Miracle-dz/UniFAR-FTUs huggingface dataset:
Deepframe: A Profile-Driven Compiler for Spatial Hardware Accelerators

Tracing code paths to form extended basic blocks is useful in many areas, compiler optimizations [1], improving instruction cache behavior [2] and custom-hardware offloading [3]. Prior work has been plagued by small traces, limited either by the overheads of dynamic profiling, statically available information [4], or side-exit branches [5]. In this work, we rethink what code path sequences to fuse and construct long traces for offloading to spatial accelerators, while minimizing the occurrence of side exits which limit dynamic coverage. We introduce a novel technique that recasts learning a program's execution patterns as a natural-language-processing problem, CBOW (Continuous Bag of Words). We then use a deep learning network to learn the relationships among paths. During the compilation phase, the compiler uses a sequence miner to decide what paths are likely to occur. The learning network predicts a Deepframe online, which is an extended basic block comprising a multi-path sequence (each path itself is composed of multiple basic blocks). We demonstrate the efficacy of Deepframe on spatial hardware accelerators and find the following: i) Deepframe can construct up to 5x (max: 27x) longer offload regions compared to prior approaches. ii) Surprisingly far-flung ILP (instruction-level parallelism) and MLP (memory-level parallelism) can be mined from the frames statically (5.5x increase in ILP and 10.5x increase in MLP). iii) The frames offloaded to the spatial accelerator have minimal side exits (mis-speculation) and achieve sufficient dynamic coverage to improve overall application performance (up to 9x improvement). We will be releasing open-source our end-to-end compiler prototype based on LLVM.
BESOS: a Collaborative Building and Energy Simulation Platform

Numerous software modelling tools and design techniques exist to answer questions related to optimal or exploration of building and energy system design. Current research requires that these tools and techniques are combined, leading to the energy- and time-consuming task of linking them. Our demo presents BESOS, a platform designed to facilitate the interaction of several commonly-used tools to analyze and design building and energy systems. This platform is cloud-based and open-source, making it widely available for the research community. Attendees will be able to run and modify two test example applications during the demo, the first one focusing on constructing a surrogate model that predicts building energy demand, the second, optimally designing an energy system for a remote community.
A Novel Semantic Complex Event Processing Framework for Streaming Processing

Streaming events are on the increase in various industries, with applications needing data analysed rapidly for real-time detection. A large amount of data from multiple sensors streamed simultaneously is creating a new challenge for instantaneous decision making hence necessitating the need for a highly efficient event processing, detection of events, patterns, ontologies, definition and behaviour rules.The objective of this work is to develop a framework that integrates SCEP into the traditional CEP engine. The approach proposes to address real-time detection of complex events as it occurs also with the ability to detect anomalies of events.
δ -logit : Dynamic Diﬃculty Adjustment Using Few Data Points

Diﬃculty is a fundamental factor of enjoyment and motivation in video games. Thus, many video games use Dynamic Diﬃculty Adjustment systems to provide players with an optimal level of challenge. However, many of these systems are either game speciﬁc, limited to a speciﬁc range of diﬃculties, or require much more data than one can track during a short play session. In this paper, we introduce the δ -logit algorithm. It can be used on many game types, allows a developer to set the game’s diﬃculty to any level, with, in our experiment, a player failure error prediction rate lower than 20% in less than two minutes of playtime. In order to roughly estimate the diﬃculty as quickly as possible, δ -logit drives a single metavariable to adjust the game’s diﬃculty. It starts with a simple +/- δ algorithm to gather a few data points and then uses logistic regression to estimate the players failure probability when the smallest required amount of data has been collected. The goal of this paper is to describe δ -logit and estimate its accuracy and convergence speed with a study on 37 participants playing a tank shooter game.
Sparse Bayesian Inference Based Direct Localization for Massive MIMO

