Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatio‐temporal relationships between rainfall and convective clouds during Indian monsoon through a discrete lens

The Indian monsoon, a multi‐variable process causing heavy rains during June–September every year, is very heterogeneous in space and time. We study the relationship between rainfall and outgoing longwave radiation (OLR) – a proxy for convective cloud cover – for monsoon between 2004 and 2010. To identify, classify and visualize spatial patterns of rainfall and OLR we use a discrete and spatio‐temporally coherent representation of the data, created using a statistical model based on Markov Random Field. Our approach clusters the days with similar spatial distributions of rainfall and OLR into a small number of spatial patterns. We find that eight daily spatial patterns each in rainfall and OLR, and seven joint patterns of rainfall and OLR, describe over 90% of all days. Through these patterns, we find that OLR generally has a strong negative correlation with precipitation, but with significant spatial variations. In particular, peninsular India (except for the west coast) is under significant convective cloud cover over a majority of days but remains rainless. We also find that much of the monsoon rainfall co‐occurs with low OLR, but some amount of rainfall in Eastern and North‐western India in June occurs on OLR days, presumably from shallow clouds. To study day‐to‐day variations of both quantities, we identify spatial patterns in the temporal gradients computed from the observations. We find that changes in convective cloud activity across India most commonly occur due to the establishment of a north–south OLR gradient which persists for 1–2 days and shifts the convective cloud cover from light to deep or vice versa. Such changes are also accompanied by changes in the spatial distribution of precipitation. The present work thus provides a highly reduced description of the complex spatial patterns and their day‐to‐day variations, and could form a useful tool for future simplified descriptions of this process.
A Survey of Knowledge-based Sequential Decision Making under Uncertainty

Reasoning with declarative knowledge (RDK) and sequential decision-making (SDM) are two key research areas in artificial intelligence. RDK methods reason with declarative domain knowledge, including commonsense knowledge, that is either provided a priori or acquired over time, while SDM methods (probabilistic planning and reinforcement learning) seek to compute action policies that maximize the expected cumulative utility over a time horizon; both classes of methods reason in the presence of uncertainty. Despite the rich literature in these two areas, researchers have not fully explored their complementary strengths. In this paper, we survey algorithms that leverage RDK methods while making sequential decisions under uncertainty. We discuss significant developments, open problems, and directions for future work.
Color–color diagrams as tools for assessment of the variable absorption in high mass X-ray binaries

High mass X-ray binaries hold the promise of allowing us to understand the structure of the winds of their supermassive companion stars by using the emission from the compact object as a backlight to evaluate the variable absorption in the structured stellar wind. The wind along the line of sight can change on timescales as short as minutes and below. However, such short timescales are not available for the direct measurement of absorption through X-ray spectroscopy with the current generation of X-ray telescopes. In this paper, we demonstrate the usability of color–color diagrams for assessing the variable absorption in wind accreting high mass X-ray binary systems. We employ partial covering models to describe the spectral shape of high mass X-ray binaries and assess the implication of different absorbers and their variability on the shape of color–color tracks. We show that in taking into account, the ionization of the absorber, and in particular accounting for the variation of ionization with absorption depth, is crucial to describe the observed behavior well.
Learning to Generate Diverse Dance Motions with Transformer

With the ongoing pandemic, virtual concerts and live events using digitized performances of musicians are getting traction on massive multiplayer online worlds. However, well choreographed dance movements are extremely complex to animate and would involve an expensive and tedious production process. In addition to the use of complex motion capture systems, it typically requires a collaborative effort between animators, dancers, and choreographers. We introduce a complete system for dance motion synthesis, which can generate complex and highly diverse dance sequences given an input music sequence. As motion capture data is limited for the range of dance motions and styles, we introduce a massive dance motion data set that is created from YouTube videos. We also present a novel two-stream motion transformer generative model, which can generate motion sequences with high flexibility. We also introduce new evaluation metrics for the quality of synthesized dance motions, and demonstrate that our system can outperform state-of-the-art methods. Our system provides high-quality animations suitable for large crowds for virtual concerts and can also be used as reference for professional animation pipelines. Most importantly, we show that vast online videos can be effective in training dance motion models.
Demand Forecasting using Long Short-Term Memory Neural Networks

