Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying promotion effectiveness for a retailer

Retailers spend a substantial part of their marketing budgets on promotions. While promotions already account for a large share of retailers’ revenues, promotion intensity continues to increase. Despite substantial investments in promotions, companies often have little understanding of the true performance and thus struggle to determine which promotions are working and which are not. The objective of this thesis is to quantify the impact of sales promotions, which can help retailers to identify the most and the least effective promotions. This thesis addresses the research problem by seeking answers to three key questions. First, it studies whether promotions generate a lift in sales during the promotional period. Second, the extent to which the sales lift may cannibalize the sales of other non-promoted products in that category is determined. Lastly, this thesis investigates whether promotions affect the quantities sold in the weeks after the promotion. The promotion effects were quantified using a 2-year dataset of weekly point-of-sales (POS) data obtained from a Finnish retailer. During the study period, over 140,000 promotions were implemented in nearly 500 different product categories. The main findings of this thesis are threefold. First, about three quarters of promotions generate additional sales. The magnitude of this sales lift is about 130% in comparison to normal level of sales. The interquartile range of the sales lift measure falls between 17% and 381% indicating high variation among products. Second, approximately 40% of the sales lift accounts to switching from other non-promoted products in the same category. This indicates that on average only about 60% of the additional sales are truly incremental to retailers. Lastly, this thesis did not find evidence for stockpiling effects which refers to decreased quantities sold in the weeks after the promotion period. The results imply that not all promotions generate the desired results and that the effectiveness of promotions is significantly diluted due to switching. This means that retailers should focus promotional activities to products and categories that are more effective and generate a positive impact. Systematic analysis based on quantitative data applied in this thesis helps retailers to gain insights from a large set of data and understand the true performance of promotions while guiding effective promotional decisions in the future.
Comparison of two pretreatment methods for mercury stable isotope analysis in Antarctic moss

Mercury (Hg) stable isotope analysis can provide new insight for understanding the biogeochemistry and sources of Hg in the polar regions. To completely extract the low contents of Hg in polar samples and to avoid isotopic fractionation during the sample preparation stage, an effective and reliable pretreatment method is needed. In this work, two different pretreatment methods were compared for measuring Hg stable isotopes in Antarctic moss samples. One method was acid digestion (HNO3:H2O2=5:3, v/v) and the second was a combustion-trapping treatment with a trapping solution (HNO3:HCl=2:1, v/v). There were no significant differences in the analytical results obtained with the two methods. The overall mean values and uncertainties of total Hg (THg) and the isotopic compositions of Hg in the referenced materials were all in good agreement with the certified and reported values, indicating that both methods were accurate and applicable. Acid digestion is highly efficient, while the combustion-trapping method can be used to treat samples with low Hg content. The proposed methods were successfully used to determine the Hg isotopic compositions in moss samples collected from the Antarctic. Citation: Liu H W, Yu B, Shi J B, et al. Comparison of two pretreatment methods for mercury stable isotope analysis in Antarctic moss. Adv Polar Sci, 2017, 28(1): 75-80, doi: 10.13679/j.advps. 2017.1. 00075
Characterization of Prokaryotic Community Diversity in New and Aged Pit Muds from Chinese Luzhou-flavor Liquor Distillery

The quality and yield of Luzhou-flavor liquor is directly determined by the quality of pit mud from the Luzhou-flavor liquor distillery. The aged pit mud produces the good quality liquor while new pit mud dose not. The aim of this study was to investigate the prokaryotic community diversity between new and aged pit mud by high-throughput sequencing technique and the real-time quantitative PCR (qPCR) assay. Results indicated that diversities of prokaryotic community in new pit muds were higher than those in aged pit muds. The abundances of the phylum Bacteroidetes in aged pit muds were significantly (P < 0.05) higher than those in new pit muds, while the abundances of the genus Lactobacillus and Bacillus changed in the opposite trend. Additionally, the quantity of Clostridium Kluyveri in aged pit mud was higher than that in new pit mud. Bacteroidetes, Lactobacillus, Bacillus and C. kluyveri may be the potential indicator-like microbe to distinguish new and aged pit mud fast, conveniently and reliably by qPCR. Results presented in this study provide specific understanding of the differences in prokaryotic community between the new and aged pit muds, and have laid initial foundation for identifying aged pit mud and for advancing pit mud aged.
Assess the Possibility of Screening and Supervising Influenza A (H7N9) Virus-Infected Patients via Rapid Point-of-Care-Test Kit with Upper or Lower Respiratory Specimens