Many important application scenarios in the future fifth generation (5G) systems, such as indoor navigation and autonomous driving, rely on accurate localization of users. In this paper, we propose a sparse-Bayesian-inference (SBI) based direct location algorithm for massive MIMO systems, which can exploit the sparse and high-resolution nature of angle of arrival (AoA) and any available statistical location information (SLI), to significantly improve the user localization accuracy. The existing common methods in SBI, such as approximate message passing (AMP) an variational Bayesian inference (VBI), may not work well for the massive MIMO localization problem due to their respective drawbacks. To overcome these drawbacks, we first propose a novel three-layer hierarchical structured (3LHS) sparse prior model to incorporate both the structured sparsity of the massive MIMO channel and the SLI into the SBI-based localization formulation. Then we propose a structured VBI algorithm called 3LHS-VBI to solve the resulting SBI-based localization problem. Finally, simulations verify the superior performance of the proposed location algorithm.
Fault-Tolerant Dynamic Control of a Four-Wheel Redundantly-Actuated Mobile Robot

Four-wheel redundantly-actuated mobile robot (FRMR) offers high controllability and maneuverability for automation applications. However, the robot dynamics and actuator failures are normally omitted in existing kinematic control schemes, which may lead to steering vibration and degraded robustness. To deal with these problems, a fault-tolerant dynamic control method is developed for precise trajectory tracking of the FRMR, which utilizes a two-level structure to cover the wheel-ground interactions and possible actuator failures. In the high level, with a novel fractional-order sliding mode control, this method offers an effective way to regulate the steering angle and eliminate the rotation chattering simultaneously. For the redundantly-actuated issue, a robust allocation solution is presented in the lower level to straightly determine optimal driving torques with full considerations of actuator failures and optimization efficiency. The convergence and stability of the achieved FRMR system are guaranteed theoretically. The experimental comparative results verify that higher tracking precision and enhanced robustness can be obtained using our proposed method.
Multiple-Output ZVS Resonant Inverter Architecture for Flexible Induction Heating Appliances

Flexible cooking surfaces have changed the domestic induction heating product paradigm enabling the use of a wider range of cookware materials, shapes, and positions. In order to implement such systems, multiple-output resonant inverters featuring high-performance and high-efficiency operation while achieving a cost-effective implementation are required. This paper proposes a multiple-output zero-voltage-switching resonant inverter for flexible induction heating appliances. The proposed converter features a matrix structure, enabling a cost-effective implementation with a reduced number of power devices while achieving high performance and low switching losses. It has been tested by means of an experimental prototype featuring 48 induction heating coils, proving the feasibility of the proposed approach.
Modeling Vehicle Merging Position Selection Behaviors Based on a Finite Mixture of Linear Regression Models

Vehicle merging is a complex and tactical decision process. Merging position selection behavior has been largely ignored in microscopic traffic simulators. Driver heterogeneity has received substantial attention in recent years; however, few studies have focused on the heterogeneity in merging behaviors. To account for the heterogeneity among merging drivers during the merging process and to improve the accuracy of the merging model, a finite mixture of linear regression models was developed for describing the merging position selection model. BIC was used to determine the optimal number of classes, and Latent Gold 5.0 was used to estimate parameters. Based on the US101 data in the NGSIM project, which were provided by FHWA, a 3-class linear regression model was developed. The results demonstrate that the variables differ across the classes, and the sign of each variable may also differ among the classes; hence, the strategies that are used by drivers for merging position selection differ across the classes. Cooperative lane changing of the putative leading vehicle was found to have significant influence on the merging position selection behavior; thus, merging behavior is a two-dimensional behavior that may be influenced by both lateral and longitudinal factors. Compared with previous studies, the proposed model can naturally identify the heterogeneity among drivers and is much more accurate; therefore, the proposed model is a promising tool for microscopic traffic simulation and automatic driving systems or driver assistance systems.
Maternal Overweight, Inflammation and Neurological Consequences for the Preterm Child: Results of the ELGAN Study

