Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting homogeneous nucleation rate from atomistic simulations

Nucleation is ubiquitous, from the formation of clouds to the preparation of pharmaceutical compounds, from metal casting to the tempering of chocolates, and from the growth of beautiful nautilus shells to the assembly of microtubules in cells. The first experiment for observing a nucleation event was performed by Fahrenheit in 1724, and it can be easily replicated in a kitchen: simply place a bottle of purified water in the freezer. The liquid water can be cooled to far below zero degrees Celsius without freezing due to the lack of microscopic nuclei, which are the embryos from which the freezing phase transition can occur. After that, shaking the bottle will induce nucleation which in turn prompts a rapid ice crystallization. Despite its pivotal importance and long history, we only have a rough idea about the underlying mechanism of nucleation. The classical nucleation theory says that, during the growth of a nucleus inside a bulk phase, an interface that surrounds the nucleus has to be created. This interface is associated with an energy penalty, which the system has to overcome for the nucleus to grow into a critical size which precedes an avalanche of structural transitions. It is analogous to being stuck in a valley on the Alps, so that a great deal of time and energy have to be spent to climb over a peak in order to reach another valley. And yet, we have not reached a quantitative understanding of how high the energy barrier is and how long is the waiting time of nucleation for specific systems. Taking again the example of ice nucleation from bulk liquid water, there has been a long-standing discrepancy by more than 10 orders of magnitude between the measured and the predicted expectation time of nucleation. While the classical nucleation theory is able to paint a physical picture of nucleation, for many systems it is insufficient and thus needs extension. Despite substantial improvements in recent years, experimental characterization of the dynamical nucleation processes is extremely difficult, which motivates atomistic modelling efforts that use numerical simulation techniques. However, atomistic simulations also faces a number of challenges: firstly the typical time scales accessible to atomistic simulations are confined to below microseconds, while nucleation can take hours or days to occur. We have mitigated the challenge by employing state-of-the-art enhanced sampling methods in the simulation studies of nucleation [1–5]. In a nutshell, instead of naively waiting for a rare event to happen, we place a bias to help the system overcome the energy penalty of nucleation. To return to the earlier analogy with Alpine hiking, we can flatten out the Alps by depositing (a lot of) sand into all the valleys, making the landscape level and easy to explore. Secondly, only microscopic quantities such as the coordinates and the velocities of each atom can be directly obtained from simulations. On the contrary, macroscopic observables
Semantic Queries with Pictures: The VIMSYS Model

The goal of the VIMSYS project is to create an information management system that can retrieve images or parts of images in addition to textual data. The system allows users to incrementally formulate a query starting from semantic pictorial objects. 11 allows incompletely specified and similarity-based queries. This paper presents a new layered data model and the design of the query processing unit for this system. The data model is a combination of object-oriented and functional models, and permits multiple representations of image entities. The knowledge module guides the user to progrcssively refine similarity-based queries and to query by defining new semantic objects and composing its attributes. Design considerations for the access structure of the system are also discussed, alongwith some of the problems of creating efficient mecha-
Sharing narrative and experience: digital stories and portraits at a women's centre

We present our work-in-progress designing technologies to foster social connection with isolated immigrant women in the UK. We report our preliminary studies using digital storytelling and digital portrait methods with participants at a Black, Asian and Minority Ethnic (BAME) centre supporting women who have experiences of domestic violence. While these methods have provided valuable insights, in contexts where participants feel vulnerable and cultural diversity is the norm, HCI's conventional assumptions about storytelling and probe use cannot be taken for granted. We describe our rationale for the adaptation of methods and tensions highlighted through the process.
Exact polyhedral visual hulls

We propose an exact method for efficiently and robustly computing the visual hull of an object from image contours. Unlike most existing approaches, ours computes an exact description of the visual hull polyhedron associated to polygonal image contours. Furthermore, the proposed approach is fast and allows real-time recovery of both manifold and watertight visual hull polyhedra. The process involves three main steps. First, a coarse geometrical approximation of the visual hull is computed by retrieving its viewing edges, an unconnected subset of the wanted mesh. Then, local orientation and connectivity rules are used to walk along the relevant viewing cone intersection boundaries, so as to iteratively generate the missing surface points and connections. A final connection walkthrough allows us to identify the planar contours for each face of the polyhedron. Implementation details and results with synthetic and real data are presented.
Integrating and Scheduling an Open Set of Static Analyses

To improve the productivity of the development process, more and more tools for static software analysis are tightly integrated into the incremental build process of an IDE. If multiple interdependent analyses are used simultaneously, the coordination between the analyses becomes a major obstacle to keep the set of analyses open. We propose an approach to integrating and scheduling an open set of static analyses which decouples the individual analyses and coordinates the analysis executions such that the overall time and space consumption is minimized. The approach has been implemented for the Eclipse IDE and has been used to integrate a wide range of analyses such as finding bug patterns, detecting violations of design guidelines, or type system extensions for Java
The Predictive Audit Framework

