Miracle-dz/UniFAR-FTUs huggingface dataset:
Frustum Votenet and its Application to the Waymo Lidar Dataset

Votenet [5] is a novel approach to the 3D point cloud object detection problem. It achieved SOTA results in multiple 3D object detection tasks for indoor scenes. However, other work [3] found that it performs less well on outdoor scenes without modiﬁcations. Our contributions in this work are twofold: ﬁrst, we will benchmark Votenet on (a subset of) the Waymo lidar dataset [1], (the ﬁrst time this has been done to our knowledge). Second, we will build on the ideas of [6] by reducing the problem of whole outdoor scene 3D object detection to 3D object detection within a pre-deﬁned viewing frustum obtained from 2D image recognition data. While our results still require additional veriﬁcation, we observed that Frustum VoteNet outperformed status quo VoteNet by a factor of 6 in terms of mAP.
Functions of Code Switching from Arabic to English among Jordanian Pilots in their Daily Informal Conversations: A Case Study

This study examines the frequency and the functions of code switching in informal conversations among Jordanian pilots, who have created their own jargon. It also explores the most frequent English expressions that the pilots switch to in their informal Arabic discourse. The conversations of eight Jordanian pilots aged between thirty and fifty-five were tape-recorded in three separate informal natural settings. The data were used for the purpose of finding out what the pragmatic and communicative functions are that the pilots’ code switching serves, and to investigate the most frequent expressions used in their conversations. The results showed that eight main conversational functions can be identified in their code-switching routines, namely: to compensate for the lack of exact equivalents in Arabic, to avoid interruption to the communication when not knowing the Arabic equivalent, to replace long and technical terminology in Arabic with acronyms in English (acronyms are not common in Arabic), to use aviation titles and ranks, to quote/ directly report phrases of speakers, to say the numbers, to refer to names of companies, places, documents, and organizations, and to insert some English formulaic expressions. The findings also showed that the most frequent terms and expressions used in code switching amongst Jordanian pilots are more related to the aviation register than to common-core vocabulary.
Biochemical Characterization of Carcinogen-induced Mammary Hyperplastic Alveolar Nodule and Tumor in the Rat1

Biochemical parameters characterizing growth, func tional activity, and hormone dependence were compared in the normal mammary gland, the 7,12-dimethylbenz(a)anthracene-induced hyperplastic alveolar nodule (HAN), and the mammary tumor in the rat. The rate of DNA synthesis in HAN was significantly lower than the rates in either the normal mammary gland cells or the mammary tumor cells cultured in medium containing identical hormone supple ment for the same duration of time. The rate of casein synthesis in the expiants of pregnant rat mammary gland and HAN was greatly stimulated when cultured in medium containing insulin, cortisol, and prolactin. The mammary tumor, however, failed to produce an increase in casein synthesis under the same experimental conditions. The specific estradiol-binding proteins were either absent or present in very low concentrations in HAN. In contrast, mammary tumor cytosol contained high concentrations of specific estrogen-binding proteins. The normal mammary gland, in spite of its low cellularity, had twice as many estradiol-binding macromolecules as did HAN. Altogether, these results show that HAN cell populations differ from normal mammary gland and mammary tumor cells by their nonresponsiveness to hormonal stimulation for growth and by their lack of specific receptors for estradiol. They retain, however, the functional capacity to synthesize casein, a biochemical property that the mammary tumor does not possess.
Molecular identification of fluoroquinolone resistance in Salmonella spp. isolated from broiler farms and human samples obtained from two regions in Colombia

Background and Aim: Salmonella is one of the most common foodborne pathogens, the emergence of antibiotic-resistant strains of which is increasing. The aim of this study was to phenotypically and genotypically characterize the fluoroquinolone resistance of Salmonella isolates from broiler and humans in two regions of Colombia. Materials and Methods: Salmonella strains (n=49) were evaluated. The phenotype of antibiotic resistance was assessed by an automated method and agar diffusion method, as well as the presence of the quinolone resistance genes qnrA, qnrB, qnrC, qnrD, qnrS, and aac(6’)-Ib as determined by polymerase chain reaction. Results: Strains were resistant to ciprofloxacin (75%), levofloxacin (57.1%), and enrofloxacin (38.8%). Molecular identification showed that 24 out of 49 strains possessed the qnrB gene (48.9%), while only one isolate from the Santander region possessed the aac(6’)-Ib gene. Regarding Class 1 integron, it was present in 11 out of the 49 strains (22.44%). Conclusion: This study reports the presence of the gene qnrB as well the presence of Class 1 integrons in broiler Salmonella isolates, which may contribute to the resistance to fluoroquinolones.
BUILDING A NEW GROUND MOTION LOGIC TREE FOR EUROPE: NEEDS, CHALLENGES AND NEW OPPORTUNITIES FROM EUROPEAN SEISMOLOGICAL DATA

