Miracle-dz/UniFAR-FTUs huggingface dataset:
Scalable Language Modeling: WikiText-103 on a Single GPU in 12 hours Extended

Word-level language modeling (WLM) is one the foundational tasks of unsupervised natural language processing. Most modern architectures for WLM use several LSTM layers, followed by a softmax layer. Even with larger batch sizes and a multi-GPU setup, training of these networks on large-vocabulary corpora is slow due to increased computation involving the softmax and the high cost of recurrence computation. We propose a model architecture and training strategy that enables us to achieve state-of-the-art performance on the WikiText-103 data set using a single GPU while being substantially faster than an NVIDIA cuDNN LSTM-based model by utilizing the Quasi-Recurrent Neural Network (QRNN), an adaptive softmax with weight tying, and longer sequences within batches.
Calliandra calothyrsus

Anneslia calothyrsa (Meisn.) Kleinhoonte Anneslia calothyrus (Meisn.) Donn. Sm. Feuilleea calothyrsa (Meisn.)Kuntze. Calliandra confusa Sprague & Riley Calliandra houstoniana var. calothyrsus (Meisn.) Barneby Anneslia confusa (Sprague & Riley) Britton & Rose Calliandra similis Sprague & Riley Anneslia similis Sprague and Riley Anneslia acapulcensis Britton and Rose. Calliandra acapulcensis (Britton and Rose) Standl.
Linkages among aquatic ecosystems

Abstract Aquatic ecosystems are almost invariably connected to other ecosystems because the dominant force of water movement facilitates physical, chemical, and biological exchanges among ecosystems. In this sense, we define an ecosystem linkage as any persistent or recurring process or attribute that connects different ecosystems in some manner. We argue that such linkages are integral, even defining, components of aquatic ecosystem structure and function, and therefore, should be evaluated in the course of ecological studies. J-NABS has made significant contributions to our understanding of such linkages. The percentage of all publications in J-NABS addressing some ecological linkage has approached 10% in recent years. Historically, emphasis was placed on upstream–downstream linkages in flowing waters, and theory (e.g., river continuum, nutrient spiraling) has evolved largely around this phenomenon. However, other linkages among ecosystems have received increased attention in the past 20 y. These linkages include surface–subsurface, lake–stream, river–floodplain, and, more recently, marine–freshwater. We contend that many ecological processes, including primary production, nutrient cycling, organic matter processing, and secondary production, are driven by such exchanges because of the donor-controlled nature of many aquatic ecosystems. Exchanges of materials from aquatic ecosystems to terrestrial systems, caused by flooding, nutrient translocation, or insect emergence, can be substantial. Movement of energy and nutrients from the ocean to freshwaters, such as in the migrations of anadromous fishes, also can be dramatic. Despite increasing evidence of the importance of such linkages, considerable impediments to research, such as journal specialization, lack of interdisciplinary study teams, and limited funding of sufficient duration for such research, exist. Such obstacles are surmountable if investigators continue to emphasize that aquatic ecology will be advanced by the study of such linkages, and that environmental problems are better understood and solved in the context of that knowledge.
A comparison of the efficiency of differential display and cDNA-AFLPs as tools for the isolation of differentially expressed parasite genes.

Summary - A range of novel PCR-based techniques for the isolation of differentially expressed genes have recently been described for the isolation of stage-specifie or host-responsive parasite genes. We have been using twO such techniques, diffe­ rential display and cDNA-AFLPs, in studies on gene expression changes during hatching and subsequent development of the potata cyst nematodes Globodera rosLOchiensis and G. pallida. ln this paper, we compare the efficiency of these [wo techniques for the isolation of such genes. cDNA-AFLPs were found ta be an extremely efficient method of isolating differentially expressed parasite genes while, in contrast, differential display was of limited value. Problems associated with the techniques and their use with plant parasitic nematodes are discussed.
DO MUSSEL PATCHES PROVIDE A REFUGE FOR ALGAE FROM GRAZING GASTROPODS

