Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Sequence Alignment Method to Product Assortment and Shelf Space Allocation

In retailing, decisions about product assortment and shelf space allocation have a significant effect on customers’ purchasing decisions. Traditionally, researchers usually employed the space elasticity to optimize product assortment and space allocation models. However, the large number of parameters requiring to estimate and the nonlinear nature of space elasticity can reduce the efficacy of the space elasticity based models. Instead of space elasticity, this paper utilizes a data mining approach, Sequence Alignment Method (SAM), to resolve the product assortment and allocation problems in retailing. In our approach, the SAM is applied to explore the relationships between product categories and is compared to association rule mining. Experimental results show that SAM achieves better quality than that of association rule mining and can generate very useful information to shelf space management.
Management of mobile dynamic adaptation in Cyber-Physical Systems

The general idea of CPS (Cyber-Physical Systems) is integrating information systems with the physical world. Thus, CPS require a dynamic global network infrastructure where devices are enabled to autonomously adapt to the cyber and physical world events. Conversely, devices frequently are mobile devices that can be moved or can move by themselves, such as sensors and actuators. Current solutions for building CPS do not provide the required support to handle changes in the cyber/physical context and in particular, deal with the devices' mobility. In this paper, we present an approach that supports distributed dynamic software adaptations among mobile devices.
Approximating the stochastic knapsack problem: the benefit of adaptivity

We consider a stochastic variant of the NP-hard 0/1 knapsack problem in which item values are deterministic and item sizes are independent random variables with known, arbitrary distributions. Items are placed in the knapsack sequentially, and the act of placing an item in the knapsack instantiates its size. Our goal is to compute a solution "policy" that maximizes the expected value of items placed in the knapsack, and we consider both non-adaptive policies (that designate a priori a fixed sequence of items to insert) and adaptive policies (that can make dynamic choices based on the instantiated sizes of items placed in the knapsack thus far). We show that adaptivity provides only a constant-factor improvement by demonstrating a greedy non-adaptive algorithm that approximates the optimal adaptive policy within a factor of 7. We also design an adaptive polynomial-time algorithm which approximates the optimal adaptive policy within a factor of 5 + /spl epsiv/, for any constant /spl epsiv/ > 0.
A dynamic match between business model and firm growth: The case of Chint group

Research on business model emerges as a promising area. This article aims at exploring a dynamic match between business model and firm growth. Through a longitudinal study of a Chinese private manufacturing firm with a history of more than twenty years, it is indicated that, when moving from initial stage to adjusting and then to expansion stage, the firm experiences a significant change along three dimensions of business model: value proposition, value creation, and value system integration. The contribution of this article is fourfold: understanding firm growth process from a perspective of business model; reconceptualizing business model; extending the scope where business model can be applied; uncovering the dynamics of business model.
Adaptive Rates of Convergence in Active Learning

We study the rates of convergence in classification error achievable by active learning in the presence of label noise. Additionally, we study the more general problem of active learning with a nested hierarchy of hypothesis classes, and propose an algorithm whose error rate provably converges to the best achievable error among classifiers in the hierarchy at a rate adaptive to both the complexity of the optimal classifier and the noise conditions. In particular, we state sufficient conditions for these rates to be dramatically faster than those achievable by passive learning.
Hereditary Vitamin D Resistant Rickets: Clinical, Laboratory, and Genetic Characteristics of 2 Iranian Siblings

Purpose and Methods Hereditary vitamin D resistant rickets (HVDRR) is a rare disease that presents with signs and symptoms of rickets, alopecia, and growth retardation during the early years of life. The disease is caused by mutations in the vitamin D receptor (VDR) gene, which leads to unresponsiveness of the mutant receptor to 1-25(OH) 2 D3. The disease is transmitted as an autosomal recessive disorder and is found with equal frequency in males and females. The disease is rarely encountered and only about 100 cases are reported so far. The current paper reported the clinical and laboratory characteristics of 2 Iranian siblings with this disorder. Results and Conclusion They presented with rickets, growth retardation, muscle weakness, hypocalcemia and alopecia totalis since early childhood, and were followed up for 27 years. Sequencing of the DNA extracted from the peripheral white blood cells showed a missense G to A mutation in exon number 4 (g.30994 G > A) that led to the methionine substitution for the naturally occurring valine at position 26 in the DNA binding domain (DBD) of the VDR.
Towards a librarian of the web