Assurance is an essential part of the business process of the modern enterprise. Auditing is a widely used assurance method made mandatory for public companies since 1934. The traditional (retroactive) audit provides after-the-fact audit reports, and is of limited value in the ever changing modern business environment because it is slow and backwards looking. Contemporary auditing and monitoring technologies could shorten the audit and assurance time frame. This paper proposes the predictive audit, a forward looking contemporary audit that will bring the assurance processes, financial and non-financial, closer to the corresponding events. Rather than merely looking backward to historical data and past errors or anomalies, a predictive audit will identify possible exceptions proactively by comparing each transaction to a normative model before that transaction is executed. The paper also discusses the possibility of performing a predictive audit in a preventive manner � a preventive audit where transactions are blocked prior to execution.
The design and evaluation of a pipelined image compositing device for massively parallel volume rendering

An experimental study of software image compositing that we have carried out on a 512-node PC cluster shows the necessity of hardware compositing support to make possible real-time volume visualization scalable with large PC clusters. This paper describes the design and performance evaluation of such a hardware image compositing device. A PC cluster using such devices along with commodity graphics cards can enable simultaneous simulation and volume visualization.
Use of Particle Tracking to Determine Optimal Release Dates and Locations for Rehabilitated Neonate Sea Turtles

Sea turtles found stranded on beaches are often rehabilitated before being released back into the wild. The location and date of release is largely selected on an informal basis, which may not maximise the chance of survival. As oceanic conditions have a large influence on the movements of neonate sea turtles, this study aimed to identify the best locations and months to release rehabilitated sea turtles that would assist in their transport by ocean currents to the habitat and thermal conditions required for their survival. A particle tracking model, forced by ocean surface velocity fields were used to simulate the dispersal pathways of millions of passively drifting particles released from different locations in Western Australia. The particles represented rehabilitated, neonate turtles requiring oceanic habitats (green (Chelonia mydas), hawksbill (Eretmochelys imbricata) and loggerheads (Caretta caretta)) and flatback turtles (Natator depressus) which require neritic habitats. The results clearly identified regions and months where ocean currents were more favourable for transport to suitable habitats. Tantabiddi, near Exmouth on the north-west coast, was consistently the best location for release for the oceanic species, with dominant offshore-directed currents and a very narrow continental shelf reducing the time taken for particles to be transported into deep water. In contrast, release locations with more enclosed geography, wide continental shelves, and/or proximity to cooler ocean temperatures were less successful. Our results produced a decision support system for the release of neonate marine turtles in Western Australia and our particle tracking approach has global transferability.
A biologically inspired active compliant joint using local positive velocity feedback (LPVF)

Starting from studies which revealed that positive feedback is found in the control system for walking in arthropods, we have constructed a new positive feedback driven joint that can be used for solving compliant motion tasks. We propose two different joint constructions each of which shows passive compliance. Based on these joints we introduce three different local positive velocity feedback (LPVF) controllers and discuss their properties in the context of motion generation in closed kinematic chains. The third circuit named undelayed dLPVF is used for the control of a compliant planar manipulator which turns a crank. Our concept is of highly decentralized nature and follows the idea of embodiment. In our case this means that a process which is controlled by LPVF controllers reveals its nature when the controllers interact with this process.
A Comparison of Conventional Collagen Sponge and Collagen-Gelatin Sponge in Wound Healing

The objective of this study was to compare the effectiveness of the collagen-gelatin sponge (CGS) with that of the collagen sponge (CS) in dermis-like tissue regeneration. CGS, which achieves the sustained release of basic fibroblast growth factor (bFGF), is a promising material in wound healing. In the present study, we evaluated and compared CGSs and conventional CSs. We prepared 8 mm full-thickness skin defects on the backs of rats. Either CGSs or CSs were impregnated with normal saline solution (NSS) or 7 μg/cm2 of bFGF solution and implanted into the defects. At 1 and 2 weeks after implantation, tissue specimens were obtained from the rats of each group (n = 3, total n = 24). The wound area, neoepithelial length, dermis-like tissue area, and the number and area of capillaries were evaluated at 1 and 2 weeks after implantation. There were no significant differences in the CGS without bFGF and CS groups. Significant improvements were observed in the neoepithelial length, the dermis-like tissue area, and the number of newly formed capillaries in the group of rats that received CGSs impregnated with bFGF. The effects on epithelialization, granulation, and vascularization of wound healing demonstrated that, as a scaffold, CGSs are equal or superior to conventional CSs.
Autonomous Driving: Investigating the Feasibility of Bimodal Take-Over Requests

