Miracle-dz/UniFAR-FTUs huggingface dataset:
User Memory Reasoning for Conversational Recommendation

We study an end-to-end approach for conversational recommendation that dynamically manages and reasons over users’ past (offline) preferences and current (online) requests through a structured and cumulative user memory knowledge graph. This formulation extends existing state tracking beyond the boundary of a single dialog to user state tracking (UST). For this study, we create a new Memory Graph (MG) <-> Conversational Recommendation parallel corpus called MGConvRex with 7K+ human-to-human role-playing dialogs, grounded on a large-scale user memory bootstrapped from real-world user scenarios. MGConvRex captures human-level reasoning over user memory and has disjoint training/testing sets of users for zero-shot (cold-start) reasoning for recommendation. We propose a simple yet expandable formulation for constructing and updating the MG, and an end-to-end graph-based reasoning model that updates MG from unstructured utterances and predicts optimal dialog policies (eg recommendation) based on updated MG. The prediction of our proposed model inherits the graph structure, providing a natural way to explain policies. Experiments are conducted for both offline metrics and online simulation, showing competitive results.
Analysis of the spatial impact of the tourism industry on Vietnam’s economic growth

Based on the study of spatial characteristics of Vietnam's tourism industry in the 2007-2018 period, the authors built a spatial table data model to analyze the spatial impact of tourism on Vietnam's economic growth. The research results indicate that Vietnam's tourism industry has convergence and there exists a positive spatial relationship, with provinces with highly developed tourism industries concentrated mainly in the two regions of the Red river delta and the Southeast region. In addition, based on the results of spatial regression, it can be seen that the regional tourism development has little effect on the tourism development of neighboring areas, but the extent of the tourism industry's influence on growth of local economy is huge. Tourism is recognized around the world as one of the largest and fastest growing economic sectors. In developing countries such as Vietnam, tourism is seen as a tool to encourage economic development and it also serves to alleviate poverty
FERTILIZATION IN BARLEY

A B S T R A C T The mature embryo sac of barley consists of an egg, two synergids, a central cell, and up to 100 antipodal cells. At shedding the male gametophyte is 3-celled, consisting of a vegetative cell with a large amount of starch and two sperms having PAS+ boundaries. Before pollination the nucleus and cytoplasm of each synergid appear normal. After pollination the nucleus and cytoplasm of one synergid undergo degeneration. The pollen tube grows along the surface of the integument of the ovule, passes through the micropyle, and enters the degenerate synergid through the filiform apparatus. The pollen tube discharges the vegetative nucleus, two cellular sperms, and a variable amount of starch into the degenerate synergid. Soon after deposition the sperms migrate by an unknown mechanism to the chalazal end of the degenerate synergid. Sperm nuclei then enter the cytoplasm of the egg and central cell, ultimately resulting in the formation of the zygote and primary endosperm nucleus, respectively. Sperm boundaries do not enter egg or central cell, but it was not possible to determine the fate of other sperm components. Degenerate vegetative and synergid nuclei remain in the synergid after fertilization, constituting what are considered to be X-bodies in barley. The second synergid degenerates during early embryogeny. THE ENTRANCE and discharge of the pollen tube into the embryo sac, the role of the synergids, and
Suggesting Natural Method Names to Check Name Consistencies

Misleading names of the methods in a project or the APIs in a software library confuse developers about program functionality and API usages, leading to API misuses and defects. In this paper, we introduce MNire, a machine learning approach to check the consistency between the name of a given method and its implementation. MNire first generates a candidate name and compares the current name against it. If the two names are sufficiently similar, we consider the method as consistent. To generate the method name, we draw our ideas and intuition from an empirical study on the nature of method names in a large dataset. Our key finding is that high proportions of the tokens of method names can be found in the three contexts of a given method including its body, the interface (the method's parameter types and return type), and the enclosing class' name. Even when such tokens are not there, MNire uses the contexts to predict the tokens due to the high likelihoods of their co-occurrences. Our unique idea is to treat the name generation as an abstract summarization on the tokens collected from the names of the program entities in the three above contexts. We conducted several experiments to evaluate MNire in method name consistency checking and in method name recommending on large datasets with +14M methods. In detecting inconsistency method names, MNire improves the state-of-the-art approach by 10.4% and 11% relatively in recall and precision, respectively. In method name recommendation, MNire improves relatively over the state-of-the-art technique, code2vec, in both recall (18.2% higher) and precision (11.1% higher). To assess MNire's usefulness, we used it to detect inconsistent methods and suggest new names in several active, GitHub projects. We made 50 pull requests (PRs) and received 42 responses. Among them, five PRs were merged into the main branch, and 13 were approved for later merging. In total, in 31/42 cases, the developer teams agree that our suggested names are more meaningful than the current names, showing MNire'S usefulness.
Isohumulones modulate blood lipid status through the activation of PPARa

