Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward Distributing Autonomy over Robot Teams

This paper presents a way to command a system of systems robustly as a single entity. Instead of modeling each component system in isolation and then manually crafting interaction protocols, this approach starts with a model of the collective population as a single system. By compiling the model into separate elements for each component system and utilizing a teamwork model for coordination, it circumvents the complexities of manually crafting robust interaction protocols. The resulting system is both globally responsive by virtue of a team oriented interaction model and locally responsive by virtue of a distributed approach to planning as well as model-based fault detection, isolation, and recovery.
APRILab: Regulation Dilemma in South Harbor & Aalborg East, Denmark

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Effects of episodic acidification on Atlantic salmon (Salmo salar) smolts

The effect of episodic acidification on Atlantic salmon (Salmo salar) smolt physiology and survival in fresh water (FW) and seawater (SW) was investigated. Smolts were held in either ambient (control, pH 6.06.6), acidified (chronic, pH 4.46.1), or episodically acidified (episodic, pH reduction from control levels to pH ~5.2 for 48 h once weekly) river water for 31 days and then transferred to 34 SW. Smolts fed little while in acidified conditions and chronic smolts did not grow in length or weight. In FW, chronic smolts experienced increases in hematocrit and plasma potassium and reductions in plasma sodium and chloride. Upon transfer to SW, chronic and episodic smolts experienced reductions in hematocrit, increases in plasma sodium, chloride, and potassium levels, and suffered mortalities. Gill Na+,K+-ATPase and citrate synthase activities were reduced by exposure to acid. For most parameters, the effect of episodic acid exposure was less than that of chronic acidification. Exposure to acidic conditio.
Clozapine reduces severe self-mutilation and aggression in psychotic patients with borderline personality disorder.

BACKGROUND Clozapine has been reported to be effective in diminishing violence toward others in psychotic patients. This article describes the impact of clozapine on severe self-mutilation among patients with the dual diagnoses of borderline personality disorder and persistent psychoses. METHOD Seven subjects known to the authors were selected for careful chart audits. These subjects had been admitted to 2 state psychiatric hospitals owing to severe self-mutilation and/or violence and subsequently treated with clozapine. A mirror-image design anchored to the start date of clozapine treatment and extending in either direction to a maximum of 1 year was used to extract data. Data extracted included incidents of self-mutilation (restraint), seclusion, the as and when needed (p.r.n.) use of medications, injuries to staff and peers, hospital privileges, and Global Assessment of Functioning (GAF) scores. RESULTS The subjects were all white women with a mean age of 37 years. All subjects carried DSM-III-R or DSM-IV borderline personality disorder diagnoses and an Axis I disorder diagnosis. They had received trials of several psychotropic agents, often in combination and mostly without benefit. After clozapine treatment, there were statistically significant reductions in incidents of self-mutilation (restraint), seclusion, the use of p.r. n. antianxiety medications, and injuries to staff and peers. These subjects received higher levels of hospital privileges, and their GAF scores nearly doubled following clozapine treatment. Four subjects were subsequently discharged from hospital. CONCLUSION These preliminary but nonetheless favorable results suggest that clozapine deserves careful consideration for a controlled study in patients with borderline personality disorder and psychoses, especially if the clinical issues include severe self-mutilation, aggression, and violence. Until such studies are done, the risk-to-benefit ratio of clozapine treatment needs to be carefully evaluated on an individualized basis in such subjects.
Hepatitis C Virus Proteins Activate NRF2/ARE Pathway by Distinct ROS-Dependent and Independent Mechanisms in HUH7 Cells