Autonomous vehicles will need de-escalation strategies to compensate when reaching system limitations. Car-driver handovers can be considered one possible method to deal with system boundaries. The authors suggest a bimodal auditory and visual handover assistant based on user preferences and design principles for automated systems. They conducted a driving simulator study with 30 participants to investigate the take-over performance of drivers. In particular, the authors examined the effect of different warning conditions take-over request only with 4 and 6 seconds time budget vs. an additional pre-cue, which states why the take-over request will follow in different hazardous situations. Their results indicated that all warning conditions were feasible in all situations, although the short time budget 4 seconds was rather challenging and led to a less safe performance. An alert ahead of a take-over request had the positive effect that the participants took over and intervened earlier in relation to the appearance of the take-over request. Overall, the authors' evaluation showed that bimodal warnings composed of textual and iconographic visual displays accompanied by alerting jingles and spoken messages are a promising approach to alert drivers and to ask them to take over.
Composite structure of the crystalline epicuticular wax layer of the slippery zone in the pitchers of the carnivorous plant Nepenthes alata and its effect on insect attachment

SUMMARY The slippery zone situated below the peristome inside pitchers of most carnivorous plants from the genus Nepenthes is covered with a thick layer of epicuticular wax. This slippery zone is reported to play a crucial role in animal trapping and prey retention. In N. alata, the wax coverage consists of two clearly distinguished layers. These layers differ in their structure, chemical composition and mechanical properties, and they reduce the insect attachment in different ways. The lower layer resembles foam, composed of interconnected membraneous platelets protruding from the surface at acute angles. The upper layer consists of densely placed separate irregular platelets, located perpendicular to the subjacent layer. Crystals of the upper layer bear small stalks, directed downwards and providing connections to the lower layer. These morphological distinctions correlate with differences in the chemical composition of waxes. The compound classes of alkanes, aldehydes, primary alcohols, free fatty acids, esters and triterpenoids occurred in extracts from both wax layers, but in different proportions. Chain length distributions in aliphatics were different in extracts from the lower and the upper wax layers. Waxes of the upper and lower layers exhibited different mechanical properties: wax of the lower layer is harder and stiffer than that of the upper layer. Moreover, crystals of the upper layer are brittle and may be easily exfoliated or broken to tiny pieces. Laboratory experiments using tethered insects showed that both wax layers reduce the attachment force of insects. It is assumed that a decrease in insect attachment on the two distinct wax layers is provided by the two different mechanisms: (1) crystals of the upper wax layer contaminate insects' adhesive pads; (2) the lower wax layer leads to a reduction of the real contact area of insects' feet with the plant surface.
RGB-D Object Recognition Using Deep Convolutional Neural Networks

We address the problem of object recognition from RGB-D images using deep convolutional neural networks (CNNs). We advocate the use of 3D CNNs to fully exploit the 3D spatial information in depth images as well as the use of pretrained 2D CNNs to learn features from RGB-D images. There exists currently no large scale dataset available comprising depth information as compared to those for RGB data. Hence transfer learning from 2D source data is key to be able to train deep 3D CNNs. To this end, we propose a hybrid 2D/3D convolutional neural network that can be initialized with pretrained 2D CNNs and can then be trained over a relatively small RGB-D dataset. We conduct experiments on the Washington dataset involving RGB-D images of small household objects. Our experiments show that the features learnt from this hybrid structure, when fused with the features learnt from depth-only and RGB-only architectures, outperform the state of the art on RGB-D category recognition.
Unplannability IPC Track

The majority of research in the field of automated planning focuses on the synthesis of plans for problems that are solvable. We propose an IPC track to focus on the important and understudied area of unplannibility: proving that a planning problem is unsolvable. We will focus on classical planning problems, as methods for determining whether or not unplannability can have wider applications for classical planning problems (e.g., recognizing and avoiding deadends in the state space) as well as solving planning problems with uncertainty (e.g., identifying when a deterministic approximation of the problem is unsolvable). The unplannability track follows similar contests in other fields; for example, the UNSAT track for the field of Boolean Satisfiability. In a similar vein, we hope that the introduction of an unplannability track will foster new innovation for techniques dedicated to identifying planning problems that cannot be solved.
Cutting Edge: Activation by Innate Cytokines or Microbial Antigens Can Cause Arrest of Natural Killer T Cell Patrolling of Liver Sinusoids1