In this paper we investigate to what extent long short-term memory neural networks (LSTMs) are suitable for demand forecasting in the e-grocery retail sector. For this purpose, univariate as well as multivariate LSTM-based models were developed and tested for 100 fast-moving consumer goods in the context of a master's thesis. On average, the developed models showed better results for food products than the comparative models from both statistical and machine learning families. Solely in the area of beverages random forest and linear regression achieved slightly better results. This outcome suggests that LSTMs can be used for demand forecasting at product level. The performance of the models presented here goes beyond the current state of research, as can be seen from the evaluations based on a data set that unfortunately has not been publicly available to date.
Domain-specific Communication Optimization for Distributed DNN Training

Communication overhead poses an important obstacle to distributed DNN training and draws increasing attention in recent years. Despite continuous efforts, prior solutions such as gradient compression/reduction, compute/communication overlapping and layer-wise flow scheduling, etc., are still coarse-grained and insufficient for an efficient distributed training especially when the network is under pressure. We present DLCP, a novel solution exploiting the domain-specific properties of deep learning to optimize communication overhead of DNN training in a fine-grained manner. At its heart, DLCP comprises of several key innovations beyond prior work: e.g., it exploits {\em bounded loss tolerance} of SGD-based training to improve tail communication latency which cannot be avoided purely through gradient compression. It then performs fine-grained packet-level prioritization and dropping, as opposed to flow-level scheduling, based on layers and magnitudes of gradients to further speedup model convergence without affecting accuracy. In addition, it leverages inter-packet order-independency to perform per-packet load balancing without causing classical re-ordering issues. DLCP works with both Parameter Server and collective communication routines. We have implemented DLCP with commodity switches, integrated it with various training frameworks including TensorFlow, MXNet and PyTorch, and deployed it in our small-scale testbed with 10 Nvidia V100 GPUs. Our testbed experiments and large-scale simulations show that DLCP delivers up to $84.3\%$ additional training acceleration over the best existing solutions.
The LOFAR view of FR 0 radio galaxies

We explore the low-frequency radio properties of the sources in the Fanaroff-Riley class 0 catalog (FR0CAT) as seen by the Low-Frequency ARray (LOFAR) observations at 150 MHz. This sample includes 104 compact radio active galactic nuclei (AGN) associated with nearby (z < 0.05) massive early-type galaxies. Sixty-six FR0CAT sources are in the sky regions observed by LOFAR and all of them are detected, usually showing point-like structures with sizes of ≲3–6 kpc. However, 12 FR 0s present resolved emission of low surface brightness, which contributes between 5% and 40% of the total radio power at 150 MHz, usually with a jetted morphology extending between 15 and 50 kpc. No extended emission is detected around the other FR 0s, with a typical luminosity limit of ≲5 × 1022 W Hz−1 over an area of 100 kpc × 100 kpc. The spectral slopes of FR 0s between 150 MHz and 1.4 GHz span a broad range (−0.7 ≲ α ≲ 0.8) with a median value of ᾱ ∼ 0.1; 20% of them have a steep spectrum (α ≳ 0.5), which is an indication of the presence of substantial extended emission confined within the spatial resolution limit. The fraction of FR 0s showing evidence for the presence of jets, by including both spectral and morphological information, is at least ∼40%. This study confirms that FR 0s and FR Is can be interpreted as two extremes of a continuous population of jetted sources, with the FR 0s representing the low end in size and radio power.
Early Identification of Services in HTTPS Traffic

Traffic monitoring is essential for network management tasks that ensure security and QoS. However, the continuous increase of HTTPS traffic undermines the effectiveness of current service-level monitoring that can only rely on unreliable parameters from the TLS handshake (X.509 certificate, SNI) or must decrypt the traffic. We propose a new machine learning-based method to identify HTTPS services without decryption. By extracting statistical features on TLS handshake packets and on a small number of application data packets, we can identify HTTPS services very early in the session. Extensive experiments performed over a significant and open dataset show that our method offers a good accuracy and a prototype implementation confirms that the early identification of HTTPS services is satisfied.
On the Approximation Lower Bound for Neural Nets with Random Weights