Hepatitis C virus (HCV) is a highly pathogenic human virus associated with liver fibrosis, steatosis, and cancer. In infected cells HCV induces oxidative stress. Here, we show that HCV proteins core, E1, E2, NS4B, and NS5A activate antioxidant defense Nrf2/ARE pathway via several independent mechanisms. This was demonstrated by the analysis of transient co-expression in Huh7 cells of HCV proteins and luciferase reporters. Expression, controlled by the promoters of stress-response genes or their minimal Nrf2-responsive elements, was studied using luminescence assay, RT-qPCR and/or Western-blot analysis. All five proteins induced Nrf2 activation by protein kinase C in response to accumulation of reactive oxygen species (ROS). In addition, expression of core, E1, E2, NS4B, and NS5A proteins resulted in the activation of Nrf2 in a ROS-independent manner. The effect of core and NS5A was mediated through casein kinase 2 and phosphoinositide-3 kinase, whereas those of NS4B, E1, and E2, were not mediated by either PKC, CK2, PI3K, p38, or ERK. Altogether, on the earliest stage of expression HCV proteins induced a strong up-regulation of the antioxidant defense system. These events may underlie the harmful effects of HCV-induced oxidative stress during acute stage of hepatitis C.
Rapid, generalized adaptation to asynchronous audiovisual speech

The brain is adaptive. The speed of propagation through air, and of low-level sensory processing, differs markedly between auditory and visual stimuli; yet the brain can adapt to compensate for the resulting cross-modal delays. Studies investigating temporal recalibration to audiovisual speech have used prolonged adaptation procedures, suggesting that adaptation is sluggish. Here, we show that adaptation to asynchronous audiovisual speech occurs rapidly. Participants viewed a brief clip of an actor pronouncing a single syllable. The voice was either advanced or delayed relative to the corresponding lip movements, and participants were asked to make a synchrony judgement. Although we did not use an explicit adaptation procedure, we demonstrate rapid recalibration based on a single audiovisual event. We find that the point of subjective simultaneity on each trial is highly contingent upon the modality order of the preceding trial. We find compelling evidence that rapid recalibration generalizes across different stimuli, and different actors. Finally, we demonstrate that rapid recalibration occurs even when auditory and visual events clearly belong to different actors. These results suggest that rapid temporal recalibration to audiovisual speech is primarily mediated by basic temporal factors, rather than higher-order factors such as perceived simultaneity and source identity.
Biowaste compost in long-term soil fertilization: nutrients and non-essential elements in crops

Dipartimento di Chimica e Biologia “Adolfo Zambelli”, Università degli Studi di Salerno, Via Giovanni Paolo II 132, 84084, Fisciano (SA), Italy Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (CREA) Centro di Ricerca Cerealicoltura e Colture Industriali, Via Torrino 2, 81100, Caserta, Italy
An efficient, robust, and fast converging principal components extraction algorithm: SIPEX-G

Principal Components Analysis (PCA) is a very important statistical tool in signal processing, which has found successful applications in numerous engineering problems as well as other fields. In general, an on-line algorithm to adapt the PCA network to determine the principal projections of the input data is desired. The authors have recently introduced a fast, robust, and efficient PCA algorithm called SIPEX-G without detailed comparisons and analysis of performance. In this paper, we investigate the performance of SIPEX-G through Monte Carlo runs on synthetic data and on realistic problems where PCA is applied. These problems include direction of arrival estimation and subspace Wiener filtering.
Systematic Exploitation of Multiple Receptor Conformations for Virtual Ligand Screening

The role of virtual ligand screening in modern drug discovery is to mine large chemical collections and to prioritize for experimental testing a comparatively small and diverse set of compounds with expected activity against a target. Several studies have pointed out that the performance of virtual ligand screening can be improved by taking into account receptor flexibility. Here, we systematically assess how multiple crystallographic receptor conformations, a powerful way of discretely representing protein plasticity, can be exploited in screening protocols to separate binders from non-binders. Our analyses encompass 36 targets of pharmaceutical relevance and are based on actual molecules with reported activity against those targets. The results suggest that an ensemble receptor-based protocol displays a stronger discriminating power between active and inactive molecules as compared to its standard single rigid receptor counterpart. Moreover, such a protocol can be engineered not only to enrich a higher number of active compounds, but also to enhance their chemical diversity. Finally, some clear indications can be gathered on how to select a subset of receptor conformations that is most likely to provide the best performance in a real life scenario.
A novel generative encoding for exploiting neural network sensor and output geometry

