Miracle-dz/UniFAR-FTUs huggingface dataset:
The achromatic number of $K_6\square K_7$ is $18$

A vertex colouring $f:V(G)\to C$ of a graph $G$ is complete if for any two distinct colours $c_1,c_2\in C$ there is an edge $\{v_1,v_2\}\in E(G)$ such that $f(v_i)=c_i$, $i=1,2$. The achromatic number of $G$ is the maximum number $\mathrm{achr}(G)$ of colours in a proper complete vertex colouring of $G$. In the paper it is proved that $\mathrm{achr}(K_6\square K_7)=18$. This result finalises the determination of $\mathrm{achr}(K_6\square K_q)$.
Utterance-level Intent Recognition from Keywords

This paper focuses on wake on intent (WOI) techniques for platforms with limited compute and memory. Our approach of utterance-level intent classification is based on a sequence of keywords in the utterance instead of a single fixed key phrase. The keyword sequence is transformed into four types of input features, namely acoustics, phones, word2vec and speech2vec for individual intent learning and then fused decision making. If a wake intent is detected, it will trigger the power-costly ASR afterwards. The system is trained and tested on a newly collected internal dataset in Intel called AMIE, which will be reported in this paper for the first time. It is demonstrated that our novel technique with the representation of the key-phrases successfully achieved a noise robust intent classification in different domains including in-car human-machine communications. The wake on intent system will be low-power and low-complexity, which makes it suitable for always on operations in real life hardware-based applications.
Instability in large bounded domains—branched versus unbranched resonances

We study transitions from convective to absolute instability near a trivial state in large bounded domains for prototypical model problems in the presence of transport and negative nonlinear feedback. We identify two generic scenarios, depending on the nature of the linear mechanism for instability, which both lead to different, universal bifurcation diagrams. In the first, classical case of a linear branched resonance the transition is hard, that is, small changes in a control parameter lead to a finite-size state. In the second, novel case of an unbranched resonance, the transition is gradual. In both cases, the bifurcation diagram is determined by interaction of the leading edge of an invasion front with upstream boundary conditions. Technically, we analyze this interaction in a heteroclinic gluing bifurcation analysis that uses geometric desingularization of the trivial state.
1D and 2D Flow Routing on a Terrain

An important problem in terrain analysis is modeling how water flows across a terrain creating floods by forming channels and filling depressions. In this paper we study a number of flow-query related problems: given a terrain Σ represented as a triangulated xy-monotone surface with n vertices, and a rain distribution R which may vary over time, determine how much water is flowing over a given edge as a function of time. We develop internal-memory as well as I/O-efficient algorithms for flow queries. This paper contains four main results: (i) An internal-memory algorithm for answering terrain-flow queries: preprocess Σ into a linear-size data structure so that given a rain distribution R the flow-rate functions of all edges of Σ can be reported quickly. (ii) I/O-efficient algorithms for answering terrain-flow queries. (iii) An internal memory algorithm for answering edge-flow queries: preprocess Σ into a linear-size data structure so that given a rain distribution R, the flow-rate function of an edge under the single-flow direction (SFD) model can be computed quickly. (iv) We present an efficient algorithm that given a path in Σ computes the two-dimensional channel along which water flows.
A note on the Erd\H{o}s-Szekeres theorem in high dimension