A random net is a shallow neural network where the hidden layer is frozen with random assignment and the output layer is trained by convex optimization. Using random weights for a hidden layer is an effective method to avoid the inevitable non-convexity in standard gradient descent learning. It has recently been adopted in the study of deep learning theory. Here, we investigate the expressive power of random nets. We show that, despite the well-known fact that a shallow neural network is a universal approximator, a random net cannot achieve zero approximation error even for smooth functions. In particular, we prove that for a class of smooth functions, if the proposal distribution is compactly supported, then a lower bound is positive. Based on the ridgelet analysis and harmonic analysis for neural networks, the proof uses the Plancherel theorem and an estimate for the truncated tail of the parameter distribution. We corroborate our theoretical results with various simulation studies, and generally two main take-home messages are offered: (i) Not any distribution for selecting random weights is feasible to build a universal approximator; (ii) A suitable assignment of random weights exists but to some degree is associated with the complexity of the target function.
FORTIFICATION OF EDIBLE MUSHROOMS (Pleurotus ostreatus) WITH CALCIUM, SELENIUM AND VITAMIN C

Matrix engeneering is a methodology to obtain functional foods that applies the vacuum impregnation technique in order to incorporate physiologically active components into the food porous structure. The objective of this study was to develop a minimally processed product with functional characteristics by means of fortification of the mushroom Pleurotus ostreatus with calcium, selenium and vitamin C. Fortification levels for Ca and Se of 7,3 and 42,3% of the Daily Recommended Intake (DRI)/100 g of fresh mushroom, respectively, were obtained. At the beginning of the storage (4o C, 83% relative moisture), the vitamin C contents was 40% of the DRI/100g of fresh mushroom, and during storage, zero-order degradation kinetics was adjusted. The soft face of fortified mushrooms showed more browning than the rugged one (lesser luminosity values - L*), and more red (a* bigger value). Texture of the fortified product was not influenced by the impregnation dissolution but, with time, samples became harder.
Socially aware conversational agents

• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
Soil Texture From Tdr Waveform Analysis

The dispersive electromagnetic (EM) behavior of soils is strongly related to the mineralogy, soil structure, and pore fluid characteristics. However, time domain reflectometry (TDR) measurements (TDR waveforms) are predominantly used for soil water content and dry density estimation. These two parameters are calculated based on empirical equations that relate them to the soil dielectric permittivity (Ka) and the bulk electric conductivity (ECb). Ka and ECb are obtained in the time domain from few data points of the TDR waveform, disregarding most of the acquired data (usually 2048 data points) that reflects the EM response of the material over a broad frequency range. The complexity of the soil-water interaction in the presence of a time-varying EM field, and the presence of a non-transverse propagation mode in the TDR system limit the characterization of soils by dielectric spectroscopy. This paper presents a semi-empirical method for soil texture identification based on an integrated numerical and experimental analysis of the effect of the EM soil dispersive behavior on TDR waveforms. Evaluation of TDR tests conducted at 20°C on sands, silts, and clays using tap water at different water contents and dry densities shows that a simple time-domain signal processing of the first reflection from the probe section captures the effects of the EM soil-water interaction. Considering that the coefficients of the TDR empirical equations for soil water content and dry density estimation are soil-type dependent, the developed method allows self-calibrating the TDR system. The result of this work provides the basis for making the TDR technique a tool not only for water content and dry density estimation, but also for soil characterization.
Survey of health beliefs of women about performing mammography in the health servic centers of Sari

