Miracle-dz/UniFAR-FTUs huggingface dataset:
A virtual modeling system for intuitive 3D shape conceptualization

We propose an approach to build a 3D modeling environment for aiding new shape conceptualization. The proposed system consists of the following four functional components: (a) a freehand sketch Interface to allow the user to easily bring his/her rough design idea into a 2D geometric model, (b) a shape approximation module (SAM) to automatically convert the sketched 2D image into a 3D deformable model, (c) a 3D shape exploration tool to generate variety of 3D models by evolving the converted 3D model, and (d) a parametric 3D modeler to sophisticate the evolved shapes. The freehand sketch Interface employs a fuzzy Inference technique to flexibly Identify a user's handwritten image as one of seven geometric primitives commonly used in many CAD tools. After the freehand sketch Is automatically converted to a 3D model by the SAM, the model Is evolved by using a technique called Interactive Evolutionary Computation (IEC). IEC automatically generates and deforms the model according to the user's rating and allows even beginners to easily produce interesting shapes. Advanced users and experts are encouraged to use parametric modeler to finish the model with elaboration.
Mimetic communication with impedance control for physical human-robot interaction

In this paper, mimetic communication is extended to human-robot interaction tasks, in which physical contact transitions must be handled. The mimetic communication consists of imitation learning for learning low level motion primitives and a higher level interaction learning stage in which also the information about the human-robot contacts is included. For the imitation learning, Cartesian marker data from a motion capture system is used. A modification of the low level marker trajectory following algorithm is presented, which allows to reshape the trajectory of the motion primitive in accordance with the human hand motion in real-time. Moreover, for performing safe contact motion, an appropriate impedance controller is integrated into the setting. All the presented concepts are evaluated in experiments with a humanoid robot.
CIGAR: Concurrent and Interleaving Goal and Activity Recognition

In artificial intelligence and pervasive computing research, inferring users' high-level goals from activity sequences is an important task. A major challenge in goal recognition is that users often pursue several high-level goals in a concurrent and interleaving manner, where the pursuit of goals may spread over different parts of an activity sequence and may be pursued in parallel. Existing approaches to recognizing multiple goals often formulate this problem either as a single-goal recognition problem or in a deterministic way, ignoring uncertainty. In this paper, we propose CIGAR (Concurrent and Interleaving Goal and Activity Recognition) - a novel and simple two-level probabilistic framework for multiple-goal recognition where we can recognize both concurrent and interleaving goals. We use skip-chain conditional random fields (SCCRF) for modeling interleaving goals and we model concurrent goals by adjusting inferred probabilities through a correlation graph, which is a major advantage in that we are able to reason about goal interactions explicitly through the correlation graph. The two-level framework also avoids the high training complexity when modeling concurrency and interleaving together in a unified CRF model. Experimental results show that our method can effectively improve recognition accuracies on several real-world datasets collected from various wireless and sensor networks.
Oxygen-Sensitive K+ Channels Modulate Human Chorionic Gonadotropin Secretion from Human Placental Trophoblast

Human chorionic gonadotropin (hCG) is a key autocrine/paracrine regulator of placental syncytiotrophoblast, the transport epithelium of the human placenta. Syncytiotrophoblast hCG secretion is modulated by the partial pressure of oxygen (pO2), reactive oxygen species (ROS) and potassium (K+) channels. Here we test the hypothesis that K+ channels mediate the effects of pO2 and ROS on hCG secretion. Placental villous explants from normal term pregnancies were cultured for 6 days at 6% (normoxia), 21% (hyperoxia) or 1% (hypoxia) pO2. On days 3–5, explants were treated with 5mM 4-aminopyridine (4-AP) or tetraethylammonium (TEA), blockers of pO2-sensitive voltage-gated K+ (KV) channels, or ROS (10–1000μM H2O2). hCG secretion and lactate dehydrogenase (LDH) release, a marker of necrosis, were determined daily. At day 6, hCG and LDH were measured in tissue lysate and 86Rb (K+) efflux assessed to estimate syncytiotrophoblast K+ permeability. hCG secretion and 86Rb efflux were significantly greater in explants maintained in 21% pO2 than normoxia. 4-AP/TEA inhibited hCG secretion to a greater extent at 21% than 6% and 1% pO2, and reduced 86Rb efflux at 21% but not 6% pO2. LDH release and tissue LDH/hCG were similar in 6%, 21% and 1% pO2 and unaffected by 4-AP/TEA. H2O2 stimulated 86Rb efflux and hCG secretion at normoxia but decreased 86Rb efflux, without affecting hCG secretion, at 21% pO2. 4-AP/TEA-sensitive K+ channels participate in pO2-sensitive hCG secretion from syncytiotrophoblast. ROS effects on both hCG secretion and 86Rb efflux are pO2-dependent but causal links between the two remain to be established.
On the comparison of performance, capacity and economics of terrestrial base station and high altitude platform based deployment of 4G