Maternal overweight and obesity are prenatal risk factors for obstetrical complications, preterm birth, neonatal morbidity as well as cognitive and behavioural developmental disorders in children. Paediatric morbidity and mortality as well as child development disorders are significantly associated with maternal obesity. Particularly in the neurodevelopmental and psychiatric area, it is becoming increasingly clear that, in children of mothers with an increased body mass index (BMI), there is a high correlation with childhood cognitive disabilities, attention disorders, and diseases on the autistic spectrum. The ELGAN (Extremely Low Gestational Age Newborn) study is a multicentre study which has been supported since 2000 by the National Institutes of Health (NIH) and whose objective is to research predictors for neonatal brain damage and neurological-cognitive sequelae in premature infants. The areas of focus are the connection between maternal overweight and obesity and pregnancy complications, APGAR scores and systemic inflammatory markers. In this overview, our aim is to summarise the work in this area and discuss it critically on the basis of current literature. We will examine the hypothesis whether maternal overweight and obesity in terms of a chronic inflammatory state is associated with neonatal inflammation which in turn is associated with an unfavourable development prognosis.
The Effect of Electroacupuncture on the Expression of p53 mRNA in Newborn Rats following Hypoxic-ischemic Encephalopathy

To explore the neuroprotective effects of electroacupuncture on the expression of p53 innewborn rats following hypoxic-ischemic encephalopathy (HIE). Method: The hypoxic-ischemic models were made in new-born SD rats aged 7 days by colligating bilateral common carotid artery(CCA). All rats were randomly divided into sham-surgery group, model group and electroacupuncture group (EA), and the successfully established rat models were subdivided in to 1d, 3d, 7d, 21d,three time-phases. The changes of morphology in the injured cortex were observed by pathology; the real-time PCR was used to determine the expression level of P53mRNA in the injured cortex. Results: HE and pathological staining indicated that the nerve cells are arranged in order, the structure is normal, and the cell outline and the nucleus are clear at 21d in EA group. The expression of p53mRNA in 1d, 3d, 7d, 21d, four points in EA group were significantly increased than those in model group (P<0.05). Conclusion: EA plays a neuroprotective effect through promoting the expression of p53mRNA in hypoxic-ischemic brain tissuein rats.
Pen-and-paper Rituals in Service Interaction

Advisory services are ritualized encounters between an expert and an advisee. Empathetic, high-touch relationship between those two parties was identified as the key aspect of a successful advisory encounter. To facilitate the high-touch interaction, advisors established rituals which stress the unique, individual character of each client and each single encounter. Simultaneously, organizations like banks or insurances rolled out tools and technologies for use in advisory services to offer a uniform experience and consistent quality across branches and advisors. As a consequence, advisors were caught between the high-touch and high-tech aspects of an advisory service. This manuscript presents a system that accommodates for high-touch rituals and practices and combines them with high-tech collaboration. The proposed solution augments pen-and-paper practices with digital content and affords new material performances coherent with the existing rituals. The evaluation in realistic mortgage advisory services unveils the potential of mixed reality approaches for application in professional, institutional settings. The blow-by-blow analysis of the conversations reveals how an advisory service can become equally high-tech and high-touch thanks to a careful ritual-oriented system design. As a consequence, this paper presents a solution to the tension between the high-touch and high-tech tendencies in advisory services.
Comparative evaluation of low-level laser therapy and ultrasound heat therapy in reducing temporomandibular joint disorder pain