A significant problem for evolving artificial neural networks is that the physical arrangement of sensors and effectors is invisible to the evolutionary algorithm. For example, in this paper, directional sensors and effectors are placed around the circumference of a robot in analogous arrangements. This configuration ensures that there is a useful geometric correspondence between sensors and effectors. However, if sensors are mapped to a single input layer and the effectors to a single output layer (as is typical), evolution has no means to exploit this fortuitous arrangement. To address this problem, this paper presents a novel generative encoding called connective Compositional Pattern Producing Networks (connective CPPNs) that can effectively detect and capitalize on geometric relationships among sensors and effectors. The key insight is that sensors and effectors with consistent geometric relationships can be exploited by a repeating motif in the neural architecture. Thus, by employing an encoding that can discover such motifs as a function of network geometry, it becomes possible to exploit it. In this paper, a method for evolving connective CPPNs called Hypercube-based Neuroevolution of Augmenting Topologies (HyperNEAT) discovers sensible repeating motifs that take advantage of two different placement schemes, demonstrating the utility of such an approach.
Memory-enhanced Evolutionary Robotics: The Echo State Network Approach

Interested in Evolutionary Robotics, this paper focuses on the acquisition and exploitation of memory skills. The targeted task is a well-studied benchmark problem, the Tolman maze, requiring in principle the robotic controller to feature some (limited) counting abilities. An elaborate experimental setting is used to enforce the controller generality and prevent opportunistic evolution from mimicking deliberative skills through smart reactive heuristics. The paper compares the prominent NEAT approach, achieving the non-parametric optimization of Neural Nets, with the evolutionary optimization of Echo State Networks, pertaining to the recent field of Reservoir Computing. While both search spaces offer a sufficient expressivity and enable the modelling of complex dynamic systems, the latter one is amenable to robust parametric, linear optimization with Covariance Matrix Adaptation-Evolution Strategies.
Evaluating the usability of recent consumer-grade 3D input devices

Recently, 3D input devices such as the Microsoft Kinect sensor or the Leap Motion controller became increasingly popular — the later specialized in recognizing hand-gestures, advertising a very precise localization of tools and fingers. Such devices promise to enable a touchless interaction with the computer in three-dimensional space enabling the design of entirely new user interfaces for natural 3D-modeling. However, while implementing a modeling application we found that there are still fundamental problems that can not easily be solved: The lack of a precise and atomic gesture for enabling and disabling interaction (clicking gesture) and a poor human depth perception and localization within an invisible coordinate frame. In this paper, we show why the precision of the interaction is not limited by hardware but software constraints.
2-D P-SV and SH spectral element modelling of seismic wave propagation in non-linear media with pore-pressure effects

It has long been recognised that the effects of superﬁcial geological layers, or site effects, can play a major role on the seismic ground motion at the free surface. In this study, we com-pute wave propagation in a 2D asymmetrical basin considering both soil nonlinearity and pore-pressure effects. Equations of elastodynamics of wave propagation are solved using the spectral element method (SEM). The geometry of the basin gives rise to basin-edge generated waves, that are different for in-plane (P-SV) and out-of-plane (SH) wave propagation and resulting in different nonlinear response. Moreover, the excess-pore pressure development in superﬁcial liqueﬁable layers (effective stress analysis) brings larger deformation and loss of strength than the analysis without pore-pressure effects (total stress analysis). The coupling of vertically propagating waves and the waves speciﬁcally generated in 2D model leads to waves whose amplitude and duration are higher than the 1D case. This multi-dimensional effect increases material nonlinearity. Such complex waveﬁeld provokes larger deformation and higher pore-pressure rise that cannot be predicted by 1D modelling. Therefore, our paper suggests the use of multi-dimensional modelling while studying seismic wave propagation in both linear and nonlinear complex media.
Patient-Satisfaction Measures in Anesthesia: Qualitative Systematic Review