If the World Wide Web (WWW) is considered to be a huge library, it would need a librarian, too. Google and other web search engines are more or less just keyword databases and cannot fulfil this person's tasks in a sufficient manner. Therefore, an approach to improve cataloguing and classifying documents in the WWW is introduced and its efficiency demonstrated in first simulations.
A framework for retrieval and annotation in digital humanities using XQuery full text and update in BaseX

A key difference between traditional humanities research and the emerging field of digital humanities is that the latter aims to complement qualitative methods with quantitative data. In linguistics, this means the use of large corpora of text, which are usually annotated automatically using natural language processing tools. However, these tools do not exist for historical texts, so scholars have to work with unannotated data. We have developed a system for systematic, iterative exploration and annotation of historical text corpora, which relies on an XML database (BaseX) and in particular on the Full Text and Update facilities of XQuery.
Soft Load Balancing Over Heterogeneous Wireless Networks

Ongoing next-generation networks are expected to be deployed over current existing networks in the form of overlayed heterogeneous networks, particularly in hot-spot areas. Therefore, it will be necessary to develop an interworking technique, such as load balancing, to achieve increased overall resource utilization in the various heterogeneous networks. In this paper, we present a new load-balancing mechanism termed ldquosoftrdquo load balancing, where the Internet Protocol (IP) traffic of a user is divided into subflows, each of which flows into a different access network. The terminology of soft load balancing involves the use of both load-sharing and handover techniques. Through a numerical analysis, we obtain an optimal load-balancing ratio (LBR) to determine the volume of traffic delivered to each network over an overlayed multicell environment. Using the optimal LBR, a more reliable channel transmission can be achieved by efficiently reducing the outage probability for given user traffic.
PRELIMINARY MODEL FOR OXALATE FORMATION IN EVAPORATOR SCALE

A comparison of a standard and a typical scale chromatogram is shown in Figure 1. The phosphate value by this method may be lower than the true value due to incomplete et al., 1953) based on the change in absorbance at 520 nm of a ferri-salicylate complex on. addition of oxalate. Details are described in Appendix 2. Titratable acidity in clear juice (10 g) and syrup (5 g) was measured on a Metrohm E346 Potentiograph using 0,1 N sodium hydroxide and titrated to an end point of pH 8,1.
Optimal Trading in a Dynamic Market

We consider the problem of mean-variance optimal agency execution strategies, when the market liquidity and volatility vary randomly in time. Under specific assumptions for the stochastic processes satisfied by these parameters, we construct a Hamilton-Jacobi-Bellman equation for the optimal cost and strategy. We solve this equation numerically and illustrate optimal strategies for varying risk aversion. These strategies adapt optimally to the instantaneous variations of market quality. A fundamental part of agency algorithmic trading in equities and other asset classes is trade scheduling. Given a trade target, that is, a number of shares that must be bought or sold before a fixed time horizon, trade scheduling means planning how many shares will be bought or or sold by each time instant between the beginning of trading and the horizon. Grinold and Kahn (1995) and Almgren and Chriss (2000) suggested that the optimal trajectory could be determined by balancing market impact cost, which leads toward slow trading, against volatility risk which pushes toward rapid completion of the order. This framework leads to an “efficient frontier,” in which the trade schedule is selected from a one-parameter family based on a risk aversion parameter that must be specified by the trading client. While other factors such as anticipated price drift, serial correlation or other short-term signals, and daily patterns, are certainly important, this fundamental “arrival price” framework has proven remarkably robust and useful in designing practical trading systems. A fundamental assumption of most of this work has been that the market parameters, such as liquidity and volatility, are constant or at least have known predictable profiles. This assumption is reasonably accurate for large-cap US stocks. Under that assumption, optimal strategies are static; that is, the trade schedule can be determined before trading starts and is not modified by the new information revealed by price moves during trading. (Almgren and Chriss (2000) ∗New York University Courant Institute and Quantitative Brokers, almgren@cims.nyu. edu
Mining Frequent Itemsets from Noisy Data