The purpose of this study was to assess the possibility of screening and supervising influenza A (H7N9) virus infected patients via rapid point-of-care-test kit with upper or lower respiratory specimens. Here, we demonstrate that the POCT kits can detect H7N9 virus (Guangzhou strain) in different type of samples, which obtained from upper and lower respiratory tract, via the simulated experiment. The detection limit ranged from 4 to 6 log10TCID50/mL and 2.78 × 107 to 1.05 × 108 copies/mL in PBS and nasopharyngeal swab solution (NSS) solutions respectively. Furthermore, the detection ranges were enhanced by 0.5 or 1 log10TCID50/mL in BALF or sputum solution (SS) diluents for some parts of the POCT kits. Furthermore, we observed that there were higher replication and longer screening of H7N9 virus in lower respiratory tract (LRT) samples, such as endotracheal aspirate (ETA) and sputum, from the H7N9 virus-infected patients, although the detection results of POCT kits were negative for these clinical samples. So that, we think that POCT kits can be used to screen and supervise H7N9 virus-infected patients if in the accurate timing. And the LRT samples, special ETA and sputum, seem a good sample option for detecting H7N9 virus via POCT kits, so we need pay more attention to the LRT samples when the new POCT kits were developed.
Simulation study of pressure and temperature dependence of the negative thermal expansion in Zn(CN) 2

Pressure and temperature dependence of the negative thermal expansion in Zn(CN)${}_{2}$ is fully investigated using molecular dynamics simulations with a built potential model. The advantage of this study is that it allows us to reproduce the exotic behaviors of the material, including the negative thermal expansion (NTE), the reduction of NTE with elevated temperature, the pressure enhancement of NTE, and the pressure-induced softening. Results of the study provide us detailed data to link the properties in the energy space and the real space, giving us insights to understand the properties and the connections between them.
Practical Paper The practical application of computational fluid dynamics to dissolved air flotation, water treatment plant operation, design and development

Tony Amato Enpure Ltd, Enpure House, Woodgate Business Park, Kettleswood Drive, Birmingham B323DB, UK E-mail: tamato@enpure.co.uk Jim Wicks The Fluid Group, Magdalen Centre, The Oxford Science Park, Oxford OX44GA, UK E-mail: jim.wicks@thefluidgroup.com Computational fluid dynamics (CFD) can be applied to the advancement of dissolved air flotation (DAF) plant design. The use of CFD in design and predictive analysis, in particular here with reference to the upgrading of an existing DAF plant from 30 to 60Ml/d and associated diagnostics, while still developing, helped by the emergence of ever more powerful computational systems, can be regarded as an established tool providing beneficial and useful data, although on occasions care may be required in the interpretation of results. The initial CFD studies were undertaken using the existing and upgraded works flows and structures at both ‘low’ and ‘high’ temperatures, i.e. 2 and 208C, while the modelling results are reported using graphical representations of ‘contours of flow velocity’ and ‘velocity vectors’. In addition the degree of short circuiting based on T10 together with other retention parameters T50 and T50/m are reported. Further modifications were also considered: how changes to the incline baffle and tank depth can impact on the predicted distribution, vorticity and in practice on the actual subnatant water quality measured in terms of turbidity. Finally applying CFD to DAF plant design is shown to be a beneficial tool for the designer.
A char-based seq 2 seq submission to the E 2 E NLG Challenge