The effective mitigation of earthquake risk requires the assessment of earthquake hazard at national and regional scale. A pan-European seismic hazard model is currently in development, building on the foundations laid by the 2013 European Seismic Hazard Model (ESHM2013). In the five years elapsed since its construction a new generation of ground motion prediction equations (GMPEs) has been published. This, alongside the recent publication of the Engineering Strong Motion database, prompts an evaluation of the new generation of GMPEs and their comparison against this considerably enlarged dataset of strong motion records. Adopting a recent loglikelihood metrics to evaluate the fit of ground motion models to data, GMPEs are compared firstly against each other, to perceive the current model-to-model spread, and then against the ESM database. Three major tectonic environments found in Europe (active shallow crustal regions, subduction zones and the Vrancea deep seismogenic source) are assessed and potential models for seismic hazard application identified. Regional variation in model fit is clearly seen for active shallow crustal regions, whilst for subduction zones and Vrancea recent models seem to provide an improved fit to European data when compared with their selected predecessors in ESHM2013. These results highlight the potential challenges and considerations needed for the construction of a new European GMPE logic tree, and lay the groundwork for its proposed revision.
Building footprint extraction based on RGBD satellite imagery

Artiﬁcial intelligence is now used for maintaining accurate up-to-date maps to respond to humanitarian, ecological and disaster recovery challenges. These tasks require near real-time, accurate, automated mapping directly from aerial and satellite images. In this application project, we apply Mask-RCNN and Conditional Adversarial Network methods for building footprint segmentation. We approach this problem as supervised learning, apply data augmentation, experiment with learning parameters, transfer learning, leveraging multi-modal RGB-D data and achieve high accuracy results.
Cross-collection Linking of Botanical Imagery in Ghent Altarpiece to Learn More about Van Eyck’s Masterpiece and to Explore a Region’s Plant Richness and Diversity over Time

As people on average only spent 20 seconds(s) observing an artwork, they mostly miss a lot of informative details that are contained within it. As an example, the 75 different plants that can be found in the Ghent Altarpiece is something not a lot of people are aware of. Within this article, we present a methodology, based on cross-collection linking, to create awareness about the botanical imagery in Van Eyck’s masterpiece and to inform people about their region’s plant richness and diversity over time. As such, this article is a nice example of how the interdisciplinary fields of cultural heritage and botany can go hand in hand to facilitate its dissemination to the general public. The plants in the painting can be queried by their name or by a picture taken with a mobile device—a plant recognition app is used to evaluate the pictures taken from the plants. A study has also been performed to evaluate these apps and to select the most appropriate one for the collection of plants in the Ghent Alterpiece. Currently, we link the detected plants to herbaria, observation data, Global Biodiversity Information Facility plantinfo, and recent wikimedia commons pictures, but other links can also be easily integrated with the platform. Finally, we also studied nowadays plant observations (volunteered geographic information) in more detail and reveal which region currently has most of Van Eyck’s plants/flowers.
The FATE Landscape of Sign Language AI Datasets

Sign language datasets are essential to developing many sign language technologies. In particular, datasets are required for training artificial intelligence (AI) and machine learning (ML) systems. Though the idea of using AI/ML for sign languages is not new, technology has now advanced to a point where developing such sign language technologies is becoming increasingly tractable. This critical juncture provides an opportunity to be thoughtful about an array of Fairness, Accountability, Transparency, and Ethics (FATE) considerations. Sign language datasets typically contain recordings of people signing, which is highly personal. The rights and responsibilities of the parties involved in data collection and storage are also complex and involve individual data contributors, data collectors or owners, and data users who may interact through a variety of exchange and access mechanisms. Deaf community members (and signers, more generally) are also central stakeholders in any end applications of sign language data. The centrality of sign language to deaf culture identity, coupled with a history of oppression, makes usage by technologists particularly sensitive. This piece presents many of these issues that characterize working with sign language AI datasets, based on the authors’ experiences living, working, and studying in this space.
C-Hg

Computer-assisted systems can provide efficient and engaging ASD intervention environments for children with Autism Spectrum Disorder (ASD). However, most existing computer-assisted systems target only one skill deficit (e.g., social conversation skills) and ignore the importance of other areas, such as motor skills, that could also impact social interaction. This focus on a single domain may hinder the generalizability of learned skills to real-world scenarios, because the targeted teaching strategies do not reflect that real-world tasks often involve more than one skill domain. The work presented in this article seeks to bridge this gap by developing a Collaborative Haptic-gripper virtual skill training system (C-Hg). This system includes individual and collaborative games that provide opportunities for simultaneously practicing both fine motor skills (hand movement and grip control skills) as well as social skills (communication and collaboration) and investigating how they relate to each other. We conducted a usability study with 10 children with ASD and 10 Typically Developing (TD) children (8–12 years), who used C-Hg to play a series of individual and collaborative games requiring differing levels of motor and communication skill. Results revealed that participant performance significantly improved in both individual and collaborative fine motor skill training tasks, including significant improvements in collaborative manipulations between partners. Participants with ASD were found to conduct more collaborative manipulations and initiate more conversations with their partners in the post collaborative tasks, suggesting more active collaboration and communication of participants with ASD in the collaborative tasks. Results support the potential of our C-Hg system for simultaneously improving fine motor and social skills, with implications for impacts of improved fine motor skills on social outcomes.
Improving Power of DSP and CNN Hardware Accelerators Using Approximate Floating-point Multipliers