As we face huge amounts of varied information, data mining, which helps us discover hidden features or rules from voluminous data systematically, has become more important [3, 4, 6, 10]. However, real world data is often dirty, including noise such as missing or irrelevant values. The information mined from such noisy data may be incorrect. We model noisy data with probabilities, assuming that noise is mixed with data statistically. We also propose a way to find frequent itemsets [2] by estimating supports on noiseless data from noisy data. An algorithm using FP-tree [6, 10] is also presented to mine frequent itemsets efficiently.
Effects of rosuvastatin and/or β-carotene on non-alcoholic fatty liver in rats

The prevalence of non-alcoholic fatty liver disease (NAFLD) has markedly increased, especially in patients exhibit one or more features of the metabolic syndrome. This study investigates the effect of rosuvastatin (RSV) and/or β-carotene (βC) in NAFLD-induced rats. Rats were classified into nine groups; normal (I), NAFLD-induced with high-fat diet (HFD; II), NAFLD switched to regular diet (RD; III), NAFLD-HFD or NAFLD-RD treated with RSV (IV, V), βC (VI, VII) or both RSV+βC (VIII, IX), respectively. After four weeks, rats were sacrificed to obtain serum samples and liver tissues. Liver histology, lipid profile, liver oxidative stress markers, and adipocytokines were measured. Liver sections of rats with NAFLD-HFD revealed steatosis, lose of hepatic architecture, inflammation and hepatocyte vacuolation with high percentage of cell fibrosis. Serum levels of ALT, AST, ALP, gamma glutamyl transferase (GGT) and lipid profile (triglycerides, cholesterol, LDL and VLDL) were significantly increased (P<0.05) compared with normal. Also, hepatic malondialdehyde level and serum leptin, tumor necrosis factor-alpha (TNF-α) and transforming growth factor-β1 (TGF-β1) were increased. Meanwhile, superoxide dismutase (SOD) activity, GSH content in liver, serum HDL and adiponectin were decreased (P<0.05) vs normal. These changes were observed to a lesser extent in NAFLD-RD group. Administration of RSV or/and βC almost improved all previously mentioned parameters. Moreover, hepatic steatosis was decreased and inflammation was markedly ameliorated with reduction of TNF-α and TGF-β. These results were more pronounced in the groups VIII and IX vs each drug alone. In conclusion RSV and βC could be beneficial for the treatment and prevention of NAFLD. Combined RSV with βC is more effective than RSV alone.
Real-Time Deep Video SpaTial Resolution UpConversion SysTem (STRUCT++ Demo)

Image and video super-resolution (SR) has been explored for several decades. However, few works are integrated into practical systems for real-time image and video SR. In this work, we present a real-time deep video SpaTial Resolution UpConversion SysTem (STRUCT++). Our demo system achieves real-time performance (50 fps on CPU for CIF sequences and 45 fps on GPU for HDTV videos) and provides several functions: 1) batch processing; 2) full resolution comparison; 3) local region zooming in. These functions are convenient for super-resolution of a batch of videos (at most 10 videos in parallel), comparisons with other approaches and observations of local details of the SR results. The system is built on a Global context aggregation and Local queue jumping Network (GLNet). It has a thinner and deeper network structure to aggregate global context with an additional local queue jumping path to better model local structures of the signal. GLNet achieves state-of-the-art performance for real-time video SR.
rILYd4, a Human CD59 Inhibitor, Enhances Complement-Dependent Cytotoxicity of Ofatumumab against Rituximab-Resistant B-cell Lymphoma Cells and Chronic Lymphocytic Leukemia