On rocky shores, cover of macroalgae is often greater growing epibiotically on mussels compared to algae growing directly attached to rock. A survey of two shores on the east coast of Ireland confirmed that mussel beds contained greater percentage algal cover and more diverse algal assemblages compared to those on rock. The reasons for this difference are not clear. It has been suggested that mussel beds provide a refuge for algae from grazing gastropods. Surprisingly, we found no evidence to support this. Using wax discs, gastropod grazing patterns were found to be similar within the mussel beds as on rock. The mussel beds do not appear to provide a refuge for algae from grazing activity at this scale and we suggest other possible mechanisms for the prevalence of epibiotic algal cover on mussels. Intertidal grazers may in fact affect the epibiotic algae on mussels and thereby affect indirectly the persistence of mussel beds.
HIGH-GRADE DIAGENETIC DICKITE AND 2M1 ILLITE FROM THE MIDDLE PROTEROZOIC KOMBOLGIE FORMATION (NORTHERN TERRITORY, AUSTRALIA)

The aim of this paper was to define the nature and the relative chronology of the diagenetic clay bearing assemblages within sandstones of the Middle Proterozoic Kombolgie formation (Northern Territory, Australia). The detrital minerals of these rocks comprise quartz, accessory zircon, tourmaline, rutile and rare phengitic white micas. Diagenetic features consist of pore-sealing secondary quartz overgrowths, strong compaction shown by interlocked structures and stylolith joints, local hematization and the occurrence of two distinct clay parageneses. Blocky crystals of dickite constitute the earlier diagenetic clays. Their FTIR spectra and their DTA curves, with a sharp dehydroxylation endothermic peak near 680oC, are characteristic of the well-ordered dickite already encountered in many deeply-buried sandstones. Quartz overgrowth may be contemporaneous with the crystallization of dickite. Illite occurred during a subsequent stage as grain coatings and as pseudomorphs of dickite in the residual pores of the sandstones. Illite seems to be contemporaneous with the major deformation features associated with compaction phenomena at the maximal burial conditions experienced by the sandstone formation. These illites are essentially of 2M1 polytype. They display pseudohexagonal platy crystals with average diameters rang ing from 2 to 10 mm. Their chemical composi t ion is Al-r ich (Ca0.01Na0.02K1.72) (Al3.82Fe 3+ 0.13Mg0.05Ti0.00Mn0.01)(Si6.27 Al1.73)O20(OH)4. These Proterozoic rocks provide a natural reference for the illite end-member occurring as a replacement of kaolin subgroup minerals during burial diagenesis of sandstones. The textural properties of the Kombolgie sandstones (absence of fracture network, low porosity, well-developed macroscopic stylolith joints.) and the crystal structure of both the diagenetic dickite and illite would tend to indicate that the Kombolgie sandstones were buried at a depth exceeding 5 km. Key Words—Crystal Form, Crystal Structure, Diagenesis, Dickite, DTA Data, FTIR, Illite, Kombolgie, Proterozoic Sandstone, XRD.
John Marmion Edmond. 27 April 1943 — 10 April 2001

John Edmond was a geochemist the unifying theme of whose research was a quantitative understanding of the processes involved in the transfer of the chemical elements into and out of the oceans; in short, what controls ocean chemistry. He achieved this through oceanographic explorations sampling ocean waters for rare metals and explorations of hot springs on the deep sea floor, rivers from the Amazon to Siberia, and the rift valley lakes of Africa. This accompanied a strong background in chemistry and an almost reverent recognition of the value of data. John challenged established paradigms and pioneered developments in element and isotope systematics as applied to geochemical processes. He will alsobe remembered for his enthusiasm, his insight, his honesty, and his defence of anyone or any group he felt was badly treated.
A Language for Counterfactual Generative Models

We present O MEGA C , a probabilistic programming language with support for counterfactual inference. Counterfactual inference means to observe some fact in the present, and infer what would have happened had some past intervention been taken, e.g. “given that medication was not effective at dose x , what is the probability that it would have been effective at dose 2 x ? ” We accomplish this by introducing a new operator to probabilistic programming akin to Pearl’s do , de-ﬁne its formal semantics, provide an implementation, and demonstrate its utility through examples in a variety of simulation models.
자동 얼굴인식을 위한 얼굴 지역 영역 기반 다중 심층 합성곱 신경망 시스템