Natural killer T (NKT) cells are innate-like lymphocytes that rapidly secrete large amounts of effector cytokines upon activation. Recognition of α-linked glycolipids presented by CD1d leads to the production of IL-4, IFN-γ, or both, while direct activation by the synergistic action of IL-12 and IL-18 leads to IFN-γ production only. We previously reported that in vitro cultured dendritic cells can modulate NKT cell activation and, using intravital fluorescence laser scanning microscopy, we reported that the potent stimulation of NKT cells results in arrest within hepatic sinusoids. In this study, we examine the relationship between murine NKT cell patrolling and activation. We report that NKT cell arrest results from activation driven by limiting doses of a bacteria-derived weak agonist, galacturonic acid-containing glycosphingolipid, or a synthetic agonist, α-galactosyl ceramide. Interestingly, NKT cell arrest also results from IL-12 and IL-18 synergistic activation. Thus, innate cytokines and natural microbial TCR agonists trigger sinusoidal NKT cell arrest and an effector response.
Efficient Access to Temporally Overlaying Spatial and Textual Trajectories

In this paper we deal with the problem of querying heterogeneous trajectory data consisting of spatial and textual trajectories defined over continuous temporal domains. In contrast with spatial trajectories, which describe the continuous movement in space of an individual, the textual trajectories of concern in this work describe the individual's step-wise changing behavior, such as the transportation means used and the activities performed in a time period. Accessing large datasets of temporally aligned spatial and textual trajectories can provide valuable information on where certain behaviors take place. In this paper we present a novel index framework, called IRWI, for the efficient processing of queries on aligned spatio-textual trajectories formulated as sequences of ordered spatio-textual range queries q = q1, . , qn (sequenced queries). IRWI consists of a hybrid, spatial and textual, index data structure, enriched with a number of features that facilitate the early pruning of trajectories during the concurrent evaluation of the sub-queries q1, . , qn. As a result, the IRWI tree can be traversed only once. The experiments, conducted on both synthetic and real datasets, show a gain in performance with respect to state-of-the art techniques that increases significantly with the length of the query sequence.
Research Reports in Oral and Maxillofacial Surgery Efficacy of Platelet-Rich Fibrin in Bone Regeneration of the Jaws: A Systematic Review

Objective: To analyze the effects of Platelet-rich fibrin (PRF) in bone regeneration procedures of the jaws. Materials and methods: The search was conducted from 2012 to 2017 in databases (MEDLINE/PubMed, Cochrane, EMBASE, Epistemonikos). Randomized clinical trials (RCTs) were included for the qualitative analysis and systematic reviews (SRs) found in the search were analyzed independently with AMSTAR. Results: 5 RCTs were selected and analyzed qualitatively, 4 articles (1 RCT and 3 SRs) evaluated results in maxillary sinus lift surgery not showing differences using PRF compared to the traditional technique. For bone regeneration of the alveolar ridge, 2 RCTs indicated that PRF in combination with autogenous bone improves bone volume. 3 articles evaluated alveolar preservation (1 RCT and 2 SRs) demonstrating that there may be an increase in the density of neoformed bone in the long term with a lower rate of buccal/ lingual reabsorption. The articles also demonstrate that the use of PRF improves the healing of soft tissues during first 7 days as well as decreasing symptomatology. Finally, 4 studies (1 RCT and 3 SRs) evaluated the effect on infra-osseous periodontal defects in which the PRF showed to be effective, improving parameters such as clinical attachment level and probing depth in comparison with the control. There was considerable heterogeneity between the studies; therefore, they could not be analyzed quantitatively. Conclusions: The use of PRF appears to improve the local conditions of the grafts and soft tissues, reducing the healing times and symptoms. However, more RCTs and protocol standardization are required to obtain reproducible results.
The LAMA Planner: Guiding Cost-Based Anytime Planning with Landmarks

LAMA is a classical planning system based on heuristic forward search. Its core feature is the use of a pseudo-heuristic derived from landmarks, propositional formulas that must be true in every solution of a planning task. LAMA builds on the Fast Downward planning system, using finite-domain rather than binary state variables and multi-heuristic search. The latter is employed to combine the landmark heuristic with a variant of the well-known FF heuristic. Both heuristics are cost-sensitive, focusing on high-quality solutions in the case where actions have non-uniform cost. A weighted A* search is used with iteratively decreasing weights, so that the planner continues to search for plans of better quality until the search is terminated. LAMA showed best performance among all planners in the sequential satisficing track of the International Planning Competition 2008. In this paper we present the system in detail and investigate which features of LAMA are crucial for its performance. We present individual results for some of the domains used at the competition, demonstrating good and bad cases for the techniques implemented in LAMA. Overall, we find that using landmarks improves performance, whereas the incorporation of action costs into the heuristic estimators proves not to be beneficial. We show that in some domains a search that ignores cost solves far more problems, raising the question of how to deal with action costs more effectively in the future. The iterated weighted A* search greatly improves results, and shows synergy effects with the use of landmarks.