Burkill and Mirsky, and Kalmanson, prove independently that, for every $r\ge 2, n\ge 1$, there is a sequence of $r^{2^n}$ vectors in $\mathbb R^n$, which does not contain a subsequence of $r+1$ vectors $v^1, v^2,\dots,v^{r+1}$ such that, for every $i$ between 1 and $n$, $(v^{j}_i)_{1\le j\le r+1}$ forms a monotone sequence. Moreover, $r^{2^n}$ is the largest integer with this property. In this short note, for two vectors $u = (u_1, u_2,\dots, u_n)$ and $v = (v_1, v_2, \dots, v_n)$ in $\mathbb R^n$, we say that $u\le v$ if, for every $i$ between 1 and $n$, $u_i\le v_i$. Just like Burkill and Mirsky, and Kalmanson, for every $k, \ell\ge 1, d\ge 2$ we find the maximal $N_1, N_2$ (which turn out to be equal) such that there are numerical two-dimensional arrays of size $(k+\ell-1)\times N_1$ and $(k+\ell)\times N_2$, which neither contain a subarray of size $k\times d$, whose columns form a non-decreasing sequence of $d$ vectors in $\mathbb R^k$, nor contain a subarray of size $\ell\times d$, whose columns form a non-increasing sequence of $d$ vectors in $\mathbb R^{\ell}$. In a consequent discussion, we consider a generalisation of this setting and make a connection with a famous problem in coding theory.
State-Machine-Based Dialogue Agents with Few-Shot Contextual Semantic Parsers

This paper presents a methodology and toolkit for creating a rule-based multi-domain conversational agent for transactions from (1) language annotations of the domains' database schemas and APIs and (2) a couple of hundreds of annotated human dialogues. There is no need for a large annotated training set, which is expensive to acquire. The toolkit uses a pre-defined abstract dialogue state machine to synthesize millions of dialogues based on the domains' information. The annotated and synthesized data are used to train a contextual semantic parser that interprets the user's latest utterance in the context of a formal representation of the conversation up to that point. Developers can refine the state machine to achieve higher accuracy. On the MultiWOZ benchmark, we achieve over 71% turn-by-turn slot accuracy on a cleaned, reannotated test set, without using any of the original training data. Our state machine can model 96% of the human agent turns. Our training strategy improves by 9% over a baseline that uses the same amount of hand-labeled data, showing the benefit of synthesizing data using the state machine.
Towards Stable Imbalanced Data Classification via Virtual Big Data Projection

Virtual Big Data (VBD) proved to be effective to alleviate mode collapse and vanishing generator gradient as two major problems of Generative Adversarial Neural Networks (GANs) very recently. In this paper, we investigate the capability of VBD to address two other major challenges in Machine Learning including deep autoencoder training and imbalanced data classification. First, we prove that, VBD can significantly decrease the validation loss of autoencoders via providing them a huge diversified training data which is the key to reach better generalization to minimize the over-fitting problem. Second, we use the VBD to propose the first projection-based method called cross-concatenation to balance the skewed class distributions without over-sampling. We prove that, cross-concatenation can solve uncertainty problem of data driven methods for imbalanced classification.
Using multichannel singular spectrum analysis to study galaxy dynamics

N-body simulations provide most of our insight into the structure and evolution of galaxies, but our analyses of these are often heuristic and from simple statistics. We propose a method that discovers the dynamics in space and time together by finding the most correlated temporal signals in multiple time-series of basis-function expansion coefficients and any other data fields of interest. The method extracts the dominant trends in the spatial variation of the gravitational field along with any additional data fields through time. The mathematics of this method is known as multichannel singular spectrum analysis (M-SSA). In essence, M-SSA is a principal component analysis of the covariance of time-series replicates, each lagged successively by some interval. The dominant principal component (PC) represents the trend that contains the largest fraction of the correlated signal. The next PC is orthogonal to the first and contains the next largest fraction, and so on. Using a suite of previously analysed simulations, we find that M-SSA describes bar formation and evolution, including mode coupling and pattern-speed decay. We also analyse a new simulation tailored to study vertical oscillations of the bar using kinematic data. Additionally, and to our surprise, M-SSA uncovered some new dynamics in previously analysed simulations, underscoring the power of this new approach.
The role of Edge-Driven Convection in the generation of volcanism I: a 2D systematic study