Patient satisfaction is an important measure of the quality of health care and is used as an outcome measure in interventional and quality improvement studies. Previous studies have found that there are few appropriately developed and validated questionnaires available. The authors conducted a systematic review to identify all tools used to measure patient satisfaction with anesthesia, which have undergone a psychometric development and validation process, appraised the quality of these processes, and made recommendations of tools that may be suitable for use in different clinical and academic settings. There are a number of robustly developed and subsequently validated instruments, however, there are still many studies using nonvalidated instruments or poorly developed tools, claiming to accurately assess satisfaction with anesthesia. This can lead to biased and inaccurate results. Researchers in this field should be encouraged to use available validated tools, to ensure that patient satisfaction is measured and reported fairly and accurately.
Nanoparticles for Imaging, Sensing, and Therapeutic Intervention

Nanoparticles have the potential to contribute to new modalities in molecular imaging and sensing as well as in therapeutic interventions. In this Nano Focus article, we identify some of the current challenges and knowledge gaps that need to be confronted to accelerate the developments of various applications. Using specific examples, we journey from the characterization of these complex hybrid nanomaterials; continue with surface design and (bio)physicochemical properties, their fate in biological media and cells, and their potential for cancer treatment; and finally reflect on the role of animal models to predict their behavior in humans.
An efficient algorithm for mining frequent maximal and closed itemsets

The mining of frequent patterns is a basic problem in data mining applications. Frequent maximal and closed itemsets mining has become an important alternative of association rule mining. In this paper we present an effective algorithm which based on the blanket approach for mining all frequent maximal & closed itemsets. The performance of the proposed algorithm had been compared with recently developed algorithms. The results show how the proposed algorithm gives better performance. This is achieved by examining the performance and functionality of the proposed technique.
INVESTIGATING THE APPLICABILITY OF DIFFERENT THERMAL COMFORT MODELS IN NATURALLY VENTILATED CLASSROOMS IN KUWAIT

A field study to investigate the applicability of different thermal comfort indices was conducted for Kuwait classrooms under naturally ventilated environment, to assess the thermal conditions during the school day. In Kuwait, the girls' and boys' schools are completely segregated in all academic levels, thus offering a wide range to investigate the differences in thermal comfort sensations between both genders. A modified thermal comfort questionnaire was used to collect responses from pupils at specific age group (11-17 years old) while measuring the thermal comfort variables at the same time. The data was analyzed for both genders, using the different thermal comfort models. All the thermal comfort indices and equations, except for PMV10, showed agreement in predicting the student's thermal sensations. The PMV10 model showed to be under predicting the student's actual mean thermal comfort sensation for both genders. The different thermal comfort models used, except for PMV10, indicate slightly higher neutral temperature values than that resulted from the students' Actual Mean Vote (AMV). A difference of 1.2 o C in neutral temperature was found between both genders. The students' neutral temperature during this naturally ventilated mode in Kuwait is lower than that indicated in tropical and sub-tropical climatic zones.
The regional assessment report on biodiversity and ecosystem services for Africa : summary for policymakers

Citation: Stringer, L. , Osman-Elasha, B. , DeClerck, F. , Gebremikael, M. B. , Barau, A. S. , Denboba, M. A. , Diallo, M. , Molua, E. , Ngenda, G. , Pereira, L. ORCID: 0000-0002-49967234, Rahlao, S. , Kalemba, M. M. , Ojino, J. A. , Belhabib, D. , Sitas, N. , StrauS, L. and Ward, C. Options for governance and decision-making across scales and sectors. In: Archer, E. , Dziba, L. , Mulongoy, K-J., Maoela, A. and Walters, A. (Eds.), The IPBES regional assessment report on biodiversity and ecosystem services for Africa. (pp. 353-414). Bonn, Germany: Secretariat of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. ISBN 978-3-947851-05-8
GABAA and GABAB antagonists differentially affect the firing pattern of substantia nigra dopaminergic neurons in vivo