In this paper, we propose a novel face recognition(FR) method that takes advantage of combining weighted deep local features extracted from multiple Deep Convolutional Neural Networks(DCNNs) learned with a set of facial local regions. In the proposed method, the so-called weighed deep local features are generated from multiple DCNNs each trained with a particular face local region and the corresponding weight represents the importance of local region in terms of improving FR performance. Our weighted deep local features are applied to Joint Bayesian metric learning in conjunction with Nearest Neighbor(NN) Classifier for the purpose of FR. Systematic and comparative experiments show that our proposed method is robust to variations in pose, illumination, and expression. Also, experimental results demonstrate that our method is feasible for improving face recognition performance
LAMMPS Code Simulation of the Defect Formation Induced by Ion Incidence in Carbon Nanotubes

A molecular dynamic calculation of the multi-walled carbon nanotube thermal sputtering induced by ion irradiation is carried out. Sputtering results comparable to experimental data are obtained. There are two models of ion and thermal sputtering discussed in the paper. The simulation tested the model of thermal amorphization and revealed that the disordering of multi-walled carbon nanotubes structure occurs as a result of their heating under ion irradiation. Classical molecular dynamic simulation was performed using LAMMPS code. Simulation cell with 14 layers multi-walled carbon nanotube 12 × 12 × 30 nm size contains 285600 atoms. Multi-walled carbon nanotube was irradiated by 80 keV energy Ar ions in cumulative mode. Simulation was performed on the Lomonosov-1 supercomputer. About 24600 nodes-hours were spent on one simulation as a whole. The balancing of MPI flows for a spatial grid of counting nodes occurred according to the scheme 8 × 8 × 128 MPI-stream. LAMMPS code was built with Intel 12.0 compiler. This configuration allowed to speed up the calculation in comparison with the calculation on a single-processor Xeon CPU X5570 2.93 GHz machine by 60 times.
Millimeter wave module for ns-3 network simulator

In this work, we present a novel module developed for the simulation of millimeter wave based cellular networks with the ns-3 simulator. The main focus of this work is the modeling of customizable channel, physical and medium access control (MAC) layers of millimeter wave systems. The over-all design and architecture of the model is discussed with emphasis on the customizability of the module. Finally, a simple simulation scenario and its results are discussed
Software-related Slack Chats with Disentangled Conversations

More than ever, developers are participating in public chat communities to ask and answer software development questions. With over ten million daily active users, Slack is one of the most popular chat platforms, hosting many active channels focused on software development technologies, e.g., python, react. Prior studies have shown that public Slack chat transcripts contain valuable information, which could provide support for improving automatic software maintenance tools or help researchers understand developer struggles or concerns. In this paper, we present a dataset of software-related Q&A chat conversations, curated for two years from three open Slack communities (python, clojure, elm). Our dataset consists of 38,955 conversations, 437,893 utterances, contributed by 12,171 users. We also share the code for a customized machine-learning based algorithm that automatically extracts (or disentangles) conversations from the downloaded chat transcripts.
GROUP COMPOSITION AND SEX RATIO IN HANUMAN LANGURS (SEMNOPITHECUS ENTELLUS) IN THE ARAVALI HILLS OF RAJASTHAN, INDIA

In the present study a total 16 groups of Hanuman Langurs (Semnopithecus entellus), including 11 unimale bisexual troops and five all male bands with a population of 540 animals, were observed at Kumbhalgarh Wildlife Sanctuary in the Aravalli Hills. They were studied for their group size, composition, sex ratio, etc. For this three focal troops BS-2, BS-5 and BS-10 were observed in three different eco-systems. The mean troop size was 41.7 (range 19 to 113) and the mean band size was 15.6 (range 8 to 32). The adult male-female sex ratio comes to 1: 4.6 in the study area.
Supplementary Material: Relation-Aware Global Attention for Person Re-identification