OFDM/OFDMA based physical layer, wide channel bandwidths and operation at higher frequency bands are the features common to all potential candidate 4G technologies in order to achieve unprecedented high data rates and better QoS. But these very features of 4G necessitate extraordinary small cell size in 4G Wireless Cellular Networks (WCN) to meet the link budgets. This makes an efficient and cost effective ubiquitous deployment solution for 4G WCNs a big challenge. This paper investigates two different deployment solutions for 4G WCNs and presents a comparison between them in terms of performance, capacity and deployment cost factors in relative terms. The first solution is conventional Terrestrial Base Stations based WCN with reduced cell size (TWCN) and second solution is 4G WCNs deployment via High Altitude Platform i.e. HWCN. WiMAX is taken as bench mark in this study as it is most well known standard that has all the aforementioned characterizing features of 4G technologies. The performance of HWCN and TWCN is evaluated through extensive system level simulations that model realistic details like link level performance, dynamic interference, and shadowing and propagation characteristics of the two systems. Effects of spectrum reuse factor, Adaptive Coding and Modulation (ACM) and user traffic type on the performance of two solutions are investigated and compared in detail. Finally a relationship between the relative deployment costs of the two systems is developed and used to assess the deployment costs of the two systems normalized over the capacity they offer in order to analyze their economic feasibility relative to each other.
Effect of spatio-temporal channel correlation on the performance of space-time codes

The determinant and rank criteria used for space-time code design apply at high SNR. Code design metrics developed for low SNR assume a channel autocorrelation matrix with equal eigenvalues, which does not hold in many practical scenarios. This paper shows that a space-time code designed to ensure full diversity at high SNR can suffer significant degradation when implemented at low-to-medium SNR because of the channel autocorrelation profile. We examine the effect of the channel autocorrelation matrix on a space-time code's performance and discuss how knowledge of this matrix can be used for code design, particularly from the aspect of space-time trellis code minimum memory requirements. Our discussion applies to both flat-fading and frequency-selective channels that are treated in a unified manner.
Preserving locality in MMVE applications based on ant clustering

Massively Multiuser Virtual Environment (MMVE) applications have the challenge of update message exchange among a large number of users. Real-time collaboration in the virtual environments requires the updates to be exchanged with the minimum end-to-end latency and overhead. This article proposes a new clustering technique to improve the update message exchange efficiency in MMVE applications. The proposed solution is based on the use of ant clustering technique in order to cluster the users based on their geographical proximity. These clusters can be used as localized routing regions in the hierarchical routing architecture and prevent local messages to be routed through long distance hops. Therefore, clustering can help to reduce both update exchange latency and underlay network traffic.
Level-Con uence of Conditional Rewrite Systems with Extra Variables in Right-Hand Sides

Level-con uence is an important property of conditional term rewriting systems that allow extra variables in the rewrite rules because it guarantees the completeness of narrowing for such systems. In this paper we present a syntactic condition ensuring level-con uence for orthogonal, not necessarily terminating, conditional term rewriting systems that have extra variables in the right-hand sides of the rewrite rules. To this end we generalize the parallel moves lemma. Our result bears practical signi cance since the class of systems that fall within its scope can be viewed as a computational model for functional logic programming languages with local de nitions, such as let-expressions and where-constructs.
A multi-stage segmentation based on inner-class relation with discriminative learning

In this paper, we proposed a segmentation approach that not only segment an interest object but also label different semantic parts of the object, where a discriminative model is presented to describe an object in real world images as multiply, disparate and correlative parts. We propose a multi-stage segmentation approach to make inference on the segments of an object. Then we train it under the latent structural SVM learning framework. Then, we showed that our method boost an average increase of about 5% on ETHZ Shape Classes Dataset and 4% on INRIA horses dataset. Finally, extensive experiments of intricate occlusion on INRIA horses dataset show that the approach have a state of the art performance in the condition of occlusion and deformation.
Effects of Molybdate and Tungstate on Expression Levels and Biochemical Characteristics of Formate Dehydrogenases Produced by Desulfovibrio alaskensis NCIMB 13491

ABSTRACT Formate dehydrogenases (FDHs) are enzymes that catalyze the formate oxidation to carbon dioxide and that contain either Mo or W in a mononuclear form in the active site. In the present work, the influence of Mo and W salts on the production of FDH by Desulfovibrio alaskensis NCIMB 13491 was studied. Two different FDHs, one containing W (W-FDH) and a second incorporating either Mo or W (Mo/W-FDH), were purified. Both enzymes were isolated from cells grown in a medium supplemented with 1 μM molybdate, whereas only the W-FDH was purified from cells cultured in medium supplemented with 10 μM tungstate. We demonstrated that the genes encoding the Mo/W-FDH are strongly downregulated by W and slightly upregulated by Mo. Metal effects on the expression level of the genes encoding the W-FDH were less significant. Furthermore, the expression levels of the genes encoding proteins involved in molybdate and tungstate transport are downregulated under the experimental conditions evaluated in this work. The molecular and biochemical properties of these enzymes and the selective incorporation of either Mo or W are discussed.
A hybrid cognitive transceiver architecture: Sensing-throughput tradeoff