The effects of local pressure application of the selective GABAA antagonists, bicuculline, gabazine, and picrotoxin, and the selective GABAB antagonists, 2‐OH‐saclofen and CGP‐55845A, on the spontaneous activity of electrophysiologically identified substantia nigra dopaminergic neurons were recorded in vivo in urethane anesthetized rats. Blockade of GABAA inputs by bicuculline powerfully and reversibly induced burst firing in dopaminergic neurons along with a modest (25%) increase in firing rate, but the increase in burst firing was not correlated with the increase in firing rate. Picrotoxin and gabazine also produced an increase in burst firing without an increase in firing rate. In contrast, local application of GABAB antagonists did not produce bursting but rather caused a modest shift to a more regular firing pattern in 50% of the cases. These data demonstrate that dopaminergic neurons in vivo are under tonic GABAergic inhibition mediated by GABAA receptors and suggest that GABAergic afferents to substantia nigra comprise a major pathway by which the firing pattern of dopaminergic neurons is controlled in vivo. Synapse 32:165–176, 1999. © 1999 Wiley‐Liss, Inc.
LogiQL: A Declarative Language for Enterprise Applications

We give an overview of LogiQL, a declarative, Datalog based language for data management and analytics, along with techniques for efficient evaluation of LogiQL programs, emphasizing theoretical foundations when possible. These techniques include: leapfrog triejoin and its associated incremental maintenance algorithm, which we measure against appropriate optimality criteria; purely-functional data structures, which provide elegant versioning and branching capabilities that are indispensable for LogiQL; and transaction repair, a lock-free concurrency control scheme that uses LogiQL, incremental maintenance, and purely-functional data structures as essential ingredients.
ParaSAIL: Bitmap Indexing Using Many Cores

In large IoT systems, many millions of records reach back-end servers every second from devices that generate data automatically and continuously. The receiving servers have to process and store these high volumes of data and support interactive ad-hoc and real-time queries that require data to be searched quickly. Servers typically create bitmap indexes to reduce the quantity of data that needs to be examined to find needles in haystacks. Building a bitmap index, particularly when data continues to arrive at high rate, incurs appreciable CPU consumption. Memory efficiency also becomes a concern as bitmap indexes can take up space in proportion with the numbers of logical fields per record -- rather than the actual numbers of fields populated with data. This paper describes a bitmap index creation method called ParaSAIL (for Parallel Sets of Aligned Index Lines). ParaSAIL focuses on maximizing the speedup from parallel execution by avoiding write-write and write-read cache line conflicts among CPUs. It is thus well positioned to benefit from systems with high numbers of cores -- from mainstream multicore processors such as Intel® Xeon® E5 and E7 machines, to many-core engines such as Intel® Xeon PhiTM coprocessors. ParaSAIL also obtains space efficiencies by creating a clustered bitmap index for an attribute value or range that only occurs intermittently in the data. An evaluation using data from an oceanographic dataset shows that ParaSAIL running on Xeon Phi coprocessor system indexes 473 million records per second and produces dense bitmaps that don't require further compression.
Upper and Lower Bounds for Programmable Vector Fields with Applications to MEMS and Vibratory Plate Parts Feeders

Programmable vector elds can be used to control a variety of exible planar parts feeders. These devices can exploit exotic actuation technologies such as arrayed, massively-parallel microfabricated motion pixels or transversely vibrating (macroscopic) plates. These new automation designs promise great exibility, speed, and dexterity|we believe they may be employed to orient, singulate, sort, feed, and assemble parts. However, since they have only recently been invented, programming and controlling them for manipulation tasks is challenging. When a part is placed on our devices, the programmed vector eld induces a force and moment upon it. Over time, the part may come to rest in a dynamic equilibrium state. By chaining together sequences of vector elds, the equilibrium states of a part in the eld may be cascaded to obtain a desired nal state. The resulting strategies require no sensing and enjoy e cient planning algorithms.