Networks. We show our network architecture (with ResNet-50 as backbone network and four RGA-SC attention modules added after the four convolutional blocks) in Table 1. Given an input image, we obtain a feature vector z of 2048-dimension after the global average pooling, then input this feature vector z to a Batch Normlization layer and get the feature vector ẑ. Following the common practice, both triplet loss with hard mining [3] and classification loss (cross entropy loss with label smoothing [6, 9]) are adopted in training, which are added on z and ẑ respectively with weights of 1.0 and 1.0. The classifier consists of a Fully Connected layer (FC) with Softmax activation, and the dimension of its output is equal to the number of identities in the training set. For the triplet loss with hard mining [3], we sample P=16 identities and K=4 images for each identity as a mini-batch with the margin parameter set to 0.3. We in general use the l2 normalized feature vector of z for feature l2 distance calculation with in testing (on CUHK03, MSMT17). For Market-1501, similar to [5], we use the l2 normalized feature vector of ẑ for feature distance calculation in testing, which gives performance a little better than that using z (the difference is small, i.e., 0.7% in mAP, 0.2% in Rank-1 for our final scheme). Training. For all the re-id models, we initialize the residual blocks with ImageNet [1] pre-trained weights and train the entire model for 600 epochs in total by adopting the Adam optimizer. During the training, we first warm up with a linear growth learning rate from 8× 10−6 to 8× 10−4. Then, the learning rate is decayed by a factor of 0.5 for every 40 epochs before the 360th epoch. All our models are implemented on PyTorch and trained on a single P100 GPU.
Predicting Sharp and Accurate Occluding Contours in Monocular Depth Estimation using Displacement Maps

The ResUpConv block is the main component of our decoder. It fuses depth and guidance features at multiple scales using skip connections. The block architecture is detailed in Fig 2. Guidance features are refined using a 3x3 residual convolution layer [5] denoted ResConv3x3. All blocks use batch-normalization, Leaky ReLU [8] activation and filters weights are initialized using Xavier initialization.
Deep Polarization Cues for Transparent Object Segmentation

Segmentation of transparent objects is a hard, open problem in computer vision. Transparent objects lack texture of their own, adopting instead the texture of scene background. This paper reframes the problem of transparent object segmentation into the realm of light polarization, i.e., the rotation of light waves. We use a polarization camera to capture multi-modal imagery and couple this with a unique deep learning backbone for processing polarization input data. Our method achieves instance segmentation on cluttered, transparent objects in various scene and background conditions, demonstrating an improvement over traditional image-based approaches. As an application we use this for robotic bin picking of transparent objects.
Weight Squeezing: Reparameterization for Model Compression Anonymous submission

In this work, we present a novel approach for simultaneous knowledge transfer and model compression called Weight Squeezing . In this method, we perform knowledge transfer from a pre-trained teacher model by learning the mapping from its weights to smaller student model weights, without signiﬁcant loss of model accuracy. We apply Weight Squeezing combined with Knowledge Distillation to a pre-trained text classiﬁcation model and compare it to various knowledge transfer and model compression methods on several downstream text classiﬁcation tasks. We observe that our approach produces competitive results. We also report that for some experiments, Weight Squeezing without Knowledge Distillation outperforms other baselines.
Differentiation of four Mycobacterium Species using DNA-DNA Hybridization Method using Specific Probes

DNA-DNA hybridization method with four oligonucleotide-specific probes was used simultaneously for differentiation and identification of four Mycobacterium species (Mycobacterium tuberculosis, M. avium, M. intracellulare, and M. kansasii). This DNA-DNA hybridization method with 4 oligonucleotide-specific probes, which targets in the rpoB region of 4 Mycobacteria species, respectively, was tested on 322 clinical isolates. Using DNA-DNA hybridization method, we detected M. tuberculosis (282 strains), M. avim (7 strains), M. intracellulare (9 strains), and M. kansasii (3 strain) from 322 clinical isolates. This result was compared with conventional biochemical test and rpoB DNA sequence analysis of this clinical isolates. We confirmed identification of Mycobacterium tuberculosis, M. avium, M. intracellulare, and M. kansasii with high sensitivity (100 %) and specificity (100 %). This DNA-DNA hybridization method could be performed within 4 hours at least. Therefore, we suggest that DNADNA hybridization method using 4 rpoB DNA probes of Mycobacteria could be used for accurate, rapid, convenient detection and identification of Mycobacterium tuberculosis, M. avium, M. intracellulare, and M. kansasii in clinical samples.
Robot Action for and around People