هدیکچ فده و هقباس : یرامیب زا یکی ناتسپ ناطرس هک تسا ریگاو ریغ یاه عـماوج رد دارـفا زا یداـیز دادعت گرم هب رجنم یم یرشب دوش . یناریا نانز رد هدش شرازگ ناطرس نیرت عیاش ، یم ناتسپ ناطرس هک دشاب 9 / 18 ناطرس لک زا دصرد هب ار اه تسا هداد صاصتخا دوخ . شور ماجنا یم مهم ناتسپ ناطرس هیلوا صیخشت رد یرگلابرغ یاه دشاب . مـهم شـقن هـب هـجوت اب اب هب یفارگ ومام ماجنا تیمها و نانز درکلمع رد اهرو ناطرس سردوز صیخشت یارب سرتسد رد شور نیرترثؤم ناونع ، نیا تسا هتخادرپ یفارگومام ماجنا هب تبسن نانز یتشادهب یاهرواب یسررب هب هعلاطم . شور و داوم اه : رد یفیصوت یسررب نیا 400 یلااب نز 40 هعجارم ،لاس زکارم هب هدننک یتشادهب یراس رهش ینامرد هنومن شور اب یریگ یفداصت زا نویپمچ یتشادهب لدم ساسا رب یفارگومام دروم رد نانآ یتشادهب یاهرواب و دندش باختنا دیدرگ زیلانآ یطابنتسا و یفیصوت رامآ زا هدافتسا اب هلصاح تاعلاطا و تفرگ رارق یسررب دروم همانشسرپ قیرط . هتفای اه : نانز تیرثکا یسررب دروم ) 5 / 69 دصرد ( و دـندوب هدادـن ماـجنا ار یفارگومام لاح هب ات 9 / 13 دـصرد ناـنز زا هداوناخ یاضعا رد ار یفارگومام ماجنا ،هعلاطم دروم ) کی هجرد ( دندومن رکذ . 8 / 55 دصرد هـک دـندوب قفاوم ًلاماک نانز زا ناتسپ تملاس زا ار درف یفارگومام ماجنا یم نئمطم دوخ یاه دنک . 6 / 41 دصرد صیخشـت هـک دـندوب قـفاوم ًلاماـک ناـنز زا یم ناتسپ نتشادرب عنام ناطرس سردوز ناتسـپ ییاـمزآدوخ ماـجنا هـک دوب نیا یفارگومام ماجنا یارب عنام نیرت عیاش و دوش یم تیافک نانآ رظن زا ناتسپ رد هدوت نتفای یارب تسـین یفارگومام ماجنا هب زاین و دنک . 5 / 34 دـصرد ـک ناـنز زا قـفاوم ًلاما دندوب درف یلغش دنور رب ناتسپ ناطرس ریثأت . 7 / 34 دصرد دـندوب ناطرس رثا رد ناتسپ نداد تسد زا قفاوم ًلاماک . لغـش نیـب نوـمزآ ناتسـپ ناطرـس تـماخو و ناطرـس هـب لاتـبا دادعتسا و یفارگومام ماجنا عناوم ،دیاوف اب طابترا رد اهنآ تارظن و نانز بترا هک دش ماجنا یرامآ دوبن راد ینعم یرامآ طا . ماـجنا عـناوم و دـیاوف اـب طاـبترا رد اـهنآ تارـظن و ناـنز تلایصـحت نیـب ینعم یرامآ طابترا یفارگومام دوب راد ) 05 / 0 P< . ( جاتنتسا : یم مک رایسب یفارگومام ماجنا نازیم ،یفارگومام هب تبسن تبثم یتشادهب یاهرواب دوجو اب دشاب . نیاربانب یم هیصوت ا اب دوش شور شریذپ شیازفا رد هک ار یلماوع ،تاقیقحت زا هدافتس دنراد شقن ناتسپ ناطرس یرگلابرغ یاه ، شور نیا زا هدافتسا تهج رد نانز قیوشت یارب لماوع نیا زا و ییاسانش دوش یرادرب هرهب ،اه . یم داهنشیپ ًانمض هک دوش کی ناونع هب ناگیار و نیتور روط هب یفارگومام نومزآ یرگلابرغ یلااب نانز رد 40 هعجارم لاس یتشادهب زکارم هب هدننک دوش هتشاذگ ارجا هب .
The Energy Budget, Niche Shift, Reproduction and Growth in a Population of Arctic Charr, Salvelinus alpinus

We studied age at niche shift and sexual maturity of Arctic charr Salvelinus alpinus (L.) from a Norwegian lake in relation to their energy budget. Young Arctic charr (age −2) fed successfully on zooplankton giving them a significant energy surplus for somatic growth. Energy intake, however, levelled off at age −3 to −4, and decreased with age among older fish. Similarly, energetic costs increased from age −2 to −3 and then the costs levelled off and decreased, probably as a consequence of a niche shift from zooplankton to zoobenthos feeding in deeper water. This shift did not increase energy intake, but reduced costs, probably through higher feeding efficiency on the larger zoobenthos in the deeper water and reduced metabolism at lower ambient temperature
Long-chain alcohols derived from the microalga Monoraphidium