Isohumulones derived from hops are the major bitter compounds in beer. It was recently reported that isohumulones activated peroxisome proliferator-activated receptors (PPARs) a and g in vitro and modulated glucose and lipid metabolism in vivo. In this study, we examined the effects of isomerized hop extract (IHE) primarily containing isohumulones in C57BL/6N male mice and found that such treatment increased their liver weight and reduced their plasma triglyceride and free fatty acid levels. Microarray analysis and quantitative real time PCR (QPCR) showed that IHE dose-dependently upregulated the expression of a battery of hepatic genes that are involved in microsomal N-oxidation and peroxisomal and mitochondrial h-oxidation. These effects were common in both genders and very similar to those found with the PPARa agonist, fenofibrate (FF). Moreover, these effects were not found in PPARa-deficient mice. Thus, our results strongly suggest that IHE intake upregulates the expression of key genes that are involved in hepatic fatty acid oxidation, and that it ameliorates the blood lipid profile by activating PPARa. D 2005 Elsevier B.V. All rights reserved.
Micropropagation of Kluai Khai (Musa acuminata ‘Klaui Khai’) Using Sword Suckers and Inflorescences at Various Development Stages

Comparison the use of inflorescence at various stages of development versus meristem of sword suckers of Kluai Khai, as a source of the primary explants for in vitro culture was conducted . For shoot initiation, the explants were cultured on semi solid and liquid medium of Murashige and Skoog (1962) supplemented with 5 ppm. of 6-benzylaminopurine (BA). It was found that on liquid medium, the culture produced the first shoot faster than the ones on semi solid medium. The first shoot of suckers occurred on the 30th and 45th days after culturing on liquid medium, and semi solid medium respectively, while those at the 5th, 3thand 1st days of developmental stage occurred on the 52nd, 52nd and 56th days of culturing respectively. After 2 months, the sucker on liquid medium was noticed to give the shoot number of 1.88 shoots per explant, where as on semi solid medium, it yielded 0.6 shoot per explant. The shoot number of inflorescence at the 5th, 3rd and 1st days of developmental stage cultured on liquid medium were 2.08 (the highest), 1.93 and 1 shoots per explant respectively. At this stage, no development of the shoots on semisolid medium had been found to develop yet. Shoot multiplication was also revealed to be stimulated by transferring explants into semi solid medium, thus yielding such higher shoot number than the others. On the 5th month, the inflorescence at the 5th day of developmental stage gave the highest shoot number of 9.06 shoots per explant which was not significantly different from those of 8.9 shoots per explant at the 3rd day of developmental stage. The shoot number of the others were significantly lower different. 10% off-type shoots, occurred in inflorescence culture. After transplanting plantlets to the nursery, the survival rate was 96 percent.
Recommendation for New Users and New Items via Randomized Training and Mixture-of-Experts Transformation

The cold start problem is a long-standing challenge in recommender systems. That is, how to recommend for new users and new items without any historical interaction record? Recent ML-based approaches have made promising strides versus traditional methods. These ML approaches typically combine both user-item interaction data of existing warm start users and items (as in CF-based methods) with auxiliary information of users and items such as user profiles and item content information (as in content-based methods). However, such approaches face key drawbacks including the error superimposition issue that the auxiliary-to-CF transformation error increases the final recommendation error; the ineffective learning issue that long distance from transformation functions to model output layer leads to ineffective model learning; and the unified transformation issue that applying the same transformation function for different users and items results in poor transformation. Hence, this paper proposes a novel model designed to overcome these drawbacks while delivering strong cold start performance. Three unique features are: (i) a combined separate-training and joint-training framework to overcome the error superimposition issue and improve model quality; (ii) a Randomized Training mechanism to promote the effectiveness of model learning; and (iii) a Mixture-of-Experts Transformation mechanism to provide 'personalized' transformation functions. Extensive experiments on three datasets show the effectiveness of the proposed model over state-of-the-art alternatives.
Explainable Word-Embeddings for Medical Digital Libraries - A Context-Aware Approach

State of the Art Neural Language Models (NLMs) such as Word2Vec are becoming increasingly successful for important biomedical tasks such as the literature-based prediction of com-plex chemical properties or for finding novel drug-disease associations (DDAs). However, NLMs have the disadvantage of being hard to interpret. Therefore, it is notoriously difficult to explain why an artificial neural network learned or predicted some specific association. Considering that digital libraries offer well-curated contexts, the challenge is to automatically create a reasonable explanation that is intuitively understandable for a user. For a pharmaceutical use case, we present a new method that generates pharmaceutical explanations for predicted DDAs in intuitively understandable sentences. In other words, our approach enables a context-aware access to embedded entities. We test the accuracy of our approach with a comprehensive retrospective analysis considering real DDA predictions. Our explanations can automatically determine the association type (Drug treats or induces a disease) of a predicted DDA with up to 83%. For existing DDAs, we even achieve accuracies up to 87%. We show that we perform better than deep-learning approaches in this classification task by up to 9%.
Creating a novel approach for mobile positioning based on CDR data