The origin of intraplate volcanism is not explained by the plate tectonic theory, and several models have been put forward for explanation. One of these models involves Edge-Driven Convection (EDC), in which cold and thick continental lithosphere is juxtaposed to warm and thin oceanic lithosphere to trigger convective instability. To test whether EDC can produce long-lived high-volume magmatism, we run numerical models of EDC for a wide range of mantle properties and edge (i.e., the oceanic-continental transition) geometries. We find that the most important parameters that govern EDC are the 5 rheological paramaters mantle viscosity η0 and activation energy Ea. However, even the maximum melting volumes found in our models are insufficient to account for island-building volcanism on old seafloor, such as at the Canary Islands and Cape Verde. Also, beneath old seafloor, localized EDC-related melting commonly transitions into widespread melting due to smallscale sublithospheric convection, inconsistent with the distribution of volcanism at these volcanic chains. In turn, EDC is a good candidate to sustain the formation of small seamounts on young seafloor, as it is a highly transient phenomenon that 10 occurs in all our models soon after initiation. In a companion paper, we investigate the implications of interaction of EDC with mantle-plume activity.
Preparation of Encapsulated Resveratrol Liposome Thermosensitive Gel and Evaluation of Its Capability to Repair Sciatic Nerve Injury in Rats

The purpose of this study was to prepare a liposomal temperature-sensitive gel able to slowly release resveratrol after local intramuscular injection. The best formulation of resveratrol liposomes was based on the highest encapsulation efficiency and drug loading designed by Box-Behnken. The prepared liposomes were approximately circular, with a mean particle diameter of and zeta potential of -6.9 mV. The optimized liposomes were dispersed in a polymer gel (PLGA-PEG-PLGA) for preparation of an in situ-formed gel at . In vitro release of the prepared liposome temperature-sensitive gel was studied and compared with ordinary drug-releasing gels, revealing a significantly longer drug release time. Finally, a rat sciatic nerve injury model was used to evaluate the pharmacological activity of the liposome temperature-sensitive gels for the repair of damaged nerves. The results indicate that the gel was able to promote recovery of damaged nerves.
Methods Used in Disinfections of Wastewater and Sewage Sludge – Short Review

Abstract Wastewater and sewage sludge are a place of occurrence of many microorganisms, including viruses, pathogenic and relatively pathogenic bacteria. They can leak into other environments, i.e. receiver waters or soil, thus creating a biological hazard. Increasing the sanitary level of safety of municipal wastewater treatment plants requires the introduction of disinfection of sewage and sewage sludge. The purpose of this article is a short review of the literature on methods used in disinfection of wastewater and sewage sludge. The work discusses the sanitary characteristics of wastewater and sewage sludge, primarily paying attention to the physical and chemical methods used to disinfect them. In addition, attention was also paid to the aspect of practical use of disinfection in municipal wastewater treatment plants around the world.
Internal Quality Assurance Model at Samarinda Midwifery Academy

The objectives to be achieved through this research are describe the Quality Assurance Model, Formulate the Quality Assurance Model, Describe the inhibiting factors and solution of the Quality assurance system at the Husada Flower Midwifery Academy, the Mahakam Pearl Midwifery Academy and the East Kalimantan Health Polytechnic. This study uses a qualitative approach to the type. Data collection techniques are carried out through in-depth interviews, participant observation and documentation. Establish procedures for preparation of implementation and required resources. Prepare human resources through the process of training, workshops and discussions. Samarinda Mahakam Pearl Midwifery Academy Samarinda. Conducted based on: Academic documents: quality standards that have been set. Quality document: as an instrument to achieve predetermined standards. Poltekkes Kemenkes East Kalimantan, The implementation of improving the quality assurance system is guided by: quality assurance principles oriented to inputs, processes and outputs. Formulation of Quality Assurance, preparation of quality improvement strategy plans is carried out systematically and structured in each midwifery academy which is oriented towards improving the quality of inputs, processes and outputs, with different strategies. Inhibiting factors and quality assurance system solutions implemented by carrying out: self-evaluation, internal academic quality audits, solutions carried out to determine the achievement of quality standards that have been set and evaluation findings used as material to improve the quality assurance improvement, which is planned, implemented and evaluated carried out implementation control and improvement in accordance with midwifery vocational education standards properly.
Design and Characterization of Biodegradable Chitosan Nanoparticles Loaded With Almotriptan Malate For Migraine Therapy