Spectrum Sensing (SS) and underlay have been considered as two important techniques for enabling the spectral coexistence of the licensed and unlicensed wireless communication systems. The SS only approach ignores the interference tolerance capability of the Primary Users (PUs) while assuming the bursty PU traffic whereas the possibility of having secondary transmission with full power is neglected in an underlay based approach. To address this, it's crucial to investigate suitable hybrid spectrum awareness and transmission strategies which can overcome the aforementioned drawbacks and achieve higher secondary throughput while protecting the PUs. In this context, we propose a hybrid cognitive transceiver which combines the SS approach with the power control based underlay approach. Furthermore, we evaluate the performance of the proposed hybrid approach considering both periodic sensing and simultaneous sensing/transmission schemes. Moreover, sensing-throughput tradeoff for the proposed hybrid approach is investigated and the performance is compared with the conventional SS only approaches in terms of the achievable throughput. It is shown that the proposed scheme can achieve a significant improvement in the secondary throughput over the conventional approaches while respecting the interference constraints of the PUs.
Network models of criminal behavior

Criminal psychology is beginning to focus on modeling the effect of mental processes and environmental stimuli on offender behavior by Strano (2004). This article presents a knowledge-based-system approach to deriving empirical models of this behavior. The inputs to the system are the psychological characteristics and environmental variables that reflect the mental state of the offender and the circumstances of the crime, while criminal actions are viewed as the outputs. Although criminologists and psychologists can identify relevant input and output variables, the processes underlying criminal behavior are only partly understood and thus cannot be modeled from first principles.
A 64-point Fourier transform chip for high-speed wireless LAN application using OFDM

In this paper, we present a novel fixed-point 16-bit word-width 64-point FFT/IFFT processor developed primarily for the application in an OFDM-based IEEE 802.11a wireless LAN baseband processor. The 64-point FFT is realized by decomposing it into a two-dimensional structure of 8-point FFTs. This approach reduces the number of required complex multiplications compared to the conventional radix-2 64-point FFT algorithm. The complex multiplication operations are realized using shift-and-add operations. Thus, the processor does not use a two-input digital multiplier. It also does not need any RAM or ROM for internal storage of coefficients. The proposed 64-point FFT/IFFT processor has been fabricated and tested successfully using our in-house 0.25-/spl mu/m BiCMOS technology. The core area of this chip is 6.8 mm/sup 2/. The average dynamic power consumption is 41 mW at 20 MHz operating frequency and 1.8 V supply voltage. The processor completes one parallel-to-parallel (i.e., when all input data are available in parallel and all output data are generated in parallel) 64-point FFT computation in 23 cycles. These features show that though it has been developed primarily for application in the IEEE 802.11a standard, it can be used for any application that requires fast operation as well as low power consumption.
Adult Human Dental Pulp Stem Cells Differentiate Toward Functionally Active Neurons Under Appropriate Environmental Cues

Human adult dental pulp stem cells (DPSCs) reside within the perivascular niche of dental pulp and are thought to originate from migrating cranial neural crest (CNC) cells. During embryonic development, CNC cells differentiate into a wide variety of cell types, including neurons of the peripheral nervous system. Previously, we have demonstrated that DPSCs derived from adult human third molar teeth differentiate into cell types reminiscent of CNC embryonic ontology. We hypothesized that DPSCs exposed to the appropriate environmental cues would differentiate into functionally active neurons. The data demonstrated that ex vivo‐expanded human adult DPSCs responded to neuronal inductive conditions both in vitro and in vivo. Human adult DPSCs, but not human foreskin fibroblasts (HFFs), acquired a neuronal morphology, and expressed neuronal‐specific markers at both the gene and protein levels. Culture‐expanded DPSCs also exhibited the capacity to produce a sodium current consistent with functional neuronal cells when exposed to neuronal inductive media. Furthermore, the response of human DPSCs and HFFs to endogenous neuronal environmental cues was determined in vivo using an avian xenotransplantation assay. DPSCs expressed neuronal markers and acquired a neuronal morphology following transplantation into the mesencephalon of embryonic day‐2 chicken embryo, whereas HFFs maintained a thin spindle fibroblastic morphology. We propose that adult human DPSCs provide a readily accessible source of exogenous stem/precursor cells that have the potential for use in cell‐therapeutic paradigms to treat neurological disease.
Transactional Execution of Java Programs