The paper accompanies our submission to the E2E NLG Challenge. This task involves generating human understandable utterances from slot-value pair Meaning Representations (or dialogue acts). Recently, word based neural network approaches (particularly Sequenceto-Sequence based approaches) came into prominence which resorted to a pre(respectively post-) processing step called delexicalization (relexicalization) to handle the rare word problem. In contrast, we first train a character level seq2seq model with attention mechanism which requires no pre/postprocessing (delexicalization, tokenization or even lowercasing). The utterances generated by this model are rated excellent in terms of fluency as well as quite reasonable in adequacy, the primary downside being the possible omission of semantic material (slot values). However, in a significant number of cases, a perfect solution can be found in the top-k list. Thus, for further improvement, we explore two different re-ranking approaches to score candidates. During the process, we also introduce a synthetic dataset creation procedure, which opens up new directions for creating artificial datasets for Natural Language Generation.
Hartree corrections in a mean-field limit for fermions with Coulomb interaction

We consider the many-body dynamics of fermions with Coulomb interaction in a mean-field scaling limit where the kinetic and potential energy are of the same order for large particle numbers. In the considered limit the spatial variation of the mean-field is small. We prove two results about this scaling limit. First, due to the small variation, i.e., small forces, we show that the many-body dynamics can be approximated by the free dynamics with an appropriate phase factor with the conjectured optimal error term. Second, we show that the Hartree dynamics gives a better approximation with a smaller error term. In this sense, assuming that the error term in the first result is optimal, we derive the Hartree equations from the many-body dynamics with Coulomb interaction in a mean-field scaling limit.
The Pushshift Reddit Dataset

Social media data has become crucial to the advancement of scientific understanding. However, even though it has become ubiquitous, just collecting large-scale social media data involves a high degree of engineering skill set and computational resources. In fact, research is often times gated by data engineering problems that must be overcome before analysis can proceed. This has resulted recognition of datasets as meaningful research contributions in and of themselves.Reddit, the so called “front page of the Internet,” in particular has been the subject of numerous scientific studies. Although Reddit is relatively open to data acquisition compared to social media platforms like Facebook and Twitter, the technical barriers to acquisition still remain. Thus, Reddit's millions of subreddits, hundreds of millions of users, and billions of comments are at the same time relatively accessible, but time consuming to collect and analyze systematically.In this paper, we present the Pushshift Reddit dataset. Pushshift is a social media data collection, analysis, and archiving platform that since 2015 has collected Reddit data and made it available to researchers. Pushshift's Reddit dataset is updated in real-time, and includes historical data back to Reddit's inception. In addition to monthly dumps, Pushshift provides computational tools to aid in searching, aggregating, and performing exploratory analysis on the entirety of the dataset. The Pushshift Reddit dataset makes it possible for social media researchers to reduce time spent in the data collection, cleaning, and storage phases of their projects.
Intermittent Pulling with Local Compensation for Communication-Efficient Federated Learning

Federated Learning is a powerful machine learning paradigm to cooperatively train a global model with highly distributed data. A major bottleneck on the performance of distributed Stochastic Gradient Descent (SGD) algorithm for large-scale Federated Learning is the communication overhead on pushing local gradients and pulling global model. In this paper, to reduce the communication complexity of Federated Learning, a novel approach named Pulling Reduction with Local Compensation (PRLC) is proposed. Specifically, each training node intermittently pulls the global model from the server in SGD iterations, resulting in that it is sometimes unsynchronized with the server. In such a case, it will use its local update to compensate the gap between the local model and the global model. Our rigorous theoretical analysis of PRLC achieves two important findings. First, we prove that the convergence rate of PRLC preserves the same order as the classical synchronous SGD for both strongly-convex and non-convex cases with good scalability due to the linear speedup with respect to the number of training nodes. Second, we show that PRLC admits lower pulling frequency than the existing pulling reduction method without local compensation. We also conduct extensive experiments on various machine learning models to validate our theoretical results. Experimental results show that our approach achieves a significant pulling reduction over the state-of-the-art methods, e.g., PRLC requiring only half of the pulling operations of LAG.
Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures

This paper shows that deep learning (DL) representations of data produced by generative adversarial nets (GANs) are random vectors which fall within the class of so-called \textit{concentrated} random vectors. Further exploiting the fact that Gram matrices, of the type $G = X^T X$ with $X=[x_1,\ldots,x_n]\in \mathbb{R}^{p\times n}$ and $x_i$ independent concentrated random vectors from a mixture model, behave asymptotically (as $n,p\to \infty$) as if the $x_i$ were drawn from a Gaussian mixture, suggests that DL representations of GAN-data can be fully described by their first two statistical moments for a wide range of standard classifiers. Our theoretical findings are validated by generating images with the BigGAN model and across different popular deep representation networks.
Psychological Capital and University Students’ Entrepreneurial Intention in China: Mediation Effect of Entrepreneurial Capitals

The aim of this study was to identify the influences of psychological capital (PC) on students’ entrepreneurial intention (EI) in China’s universities. The mediating effects of Entrepreneurial Capitals were also examined. Based on the analysis of the traditional capital and PC, the paper proposes that traditional capital is the direct factor to drive the behavior of entrepreneurship, while psychological factors do not directly affect EI, but improve EI by influencing traditional capital. A total of 1914 responses from universities in southeast China were analyzed using the structural equation modeling (SEM) approach to test study hypotheses. Results show that PC has a significant indirect impact on students’ EI only through traditional financial, human, and social capital (SC). These results support the mediating role of the traditional entrepreneurial capitals in explaining the relationship between PC and EI. Additionally, the impact of SC on EI is higher than that of financial and human capital (HC). Finally, research limitations and implications are discussed and future research directions are suggested.
Grasping Microgestures: Eliciting Single-hand Microgestures for Handheld Objects

Single-hand microgestures have been recognized for their potential to support direct and subtle interactions. While pioneering work has investigated sensing techniques and presented first sets of intuitive gestures, we still lack a systematic understanding of the complex relationship between microgestures and various types of grasps. This paper presents results from a user elicitation study of microgestures that are performed while the user is holding an object. We present an analysis of over 2,400 microgestures performed by 20 participants, using six different types of grasp and a total of 12 representative handheld objects of varied geometries and size. We expand the existing elicitation method by proposing statistical clustering on the elicited gestures. We contribute detailed results on how grasps and object geometries affect single-hand microgestures, preferred locations, and fingers used. We also present consolidated gesture sets for different grasps and object size. From our findings, we derive recommendations for the design of microgestures compatible with a large variety of handheld objects.
A statistical study of the correlation of Galactic supernova remnants and spiral arms

The distribution of observed giant H II regions and supernova remnants (SNRs) in Galactic longitude is analyzed with Monte Carlo models to determine the possible correlation with spiral arms or disk populations. The novel feature of the current analysis is that it depends mainly on the angular distribution of the H II regions and SNRs and hence is independent of distance.
Oral Presentation (PAT-3) In Vitro Growth Inhibition Activities of Natural (nCaIFN) and Recombinant (rCaIFN) Canine Interferons on Three Different Tumor-Derived Cell Lines

INTRODUCTION Recently, from many kinds of diseases one could be counted is a tumor disease. Tumor is a degenerative disease that involved many biological pathways within the host. A tumor or neoplasm can be defined as a disturbance of growth characterized by excessive, abnormal and uncontrolled proliferation of transformed or altered cell(s) at one or more primary points within the host, and frequently at one or more metastatic sites (Priosoeryanto, 1994). The treatment of tumor is mostly by medical surgery which usually combined with chemotherapeutic agent(s), unfortunately the using of chemotherapeutic agent can develop a seriously side effect to the treated-patients. Biological substances like interferon (IFN) known as anti-virus agent is also one of promising candidate for treating or preventing of tumor disorders. Feline and canine squamous cell carcinoma is one of tumor type that often found in cat and dog, and mostly develop to a very aggressive disorder. The using of in vitro cell culture is a way to avoid the use of live animals on the study of tumors especially the study of antitumor agent due to can mimic the in vivo condition. The aim of the present study is to examine the growth inhibition activity of natural and recombinant canine interferon in order to find the suitable biological substances for combating tumor disorder especially in the field of veterinary medicine and also as an information for the development of tumor treatment in the human medical side.
Flight to Liquidity and the Cross-Section of Stock Returns