Nanoparticles are designed to improve the pharmacological and therapeutic properties of conventional drugs. In the present research work, almotriptan malate was formulated as nanoparticle drug delivery system for the effective management of migraine by ion-gelation technique. Shape and size of the nanoparticles were evaluated by TEM images. FTIR and DSC studies confirmed that there were no interactions between the drug and the other ingredients. XRD study was carried out to confirm the crystalline or amorphous nature of the nanoparticles. The entrapment efficiency of was found to be 74 to 82% and drug loading capacity was found to be 15 to 16% The in-vitro release studies concluded that the release was sustained after an initial burst. The in vitro mucoadhesion study using goat nasal mucosa was found to be 54% and 69%. The kinetic study revealed that the almotriptan malate nanoparticles followed the first order kinetics.
Transmission of Pea Enation Mosaic Virus by the Pea Aphid, Acyrthosiphon pisum, following Virus Acquisition by Injection

Acyrthosiphon pisum (Harris) became highly inoculative after partially purified and density gradient-purified preparations of pea enation mosaic virus (PEMV) were injected into them as young nymphs. The aphids' mean rate of transmission, Vo , and mean (weighted) period of inoculativity, Tt , increased linearly as the dosage of injected virus increased, whereas the median latent period, LP50, decreased as dosage increased. When late 1st to early 2nd instars were inoculated with partially purified virus preparations at a concentration of A260nm = 30, a Vo of 21 transmissions per aphid per generation, a Tt of 9.35 days, and an LP50 as short as 3.0 hours were realized. All attempts to maintain inoculativity among aphid lines by the serial hemolymph-passage method failed after the 2nd passage, even though young nymphs were used as recipients in each passage. Inoculativity was maintained in over 60% of the aphid lines after the 1st passage. Aphid nymphs became inoculative when injected with hemolymph collected from aphids 4, 7, and 10 days after a 24-hour acquisition-access period on PEMV-infected plants but not when injected with hemolymph collected on the 13th day.
Fluxes during 2010-2015 Inferred from GOSAT XCO 2 2 retrievals using a new version of Global Carbon Assimilation System

Fei Jiang, Hengmao Wang, Jing M. Chen, Weimin Ju, Xiangjun Tian, Shuzhang 5 Feng, Guicai Li, Zhuoqi Chen, Shupeng Zhang, Xuehe Lu, Jane Liu, Haikun 6 Wang, Jun Wang, Wei He, Mousong Wu 7 8 9 1 Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, 10 International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China 11 2 Department of Geography and Planning, University of Toronto, Toronto, Ontario M5S3G3, 12 Canada 13 3 The Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China 14 4 National Satellite Meteorological Center, China Meteorological Administration, Beijing 15 100101, China 16 5 College of Global Change and Earth System Science, Beijing Normal University, Beijing, 17 100875, China 18 6 School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China 19 7 Jiangsu Center for Collaborative Innovation in Geographical Information Resource 20 Development and Application, Nanjing, 210023, China 21 22 23 24 25 26
Analysis of anti-oxidant and anti-inflammatory potential of Baccaurea courtallensis (Wight) Mull. Arg

The ethanolic leaf extracts of Baccuarea courtallensis (Wight) Mull.Arg. a member of the family Euphorbiaceae were assessed for its phytochemical, antioxidant and anti-inflammatory potential. The preliminary screening showed the presence of different phytochemicals among them phenol and flavonoid were quantified. The extract showed a significant inhibition of carrageenan-induced rat paw edema in Wistar rat compared to the standard anti-inflammatory drug indomethacin. Antioxidant activity was evaluated through (in vitro) assays such as DPPH radical scavenging assay and total antioxidant capacity by phosphomolybdenum method.
The Role of TPB in Predicting Sustainable Behavior in Higher Education Institution