—User geographical positioning is important for many ﬁelds that rely on passive data analytics, like targeted marketing, urban and rural transportation planning, public health, etc. A new type of data that is commonly used for passive mobility analysis is the mobile data or the so-called Call Detail Records (CDR). The CDR events are stored by mobile operators for the primary purpose of billing. They are generated every time we use SMS, call, or internet services. However, CDR data has two major drawbacks the temporal and spatial uncertainties. Although the ﬁrst problem is widely covered by trajectory reconstruction techniques, the second problem remains still challenging. Hence, in this project, we propose the usage of a new method based on the Sequential Monte Carlo algorithms called Particle Filtering. The particle ﬁltering application implemented in this project, models the trajectory movement to predict the user’s position in a given area. This method uses CDR data and solely the information related to the area of the coverage from the mobile towers. Our goal is to evaluate if this nonlinear method can out-perform the existent linear methods like Switching Kalman Filter. The usability of the method and future work are discussed in this report.
How Expert Knowledge Can Help Measurements: Three Case Studies

In addition to measurement results, we often have expert estimates. These estimates provides an additional information about the corresponding quantities. However, it is not clear how to incorporate these estimates into a metrological analysis: metrological analysis is usually based on justified statistical estimates, but expert estimates are usually not similarly justified. One way to solve this problem is to calibrate an expert the same way we calibrate measuring instruments. In the first two case studies, we show that such a calibration indeed leads to useful result. The third case study provides an example of another use of expert knowledge in measurement practice: this knowledge can be used to make semi-empirical measurement models more explainable – and thus, more reliable.
CLIMATE-INDUCED TRENDS IN GLOBAL RIVERINE WATER DISCHARGE AND SUSPENDED SEDIMENT DYNAMICS IN THE 21 CENTURY by NISHANI POORNA MORAGODA SAGY COHEN, COMMITTEE CHAIR

ii DEDICATION . iv LIST OF ABBREVIATIONS AND SYMBOLS . v ACKNOWLEDGMENTS . viii LIST OF TABLES . xi LIST OF FIGURES . xii LIST OF EQUATIONS . xv CHAPTER
Sense Amplifier Half Buffer Based Ripple Carry Adder for IEEE 754 Standards

Addition is a specifically used indispensable computation used for most of the applications including digital systems and control systems. Adder is a primitive constituent used in the construction of digital IC; also it is an essential part of signal processing applications like DSP. The speed of an adder circuit holds a considerable influence on the total performance of digital circuits. The prime objective of this research is to design ripple carry adder using different asynchronous logics like Multithreshold null convention logic (MTNCL), Multi-threshold dual spacer dual rail delay insensitive logic (MTD3L) and proposed Sense amplifier half buffer logic (SAHB). SAHB is an asynchronous Quasi-Delay -Insensitive (QDI) method used to achieve significant functional speed of the circuit. The standard library cells (2-input AND/NAND, 2-input OR/NOR, 2-input XOR/XNOR) are designed using proposed SAHB logic to design an 8- bit Ripple Carry Adder circuit. The proposed SAHB logic design provides the solution of minimum delay with improved speed compared to the existing logic design techniques. The asynchronous logics are designed using mentor graphics tool with 130nm technology. Various performances attributes like power dissipation, delay and energy are tabulated and compared with existing logics
Diversity of fouling communities grown on artificial substrata DeployeD in a polluteD anD an unpolluteD site in the aegean sea (greece)

Fouling communities, grown on artificial substrata were monitored for a half-year (4, 8, 12, 16, 20 and 26 weeks) between March and September 2006 in two sites in the Saronikos Gulf under the influence of different levels of organic pollution. Originally this area is characterized by oligotrophy. Species richness and Total percentage coverage were calculated and Man-Whitney U-Test was applied until the 26th week to determine differences between stations and sampling periods. Results indicated significant differences within time from the 12th week on (p = 0.001). Multivariate statistical analysis was used in order to compare community structures between the polluted and the control site. After a 26 week period communities differed significantly between the two study sites (global R = 0.993, p = 0.001). The control site Mavro Lithari showed a higher diversity than the polluted Aghios Kosmas site. Anomia ephippium, Dictyota dichotoma, Sphacelaria sp. and Chondria sp. contributed with almost 49 % to the dissimilarity in communities between sites (SIMPER-analysis). Several other species accounted to lesser extends to the dissimilarities between sites. Based on our knowledge this is the first study focusing diversity of fouling assemblages grown on hard substrate in the Saronikos Gulf.
Experimental study and development of mathemtical relations for machining copper using CNC WDEDM