Parallel programming is difficult due to the complexity of dealing with conventional lock-based synchronization. To simplify parallel programming, there have been a number of proposals to support transactions directly in hardware and eliminate locks completely. Although hardware support for transactions has the potential to completely change the way parallel programs are written, initially transactions will be used to execute existing parallel programs. In this paper we investigate the implications of using transactions to execute existing parallel Java programs. Our results show that transactions can be used to support all aspects of Java multithreaded programs. Moreover, the conversion of a lock-based application into transactions is largely straightforward. The performance that these converted applications achieve is equal to or sometimes better than the original lock-based implementation.
Demonstration Abstract: Accelerating Embedded Deep Learning Using DeepX

Deep learning has revolutionized the way sensor measurements are interpreted and application of deep learning has seen a great leap in inference accuracies in a number of fields. However, the significant requirement for memory and computational power has hindered the wide scale adoption of these novel computational techniques on resource constrained wearable and mobile platforms. In this demonstration we present DeepX, a software accelerator for efficiently running deep neural networks and convolutional neural networks on resource constrained embedded platforms, e.g., Nvidia Tegra K1 and Qualcomm Snapdragon 400.
User Statistics for Regulating Behavior 1 Project overview : recent changes and deliverables

In the four weeks since the first paper, the wiki user statistics project has shifted its focus towards producing a more general-purpose toolkit and a deployment guide for wiki administrators. We made this shift after realizing that the original concept (of posting a determined set of statistics about user edits to the wiki) would be appropriate for wikis with needs similar to that of Wikipedia,1 but would not be helpful to wiki in general. The user behavior promoted by our original design is in fact discouraged in some wikis, which led us to recognize that wiki implementations (engines, user interface, and strategies for adoption and cooperating) are customized to support communities in their practice. Each wiki typically represents a separate community of practice, each with its own meaning for the same behavior. We hope to provide the scripts needed to generate and store wiki statistics, and a detailed guide for querying and depl! oying the statistics to provide a range of affordances and displays. Wiki-wide leaderboards and numeric evaluations of individual contributions become only a subset of what is possible, and each application can be thoughtfully made to support current practice or help regulate behavior in support of some desired practice.
An evolutionary heuristic for the maximum independent set problem

The results obtained from the application of a genetic algorithm, GENEsYs, to the NP-complete maximum independent set problem are reported. In contrast to many other genetic algorithm-based approaches that use domain-specific knowledge, the approach presented in this paper relies on a graded penalty term component of the fitness function to penalize infeasible solutions. The method is applied to several large problem instances of the maximum independent set problem. The results clearly indicate that genetic algorithms can be successfully used as heuristics for finding good approximative solutions for this highly constrained optimization problem. <<ETX>>
Synthesis of Polythiophene–Fullerene Hybrid Additives as Potential Compatibilizers of BHJ Active Layers

Perfluorophenyl functionalities have been introduced as side chain substituents onto regioregular poly(3-hexyl thiophene) (rr-P3HT), under various percentages. These functional groups were then converted to azides which were used to create polymeric hybrid materials with fullerene species, either C60 or C70. The P3HT–fullerene hybrids thus formed were thereafter evaluated as potential compatibilizers of BHJ active layers comprising P3HT and fullerene based acceptors. Therefore, a systematic investigation of the optical and morphological properties of the purified polymer–fullerene hybrid materials was performed, via different complementary techniques. Additionally, P3HT:PC70BM blends containing various percentages of the herein synthesized hybrid material comprising rr-P3HT and C70 were investigated via Transmission Electron Microscopy (TEM) in an effort to understand the effect of the hybrids as additives on the morphology and nanophase separation of this typically used active layer blend for OPVs.
Housing Stakeholder Preferences for the “Soft” Features of Sustainable and Healthy Housing Design in the UK

It is widely recognised that the quantity and sustainability of new homes in the UK need to increase. However, it is important that sustainable housing is regarded holistically, and not merely in environmental terms, and incorporates elements that enhance the quality of life, health and well-being of its users. This paper focuses on the “soft” features of sustainable housing, that is, the non-technological components of sustainable housing and neighbourhood design that can impact occupants’ health and well-being. Aims of the study are to ascertain the relative level of importance that key housing stakeholders attach to these features and to investigate whether the opinions of housing users and housing providers are aligned with regards to their importance. An online survey was carried out to gauge the level of importance that the key stakeholders, such as housing users, local authorities, housing associations, and developers (n = 235), attach to these features. Results revealed that while suitable indoor space was the feature regarded as most important by all stakeholders, there were also a number of disparities in opinion between housing users and housing providers (and among the different types of providers). This implies a scope for initiatives to achieve a better alignment between housing users and providers.