We design an intuitive yet simple measure of market liquidity (TC) to capture “flight to liquidity” aspect of the liquidity risk. TC is constructed as the ratio of total trade volume of stocks in the top trading volume quintile to that in the bottom. Its variation captures the liquidity shift between the most liquid (highest quality) and the least liquid (lowest quality) stocks, intensified during the flight to liquidity. Among the liquidity risk factors, one constructed from TC (TC factor) is the most effective in yielding evidence consistent with the predictions of popular models of flight to liquidity. TC is a priced state variable whose pricing impact is beyond those of existing liquidity measures. Annualized return spread between top and bottom quintiles of TC factor loading sorted portfolios is about 5%. JEL: G11, G12
Pulsed Vacuum Osmotic Dehydration of Cherry Tomatoes: Impact on Physicochemical Properties and Probiotics Entrapment

Osmotic dehydration (OD) and pulsed vacuum osmotic dehydration (PVOD) were employed to assess the various properties of partially-dehydrated tomatoes. Ascorbic acid and lycopene degradation and color and texture change were determined. The mastership incorporation of probiotics ( Lactobacillus acidophilus TISTR 1338) into tomatoes was also investigated. OD mediums (20, 40 and 60 °Brix) consisted of a mixture of formulated tomato extract (FTE) and probiotic cell suspension. PVOD promoting mass transfer was clearly observed in a short-time process compared with OD. The physical and chemical properties of the tomatoes changed significantly after the dehydration processes, especially those of ascorbic acid content compared with lycopene. A more than 50 % loss of ascorbic acid was noted, starting at 10 g /100 g tomatoes of water loss. The hardness values significantly increased, while chroma values decreased. The cell entrapment on the tomatoes was in the range of 8 - 9 log CFU/g tomatoes. The highest entrapment of the probiotic bacteria was found in the long-time process (12 h) conducted with 20°Brix FTE for the PVOD and OD processes, while entrapment was decreased by the short-time process (6 h). Using high solution concentration resulted in lower cell entrapment. However, cell entrapment could be increased by using the vacuum process. These results will provide a platform that encourages the inclusion of probiotics in high quality fresh-cut products and semi-moist products. These products can then be considered as alternative probiotic food choice for consumers. doi: 10.14456/WJST.2016. 19
Impact of Monetary Policy (Interest Rate) Regimes on the Performance of the Banking Sector in Nigeria

This paper examined the impact of monetary policy regimes on the performance of ommercial banks in Nigeria. The paper used Descriptive and Ex-post Facto Research Design. It utilized time series data collected from Central Bank of Nigeria Bulletin. The study was divided into SAP Period (1986-1999) and Post SAP Period (2000 -2013). Eight Research Questions and eight Hypotheses were raised for the study. Regression and Pearson Product Moment Correlation technique were used to analyze the data collected while t-test statistic was employed in testing the hypotheses. Monetary Policy Rate was the independent variable while Total Assets Value, Deposit Mobilization, Loans and Advances and Credit to the Private Sector were the dependent variable in different regression equations. The study discovered that Monetary Policy Rate during the SAP Period did not have significant impact on the Total Assets Value, Deposit Mobilization, Loans and Advances and Credit to the Private Sector while Monetary Policy Rate during the Post SAP Period had significant impact on the Total Assets Value, Deposit Mobilization, Loans and Advances and Credit to the Private Sector respectively. The paper recommended that policy makers should administer the Monetary Policy instruments to ensure they are effective in generating and stimulating the desired level of economic activity in the banking sector. It further recommended that political interferences which distort the performance in the banking industry be minimized.