This study was to investigate the composition and characteristics of long-chained alcohols extracted from the algal strain Monoraphidium 3s35. The production of biomass was optimized using different cultivation methods. Under the aerated growth condition, this strain yielded up to 37.26% extracts of dry weight and biomass. The major compounds of the extracts are mainly long-chained alcohols (89.24%), with carbon chain length ranging from 12 to 20. Interestingly, or the long-chained alcohols, 3-(2-Methoxyethyl)-1-nonanol, 3,7,11,15-Tetramethyl-2-hexadecen-1-ol and oleyl alcohol accounted for 53.68%, 23.45%, and 12.11%, respectively. Because of their amphipathic nature, these long-chained alcohols have been widely used in bioenergy production and cosmetics industry. Furthermore, Monoraphidium 3s35 produced 9.73% of and alkanes, which can be used as an important supplement for the petrodiesel-like fuel.
Vocal Diversity in Frogs of the South American Temperate Forest

Mating calls and other vocalizations emitted in breeding areas by 11 leptodactylid and rhinodermatid species of the temperate austral forest in Chile were analyzed. Assemblages of sympatric calling species were always composed of a small number of species (4 maximum), which results in a simple acoustical environment relative to anuran communities in tropical rainforests. Acoustical separation among species is assured by differences in spectral and temporal components of the calls and diverse preferences for calling sites. Dominant frequencies were related to species size. The limited number of congeneric species coexisting in sympatry and the lack of mating calls in species of three leptodactylid genera con- tributes to the simplicity of the acoustical environment in southern Chile. Modes of call variation within and among genera suggest that the extant vocal diversity in this batrachofauna may have arisen during the course of independent evolutionary histories and that interactions among sympatric taxa have had a
The Oviposition of Dermestes ater Degeer, With Notes on Bionomics Under Laboratory Conditions

Dermestes ater Degeer,1 the black larder beetle, is a cosmopolitan species that has been reported to damage dried fish, cheese, copra, hog bristles, dried mushrooms, silk, leather, woo1, cacao, and ginger (Illingworth, 1916; Mutchler and Weiss, 1927; Blake, 1943), and as a scavenger on dead birds in Hawaii (Bryan, 1926). Its synonymy has been reviewed by Barber (1942). With the exception of a few observationLs on the life history (Illingworth, 1916) little experimental work appears to have been carried out with this beetle though the closely related larder beetle, Dermestes lardarius L. , and hide beetle, Dermestes maculatus Degeer (= D. vulpinus Fabr.) have been investigated (Kreyenberg, 1928; Dick, 1937). This paper presents data on the biology of D. ater under laboratory conditions with particular emphasis on oviposition behavior.
Mitochondrial DNA Analysis of Striped Bass Populations in Chesapeake Bay

, AND . 1986. Lateral line receptivity in the mottled sculpin (Cottus bairdi). Copeia 1986:9196. HOIN-RADKOVSKI, H. BLECKMANN AND E. SCHWARTZ. 1984. Determination of source distance in the surface feeding fish Pantodon buchholzi (Pantodontidae). Anim. Behav. 32:840-851. JANSSEN, J., S. COOMBS, D. HOEKSTRA AND C. PLATT. 1987. Anatomy and differential growth of the lateral line system of the mottled sculpin, Cottus bairdi (Scorpaeniformes: Cottidae). Brain Behav. Evol. 30: 210-229. KARLSEN, H. E. , AND O. SAND. 1987. Selective and reversible blocking of the lateral line in freshwater fish. J. Exp. Biol. 133:249-262. KAUS, S. 1987. The effect of aminoglycoside antibiotics on the lateral line organ of Aplocheilus lineatus (Cyprinodontidae). Acta Otolaryngol. 103:291298.
Inhibition of Angiotensin I-Converting Enzyme by Protease Digests from Royal Jelly

Royal jelly from the honeybee, Apis mellifera, is traditionally known to have some diverse nutritional and pharmacological functions. In order to clarify the potential physiological function of royal jelly, angiotensin-I converting enzyme (ACE)-inhibitory activities of its several protease digests were investigated. Not intact royal jelly but some protease digests showed ACE-inhibitory activities. The digests produced by Bacillus subtilis protease, protease N, had ACE-inhibitory activities with the 50% inhibition against ACE at 0.25mg/ml, which is the most potent among the various protease digests. The ACE-inhibitory activities of the protease-N digest did not change after further digestion by pepsin, trypsin and chymotrypsin. These results suggest that ACEinhibitory activities in the protease-N digests were stable without being digested by gastrointestinal enzymes. (Received Dec. 5, 2002; Accepted Mar. 17, 2003)