Purpose: Ofatumumab is an anti-CD20 antibody recently approved for treatment of fludarabine and alemtuzumab refractory chronic lymphocytic leukemia (CLL); it mediates much stronger complement-dependent cytotoxicity (CDC) than rituximab. Human CD59, a key membrane complement regulator that inhibits CDC, is highly expressed in B-cell malignancies and its upregulation is an important determinant of the sensitivity of B-cell malignancies to rituximab treatment. Previously, we have shown that the potent CD59 inhibitor rILYd4 sensitizes rituximab-resistant lymphoma cells to rituximab-mediated CDC. Here, we further investigated whether rILYd4 can sensitize B-cell malignancies to ofatumumab-mediated CDC and whether either ofatumumab-mediated CDC or rILYd4-enhanced ofatumumab-mediated CDC correlates with CD20 or CD59 expression, known biomarkers involved in rituximab activity. Experimental Design: Rituximab-resistant cell lines and primary CLL cells were used to investigate the antitumor efficacy of the combination of rILYd4 with ofatumumab or rituximab. Propidium iodide staining or alamarBlue assay were used to evaluate the CDC effect. The levels of CD20 and CD59 on the cell membrane were analyzed by flow cytometry. Results: rILYd4 enhanced CDC effects mediated by ofatumumab or rituximab on rituximab-resistant lymphoma cells and primary CLL cells in vitro. The sensitivity to CDC effects mediated by ofatumumab positively correlated with the ratio of CD20/CD59 and negatively correlated with CD59 levels on CLL cells. The degree to which rILYd4 enhanced CDC correlated positively with the CD59 levels on CLL cells. Conclusions: These data suggest that rILYd4 may enhance the anticancer activity of ofatumumab and rituximab in B-cell malignancies that have relapsed after prior antibody-based therapies. Clin Cancer Res; 17(21); 6702–11. ©2011 AACR.
Unique opportunity to harness polarization in GaN to override the conventional power electronics figure-of-merits

Summary form only given. Owing to the large breakdown electric field (Eb), wide bandgap semiconductors (WBGs) such as SiC, GaN, Ga2O3 and diamond based power devices are the focus for next generation power switching applications. The unipolar trade-off relationship between the area specific-on resistance (Ron,sp) and breakdown voltage (BV) is often employed to compare the performance limitation among various materials. The advanced features in benchmarking power devices include conduction modulation and superjunction in devices taking advantage of bipolar conduction. To this end, the GaN material system has a unique advantage due to its prominent spontaneous and piezoelectric polarization effects in GaN, AlN, InN, AlxInyGaN alloys and flexibility in inserting appropriate heterojunctions thus dramatically broaden the device design space. For instance, AlxGaN, which has a larger bandgap, can be designed into the highest field region. Another enabling feature in the GaN material system is polarization doping or Pi-doping: by compositionally grading AlxInyGaN, both electron and hole doping can be achieved, exhibiting the ideal dopant behavior - no temperature dependence or frequency dependence! This dopant characteristics can't be taken for granted for WBGs based on the knowledge in Si. Pi-doping is an extremely powerful attribute since all wide bandgap semiconductors face the challenge of deep dopants while this ideal solution exists in GaN.
Faucet: a user-level, modular technique for flow control in dataflow engines

This document presents Faucet, a modular flow control approach for distributed data-parallel dataflow engines with support for arbitrary (cyclic) topologies. When compared to existing backpressure techniques Faucet has the following differentiating characteristics: (i) the implementation only relies on existing progress information exposed by the system and does not require changes to the underlying dataflow system, (ii) it can be applied selectively to certain parts of the dataflow graph, and (iii) it is designed to support a wide variety of use cases, topologies and workloads. We demonstrate Faucet on an example computation for efficiently determining a cyclic join of relations, whose variability in rates of produced and consumed tuples challenges the flow control techniques employed by systems like Storm, Heron, and Spark. Our implementation, prototyped in Timely Dataflow, introduces flow control at critical locations in the computation, keeping the computation stable and resource-bound while introducing at most 20% runtime overhead over an unconstrained implementation. Our experience is that the information Timely Dataflow provides to user logic is sufficient for a variety of flow control and scheduling tasks, and merits further investigation.
Airway injury in an in vitro human epithelium-fibroblast model of diacetyl vapor exposure: diacetyl-induced basal/suprabasal spongiosis