Although WEDM has revolutionized the present day metal cutting, die making, press tool and precision manufacturing industries, further improvements are still required to meet the increasing demand of product precision and accuracy in those sectors of manufacturing. The machining performance is greatly influenced by various factors like work material, work thickness, discharge current. This paper briefs the effect of work piece thickness on various cutting parameters like discharge current, cutting speed and performance such as material removal rate, spark gap, when copper is machined. An attempt is made to establish mathematical relations between the work piece thickness and other cutting parameters experimental data. It includes the statistical analysis to determine the square of correlation factor, R2 and Standard deviation values. The mathematical relations are developed using Origin 8.0 software for the best fit curve from the experimental data and ANOVA analysis is applied for analyzing the errors. The results are checked for validation and are found to be encouraging. The mathematical equations explored can be used to establish the machine parameters and estimation of machining time.
Effects of high‐intensity interval training in patients with coronary artery disease after percutaneous coronary intervention: A systematic review and meta‐analysis

To evaluate whether high‐intensity interval training (HIIT) was superior to low‐intensity training or usual care among patients after percutaneous coronary intervention. The hypothesis was that HIIT would help patients after percutaneous coronary intervention (PCI) improve cardiopulmonary function, lipid profiles and in‐stent restenosis.
Role of interspecies H2 transfer to sulfate and ferric iron-reducing bacteria in acetate consumption in anoxic paddy soil

Addition of sulfate resulted in complete inhibition of methanogenesis in anoxic paddy soil. About 20% of the CH4 was produced from H2/14CO2, the rest from acetate. Inhibition of H2-dependent methanogenesis was explained by successful competition by sulfate reducers for H2, as the H2 partial pressures decreased upon addition of sulfate. However, acetate concentrations did not decrease. Sulfate reduction was stimulated by H2, but not by acetate. Counts of acetate-utilizing sulfate reducers were relatively low both in fresh and pasteurized soil indicating that the bacteria were only present as spores. Inhibition of methanogenesis by chloroform resulted in accumulation of both H2 and acetate. When sulfate was added in addition, H2 accumulation stopped, but acetate still accumulated indicating that the activity of the methanogens was necessary for acetate conversion and that acetate could not be utilized by the sulfate reducers directly. Conversion of [2-14C]acetate resulted in formation of relatively more 14CO2, when sulfate was added, indicating that the methyl group of acetate was now being oxidized instead of reduced. Addition of chloroform strongly inhibited the conversion of [2-14C]acetate, even in the presence of sulfate. A conceivable explanation is sulfate-dependent interspecies H2 transfer between acetate-utilizing methanogens and H2-utilizing sulfate reducers, changing the electron flow from CH4 production to sulfate reduction. Addition of ferrihydrite resulted only in incomplete inhibition of methanogenesis which could be explained by successful competition of ferric iron reducers for H2. The ferric iron reducers were able to use acetate directly, but did not outcompete the methanogens.
The utility of tooth enamel microstructure in identifying isolated dinosaur teeth

Hwang, S.H. 2010: The utility of tooth enamel microstructure in identifying isolated dinosaur teeth. Lethaia, Vol. 43, pp. 307–322. The identification of isolated dinosaur teeth is frequently an uncertain process because dinosaur teeth are simple in morphology compared to those of mammals. Teeth among genera and species within major dinosaur clades are often identical, and damage or abrasion of teeth further complicates their identification. To aid diagnosis of isolated teeth, systematic descriptions of dinosaur teeth have been compiled, and quantitative morphometric identification methods have also been developed. However, these aids work best with relatively intact teeth. Enamel microstructure, in contrast, can be used to identify the minutest of tooth fragments as long as the entire enamel thickness, often <100 μm, is preserved. In addition, enamel microstructure can be used to differentiate isolated teeth that are similar in morphology but have different enamel, such as ankylosaur and posterior pachycephalosaurid or basal theropod and tyrannosaurid teeth. To evaluate the efficacy of enamel microstructure as an identification tool, nine isolated dinosaur teeth, specimens originally identified as ‘Carnosauria’ indet. , Theropoda indet. , Nanotyrannus sp. , Tyrannosauridae indet. , Troodontidae indet. , Pachycephalosauridae indet. , Hadrosaurinae indet. and cf. Thescelosaurus sp. , were sectioned and their enamel examined using scanning electron microscopy. Upon inspection of their enamel microstructure, three of the specimens could be identified to genus, and the taxonomic identity of all the specimens were better understood. While enamel microstructure may not always constrain the identity of an indeterminate tooth to the generic or species level, it usually allows for a more accurate identification. □Dinosaur teeth, enamel microstructure, taxonomic identification, microfossils.