Approximate computing has emerged as a promising design alternative for delivering power-efficient systems and circuits by exploiting the inherent error resiliency of numerous applications. The current article aims to tackle the increased hardware cost of floating-point multiplication units, which prohibits their usage in embedded computing. We introduce AFMU (Approximate Floating-point MUltiplier), an area/power-efficient family of multipliers, which apply two approximation techniques in the resource-hungry mantissa multiplication and can be seamlessly extended to support dynamic configuration of the approximation levels via gating signals. AFMU offers large accuracy configuration margins, provides negligible logic overhead for dynamic configuration, and detects unexpected results that may arise due to the approximations. Our evaluation shows that AFMU delivers energy gains in the range 3.6%–53.5% for half-precision and 37.2%–82.4% for single-precision, in exchange for mean relative error around 0.05%–3.33% and 0.01%–2.20%, respectively. In comparison with state-of-the-art multipliers, AFMU exhibits up to 4–6× smaller error on average while delivering more energy-efficient computing. The evaluation in image processing shows that AFMU provides sufficient quality of service, i.e., more than 50db PSNR and near 1 SSIM values, and up to 57.4% power reduction. When used in floating-point CNNs, the accuracy loss is small (or zero), i.e., up to 5.4% for MNIST and CIFAR-10, in exchange for up to 63.8% power gain.
Experts and Questions: Exploring Perceptions of Corruption

Abstract This article is a contribution to the ‘know your data’ approach to the issue of measuring corruption, in two specific areas: the impact of the way questions are formulated on the results of surveys on corruption perception; and the potential pitfalls of using businesspeople as expert respondents in surveys measuring corruption. The article first presents and analyses the sources of two most frequently used indicators to measure corruption perceptions – the Corruption Perception Index and the Control of Corruption, one of the Worldwide Governance Indicators. Based on this analysis, hypotheses are posed on how the formulation of the questions will influence the out-comes of surveys, and what differences there will be between studies conducted on the general public and businesspeople. These are tested using data obtained from two original survey experiments conducted concurrently, one on a representative sample of the public and another on businesspeople.
The New Right and the 1948 Foundation View: A Failed Revision of South Korean Cultural Memory

Abstract The emergence of the South Korean New Right movement in the mid-2000s led to the questions of how to commemorate and evaluate the ROK state establishment in 1948, and when to precisely trace such a “foundation” (1919 or 1948? ) to be vividly discussed in South Korean society. Was 1948 primarily a political division? Or was it a “foundation for success”? Following the 2008 Foundation Day Dispute, a significant number of scholarly works on the subject has been produced. This article analyses the conservative side of this discourse, approaching the foundation dispute as a conservative attempt to regain hegemony over South Korean Cultural memory in post-democratisation South Korea. Analysing New Right-authored historiography on the subject of “foundation,” the present study discloses how conservatives narrated the formative years of the South Korean state, arguing that merely dismissing the New Right as historical revisionists is too simple a conclusion. Rather, this article argues that struggles over Cultural memory are rooted in the ideological and institutional polarisation of South Korean intellectuals in contemporary South Korea. Furthermore, by contextualising the Foundation View against progressive historiography within South Korea as well as Cold War history in a global context, this study answers why the Foundation View ultimately failed to gain acceptance.
Understanding associative false memories in aging using multivariate analyses

Age-related declines in associative memory are ubiquitous, having been observed across a wide array of stimuli and experimental paradigms. Research further shows that such decreases in behavioral discriminability arise from increases in false memories for recombined lures. The current study examined the underlying neural basis of associative false memories by using representational similarity analyses to examine both age differences in the reactivation of encoded representations during retrieval and the neural overlap in the similarity of neural patterns underlying targets and related lures during retrieval. Behaviorally, we observed an age-related reduction in d’, which was shown to be driven by increased false alarms in the older adults. While we found no age difference in the relationship between patterns of neural activity underlying hits across memory phases (as measured by ERS), the similarity of neural patterns underlying targets and lures was affected by age. Specifically, while younger and older adults exhibited overall higher pattern similarity between hits and CRs compared to hits and FAs (as measured by RSA), this difference was reduced in older adults within occipital cortices. Additionally, greater Hit-FA representational similarity correlated with increases in associative FAs across occipital, frontal, and parietal cortices. Results suggest that while neural representations underlying targets may not differ across age, greater pattern similarity between the neural representation of targets and lures may reflect reduced distinctiveness of the information encoded in memory, such that old and new items are more difficult to discriminate, leading to more false alarms.
Different Contribution of the Monkey Prefrontal and Premotor Dorsal Cortex in Decision Making During a Transitive Inference Task