The spirit of Sustainable Development Goals encourages people and institutions including higher education institutions (HEI) to take an active role to attain the goals such as performing sustainable behavior. This research, therefore, is conducted to predict the factors underlying HEI’s members to perform sustainable behavior by applying Theory of Planned Behavior. This study distributes an electronic questionnaire to 273 accounting undergraduate students in Universitas Islam Indonesia. All completed questionnaires were analyzed by assistance from a statistic tool namely smartPLS version 3. This research discovers subjective norm does not significantly influence intention as well as sustainable behavior, however, the others influence significantly. The indirect test indicates that there are no mediation effects from intention variable in order to mediate the relation between three independent variables to sustainable behavior. This research argues that the insignificant influence of subjective norm to intention and sustainable behavior results insignificant influence of intention to sustainable behavior and generates no mediation effects.
Evaluation of Phenolic Compounds, Antioxidant Activities and Antioxidant Enzymes of Wild Grape Peel and Pulp

Peel and pulp of grape (Vitis vinifera L.) berries contain a wide range of bioactive compounds that may be responsible for their biological activities. Phenolic compounds, antioxidant capacity and antioxidant enzymes of wild grape accessions from the West Azerbaijan province were investigated in different fractions of berries, i.e., peel and pulp fractions. The total phenol (TP) content ranged from 139.29-843.10 and 151.67-416.91 mg Gallic acid equivalent (GAE) per 100 g in the peel and pulp, respectively. The highest level of antioxidant capacity and antioxidant enzymes activities (Catalase (CAT)and Superoxide dismutase (SOD)) in all the native accessions was observed in peel fraction. Also, principal component analysis (PCA) demonstrated that genotypic effect is more pronounced toward peel antioxidant activity based on 2,2-Diphenyl-1-picrylhy (DPPH) assay and pulp total anthocyanin (TA) of grape berries. The present study displays the potential of native grape accessions studied for improvement of nutritional value through germplasm enhancement programs.
Effect of psychological stress on Tempomandibular joint (Experimental study)

Background: Psychological stress is considered a possible pathogenic factor for temporomandibular joint disorders (TMD), but few reports have supplied direct evidence. This study was designed to observe the effects of psychological stress on the TMJ structures.Materials and Methods: A well-established rat communication box model were used to induce a psychological stress in rats (PS group). The control group was not subjected to psychological insult. After one month, the rats were euthanized and TMJ specimens were harvested to perform a histological analysis under light microscope.Results: Light microscopy showed apparent pathological changes in the TMJs of psychologically stressed rats.Conclusion: These results indicate that psychological stress is able to induce pathologic alterations in the TMJ structures and plays an important role in TMD.
A Combined Time Series Model for the Prediction of Social Network Popularity and Content Evolution

The randomness, dynamism and uncertainty of social networks pose a challenge for revealing the mechanism of content popularity growth. Evolution of content popularity is characterized by strong heterogeneity. It is difficult for a single time series prediction model to capture all kinds of content popularity dynamic evolution patterns at the same time. Using single model to predict complex social network content popularity will lead to poor prediction ability and limited application scenarios. This paper attempts to establish a combined predicting model that integrates the predicting capabilities of multiple traditional time series models. By applying multi-class regression and analyzing the historical prediction performance of each sub-model, the combined weights of the predicted values of each sub-model are generated. The model can learn to adjust the combination weights according to the real-time prediction performance of each sub-model, so as to adapt to the dynamic changes of the evolution model and to enhance the performance of predicting content popularity. The evaluation results of real social network datasets show that the performance of the proposed model is better than that of the existing single models.