel modes of action. Over the past few years triterpenoids from higher plants have shown a wide range of anti-malarial activities. As a part of our drug discovery program for anti-malarial agents from Indian medicinal plants, roots of Glycyrrhiza glabra were chemically investigated, which resulted in the isolation and characterization of 18β-glycyrrhetinic acid (GA) as a major constituent. The in vitro studies against P. falciparum showed significant (IC50 1.69µg/ml) anti-malarial potential for GA. Similarly, the molecular docking studies showed adequate docking (LibDock) score of 71.18 for GA and 131.15 for standard anti-malarial drug chloroquine. Further, in silico pharmacokinetic and drug-likeness studies showed that GA possesses drug-like properties. Finally, in vivo evaluation showed a dose dependent anti-malarial activity ranging from 68–100% at doses of 62.5–250mg/kg on day 8. To the best of our knowledge this is the first ever report on the anti-malarial potential of GA. Further work on optimization of the anti-malarial lead is under progress.