Several studies have reported similar neural modulations between brain areas of the frontal cortex, such as the dorsolateral prefrontal (DLPFC) and the premotor dorsal (PMd) cortex, in tasks requiring encoding of the abstract rules for selecting the proper action. Here we compared the neuronal modulation of the DLPFC and PMd of monkeys trained to choose the higher rank from a pair of abstract images (target item), selected from an arbitrarily rank-ordered set (A>B>C>D>E>F) in the context of a transitive inference task. Once acquired by trial-and-error, the ordinal relationship between pairs of adjacent images (i.e., A>B; B>C; C>D; D>E; E>F), monkeys were tested in indicating the ordinal relation between items of the list not paired during learning. During these decisions, we observed that the choice accuracy increased and the reaction time decreased as the rank difference between the compared items enhanced. This result is in line with the hypothesis that after learning, the monkeys built an abstract mental representation of the ranked items, where rank comparisons correspond to the items’ position comparison on this representation. In both brain areas, we observed higher neuronal activity when the target item appeared in a specific location on the screen with respect to the opposite position and that this difference was particularly enhanced at lower degrees of difficulty. By comparing the time evolution of the activity of the two areas, we observed that the neural encoding of target item spatial position occurred earlier in the DLPFC than in the PMd.
Counting actin in contractile rings reveals novel contributions of cofilin and type II myosins to fission yeast cytokinesis

Cytokinesis by animals, fungi and amoebas depends on actomyosin contractile rings, which are stabilized by continuous turnover of actin filaments. Remarkably little is known about the amount of polymerized actin in contractile rings, so we used low concentration of GFP-Lifeact to count total polymerized actin molecules in the contractile rings of live fission yeast cells. Contractile rings of wild-type cells accumulated polymerized actin molecules at 4,900/min to a peak number of ∼198,000 followed by a loss of actin at 5,400/min throughout ring constriction. In adf1-M3 mutant cells with cofilin that severs actin filaments poorly, contractile rings accumulated polymerized actin at twice the normal rate and eventually had almost two-fold more actin along with a proportional increase in type II myosins Myo2, Myp2 and formin Cdc12. Although 30% of adf1-M3 mutant cells failed to constrict their rings fully, the rest lost actin from the rings at the wild-type rates. Mutations of type II myosins Myo2 and Myp2 reduced contractile ring actin filaments by half and slowed the rate of actin loss from the rings.
A Neuronal Code for Space in Hippocampal Coactivity Dynamics Independent of Place Fields

Hippocampus CA1 place cells express a spatial neural code by discharging action potentials in cell-specific locations (“place fields”), but their discharge timing is also coordinated by multiple mechanisms, suggesting an alternative “ensemble cofiring” neural code, potentially distinct from place fields. We compare the importance of these distinct information representation schemes for encoding environments. Using miniature microscopes, we recorded the ensemble activity of mouse CA1 principal neurons expressing GCaMP6f across a multi-week experience of two distinct environments. We find remapping of place fields and ensemble coactivity relationships; both are similarly reliable within environments and distinctive between environments. Decoding the environment from cell-pair coactivity relationships is effective and improves after removing cell-specific place tuning. Ensemble decoding relies crucially on the most anti-coactive cells distributed across CA1 and is independent of place cell firing fields. We conclude that ensemble cofiring relationships constitute an advantageous neural code for environmental space, independent of place fields.
Using of industrial waste materials for textile wastewater treatment.

Sorption is one of the several methods that have been successfully utilized for dyes removal. A large number of materials have been used as suitable sorbents for decolourization of industrial effluents: activated carbon (the most common but expensive adsorbent), polymeric resins, various low-cost adsorbents (agricultural and industrial by-products, peat, chitin, silica, bentonite, other clays, fly ash). Our paper is a review about our researches regarding different types of industrial and agricultural waste materials with sorptive properties (ashes, textile fibres, sawdust, lignin, sun flower shells, corn cob, etc.) that were utilized into textile wastewater treatment. Batch sorption experiments were carried out in order to establish the favourable conditions to uptake of dyes. The studied operating variables were: pH, sorbent dose, dyes concentration, temperature and sorption time. The sorption systems were described using Freundlich, Langmuir and Dubinin-Radushkevich isotherm models.