Most robotics problems look something like this: 1) an engineer writes down an objective, in the form of reward, cost, loss, constraints, goal, acceptability threshold, etc. 2) the robot is in charge of finding behavior that meets the objective. But when robots need to interact with people, the way we formulate these problems needs to fundamentally change, and, with them, the algorithms we use to generate the robot’s behavior. First, robots will not act in isolation. From autonomous cars to quadrotors to mobile manipulators in the home, robots will work with and around us. This makes robot action chosen in isolation far from sufficient – robots will need to choose actions that coordinate well with ours. Second, robots assisting us will need to do what we want them to do. Only the passenger in a self-driving car knows what it means for the ride to be comfortable, and how much they want to prioritize comfort over efficiency. As for us, the robot engineers, we might know what behavior we want to see, but not necessarily what magic set of numbers will make the robot produce it reliably across any new situation it might face. Thus, figuring out how to generate the behavior is only half the battle. The other half is figuring out the objective itself. And the key to that lies with us, people – what we want internally, be it as end-users or as engineers, should be the robot’s objective, even if we can’t always explicate it. My group’s research agenda is to formalize and algorithmically solve the problem of robot action not in isolation, but for assistance of and in coordination with people – this is what I call robot action for people, and around people. Approach. We formalize the problem as a human-robot system. The key to our approach is modeling people as intentional agents, whose behavior is driven (albeit imperfectly) by what they want. We formalize intent – someone’s goals, preferences about the task, and preferences about their interaction with the robot – generally via a reward function whose parameters are unknown to the robot, and thus latent state. Robot action for people is then defined by optimality with respect to this reward function. The same function drives human behavior, so robot action around people becomes a response to this behavior. This framework gives us a systematic way to break down interaction into its core components: identifying sources of evidence about the latent state (1), modeling their relation to the latent state to perform estimation (2), generating the robot’s actions with respect to the latent state, in light of the human also acting simultaneously (3), and accounting for the engineer/designer as a human that is part of the human-robot system (4).
Genetic diversity evaluation of rapeseed genotypes (Brassica napus L.) based on phenotypic traits and random amplified polymorphic DNA (RAPD) markers

Oilseed is the most important source of vegetable oil and the basis of breeding strategies is genetic diversity assessment. Genetic diversity of 19 rapeseed genotypes as well as their ancient ancestors Brassica rapa L. and Brassica oleracea L. were assessed using random amplified polymorphic DNA (RAPD) primers and morpho-phenological traits. Path analysis showed that number of pods per main branch had the highest direct effect on seed yield. Stepwise regressing showed numbers of pods per main branch was entered as the first variable in the model and explained 79% of seed yield variation. Phenotypic cluster showed that genotypes were divided into 4 groups. Polymorphic RAPD primers produced 74 bands. The range of PIC value for the used primer was 0.35 to 2.78. Result indicates primer D as the best primer for genetic diversity analysis. Molecular similarity matrix showed that Magnum and Hyola308 had the highest similarity. Molecular cluster had divided the genotypes into 3 groups; early maturing and high yielding cultivars were located in the first group, genotypes with high number of seed per pod and seed yield were located in the second group, while genotypes at third group had lowest number of pods per main branch and number of seed per pod. Obtained biplot from two first principal component analysis (PCA) showed that number of pod per main branch has an important role on seed yield, and this can be mentioned as an important trait for breeding programs. Key words: Genetic diversity, path analysis, RAPD marker, rapeseed.
Price-setting Behaviour and Inflation Dynamics in SEACEN Member Economies and their Implications for Inflation

Central banks are constantly faced with the challenge of ensuring price stability in their respective economies. Recent developments in the world economy indicate that while most advanced economies have been successful in maintaining inflation at their target levels, some appear to have been faced with the challenge of driving inflation up towards the desired levels.4 With respect to emerging market and developing economies, a notable moderation in inflation has been observed over the past decade and a half, although inflation remains well above levels seen in advanced economies (IMF, 2018).