Background Pain, limitations in opening, asymmetrical jaw movements, and temporomandibular joint (TMJ) sounds are the most common findings in temporomandibular joint disorders (TMDs), which causes excruciating pain, inflammation of the surrounding muscles, posterior fibers, and synovial fluid. This study aimed to evaluate and compare the effects of ultrasound heat therapy and low-level laser therapy (LLLT) in reducing TMD-related pain. Methods This prospective study included 42 patients (age range, 25–45 years), who were divided into two groups of 21 patients each. All patients were prescribed a non-steroidal anti-inflammatory drug (NSAID) twice a day for 5 days for temporary relief of pain prior to the commencement of treatment. Patients were kept on a soft diet and asked to restrict mouth opening during the same period. Fifteen sessions of LLLT (Group A) or ultrasound therapy (Group B) were administered to the affected side. Results Post-therapy, the mean visual analog scale score for group A and group B was 4.81 (2.01) and 6.19 (1.20), respectively; the difference was statistically significant and favoring the LLLT group. Similarly, the mean mouth opening for group A and group B was 3.99 (0.40) and 3.65 (0.41), respectively; the difference was statistically significant and favoring the LLLT group. Conclusion Our study recommends LLLT for treating TMD-related pain with no underlying bony pathology.
Joining Together Online

The field of Computer Supported Cooperative Work (CSCW) has an enduring interest in studying and designing technologies that bring people together in partnerships, teams, crowds, communities, and other collectives. As the technologies enabling group formation have evolved, so too have the guiding questions pursued by CSCW scholars. This review outlines the trajectory of scholarship on group formation with an eye towards the most pressing future questions in this area. To understand how CSCW researchers have studied technology-enabled group formation, we systematically review articles published at CSCW from 1992 to 2018. Exploring more than 2,000 potentially relevant works, we identified 35 focused on technologies and group formation. Content coding and thematic analysis revealed four periods and six themes in the study of online group formation. These themes include: group composition, self-presentation, assembly mechanisms, recruitment, organizing structures, and group culture. Quo vadis? Based on our review, we offer recommendations for the next generation of CSCW scholarship seeking to understand and enable collectives joining together online.
Oops I Did it Again: Further Adventures in the Land of ICS Security Testbeds

Research efforts in the security of Industrial Control Systems (ICS) have dramatically increased over the past few years. However, there is a limiting factor when work cannot be evaluated on real-world systems due to safety and operational reasons. This has led to multiple deployments of ICS testbeds covering multiple sectors including water treatment, power distribution and transportation networks. Over the last five years, we have designed and constructed ICS testbeds to support cyber security research. Our prior work in building testbeds culminated in a set of design principles and lessons learnt, formulated to support other researchers in designing and building their own ICS testbeds. In the last two years we have taken these lessons and used them to guide our own greenfield large-scale, complex and process-diverse security testbed affording a rare opportunity to design and build from the ground up -- one in which we have been able to look back and validate those past lessons and principles. In this work we describe the process of building our new ICS and Industrial Internet of Things (IIoT) testbed, and give an overview of its architecture. We then reflect on our past lessons, and contribute five previously unrecognised additional lessons based on this experience.
Cross-Cultural Differences in the Use of Online Mental Health Support Forums

Online mental health forums facilitate supportive relationships between peers that transcend national and cultural boundaries. While past work in medical anthropology indicates a central role of cultural identity in how individuals frame their mental well-being and distress, little research has been done to investigate the role of culture in seeking and providing mental health support on online forums. Using data from two mental health forums, we analyze cross-cultural differences in mental health expression between people from different countries. We characterize these differences along three dimensions--identity, language use, and support behavior. Through comparing usage of the platform by individuals from three Asian countries with their counterparts from primarily Western countries, we find that individuals from these less-represented countries mention their own country more often when expressing distress, use fewer clinical language terms, and are more likely to provide support to people from the same country as them, as expected from past work on mental health in these countries. Contrary to past work, however, we find that the use of clinical mental health language is not affected over time by interacting with others in an international forum. While these findings are useful for understanding the role of culture in mental health support, they also have practical design implications for online forums. We find that the three dimensions of cultural differences we analyze are correlated with receiving effective support, and make design recommendations that can improve quality of support for the people in the minority on these forums.
Multiuser-MIMO under Equally-Correlated Generalised-Rician Fading

Using an opportunistic transmission protocol in which users contend for transmission to a base station under equally-correlated generalised- Rician fading, new singleintegral selection combiner output cumulative distribution functions of multivariate equally-correlated generalised- Rician fading for multiuser multiple-input- multiple-output systems, and even degrees of freedom with multiple transmit and receive antennas per user are obtained in this paper. Cross-verification is mathematically performed to validate the proposed findings. The new findings provide a useful mathematical framework to assess performance of wireless networks under equally- correlated generalised-Rician fading environments. The effectiveness of the new findings is exemplified by computing average bit error rates for the Binary Phase-Shift Keying scheme under equallycorrelated generalised-Rician fading, and plotted against several important parameters. Simulation results are shown to exactly match numerical simulation. Detailed discussions are given.
Anti-inflammatory effect of remifentanil in lipopolysaccharide–stimulated amniotic epithelial cells

Background Sometimes general anesthesia is required for dental surgery in pregnant women. Facial bone fractures or neck abscess should be treated immediately. Dental surgery, however, creates a stressful situation that can cause inflammation. Inflammatory responses are a well-known major cause of preterm labor and preterm birth. Here we demonstrate the effects of remifentanil on the factors related to preterm labor and its mechanism of action on amniotic-derived epithelial cells (WISH cells). Methods WISH cells were exposed to lipopolysaccharide (LPS) for 24 h and co-treated with various concentrations of remifentanil. MTT assays were performed to measure cell viability. To explain the effects of remifentanil on the factors related to inflammation in WISH cells, activation of nuclear factor kappa B (NF-κB) and p38 and the expression of interleukin (IL)-1β, tumor necrosis factor (TNF)-α, cyclooxygenase (COX)2, and prostaglandin E (PGE)2 were quantified using western blotting and RT-PCR, respectively. Results Remifentanil did not affect WISH cell viability. In western blot analysis, co-treatment with remifentanil resulted in decreased phosphorylation of NF-κB, and expression of COX2 and PGE2 in LPS-induced inflammation, but the results were statistically significant only at low concentrations. Reduction of IL-1β and TNF-α expression was also observed with RT-PCR. Conclusion Co-treatment with remifentanil does not affect the viability of WISH cells, but reduces the expression of the factors related to inflammation, which can induce uterine contraction and preterm labor. These findings provide evidence that remifentanil may inhibit uterine contraction and preterm labor in clinical settings.
Exploring Actinobacteria Associated With Rhizosphere and Endosphere of the Native Alpine Medicinal Plant Leontopodium nivale Subspecies alpinum

The rhizosphere of plants is enriched in nutrients facilitating growth of microorganisms, some of which are recruited as endophytes. Endophytes, especially Actinobacteria, are known to produce a plethora of bioactive compounds. We hypothesized that Leontopodium nivale subsp. alpinum (Edelweiss), a rare alpine medicinal plant, may serve as yet untapped source for uncommon Actinobacteria associated with this plant. Rhizosphere soil of native Alpine plants was used, after physical and chemical pre-treatments, for isolating Actinobacteria. Isolates were selected based on morphology and identified by 16S rRNA gene-based barcoding. Resulting 77 Actinobacteria isolates represented the genera Actinokineospora, Kitasatospora, Asanoa, Microbacterium, Micromonospora, Micrococcus, Mycobacterium, Nocardia, and Streptomyces. In parallel, Edelweiss plants from the same location were surface-sterilized, separated into leaves, roots, rhizomes, and inflorescence and pooled within tissues before genomic DNA extraction. Metagenomic 16S rRNA gene amplicons confirmed large numbers of actinobacterial operational taxonomic units (OTUs) descending in diversity from roots to rhizomes, leaves and inflorescences. These metagenomic data, when queried with isolate sequences, revealed an overlap between the two datasets, suggesting recruitment of soil bacteria by the plant. Moreover, this study uncovered a profound diversity of uncultured Actinobacteria from Rubrobacteridae, Thermoleophilales, Acidimicrobiales and unclassified Actinobacteria specifically in belowground tissues, which may be exploited by a targeted isolation approach in the future.