Abstract Inhalation exposure to diacetyl (DA) is associated with obliterative bronchiolitis (OB) in workers and induces OB-like fibrotic airway lesions in rats. The pathogenesis of OB is poorly understood in part due to complex interactions between airway epithelial, mesenchymal and blood-derived inflammatory cells. DA-induced airway toxicity in the absence of recruited-inflammatory/immune cells was characterized using an air-liquid interface (ALI) model consisting of human airway epithelium with (Epi/FT) and without (Epi) a mesenchymal component. ALI cultures were exposed to 25 mM DA-derived vapors (using vapor cups) for 1 h on day 0, 2 and 4. In some experiments, the tissues were exposed to 2,3-hexanedione (Hex) which is structurally-similar, but much less fibrogenic than DA. Lactate dehydrogenase activity and day 6 histopathologic changes associated with epithelial injury, including basal/suprabasal spongiosis, were increased following exposure of Epi/FT tissues to DA but not control or Hex vapors. IL-1a, IL-6, IL-8, sIL-1Ra, TGFa, MCP-3 and TNFa proteins were increased following DA exposure of Epi/FT tissues; only IL-1a, IL-8, sIL-1Ra and TGFa were increased following exposure of Epi tissues. MMP-1, MMP-3 and TIMP-1 proteins were increased following DA exposure of Epi/FT tissues; whereas MMP-2, MMP-7 and TIMP-2 were decreased, and production was largely dependent upon the presence of sub-epithelial stromal matrix/fibroblasts. Hex-induced protein changes were minimal. This in vitro study demonstrated that exposure of human airways to DA vapors induced epithelial injury (with the histopathologic feature of basal/suprabasal spongiosis) and increased release of pro-inflammatory and pro-fibrotic cytokines/chemokines as well as MMPs/TIMPs in the absence of recruited-inflammatory cells.
Parafoveal-on-foveal effects on eye movements during reading

Parafoveal-on-foveal effects refer to the possibility that processing of the parafoveal word can influence the fixation durations on the foveal word during reading. In this Chapter, I will review the literature of studies examining this issue. Effects observed in reading-like tasks have been questioned on methodological grounds with regards to the generalisibility to normal reading. The clearest evidence for the existence of parafoveal-on-foveal effects comes from experiments allowing tight control over the stimuli but restricting the observations to fixation locations very close to the parafoveal word, and from corpus studies showing reliable but numerically small effects. I will make the claim that with regards to taking reported parafoveal-on-foveal effects as evidence for parallel lexical processing, the jury is still out. The argument is that as long as parafoveal-on-foveal effects are numerically small and difficult to replicate in a controlled experiment, they can be explained on the basis of mislocated fixations, machine error and binocular disparity. These latter three influences can create apparent parafoveal-on-foveal effects without being linked to parallel lexical processing.
Validation of sub-sentential paraphrases acquired from parallel monolingual corpora

The task of paraphrase acquisition from related sentences can be tackled by a variety of techniques making use of various types of knowledge. In this work, we make the hypothesis that their performance can be increased if candidate paraphrases can be validated using information that characterizes paraphrases independently of the set of techniques that proposed them. We implement this as a bi-class classification problem (i.e. paraphrase vs. not paraphrase), allowing any paraphrase acquisition technique to be easily integrated into the combination system. We report experiments on two languages, English and French, with 5 individual techniques on parallel monolingual parallel corpora obtained via multiple translation, and a large set of classification features including surface to contextual similarity measures. Relative improvements in F-measure close to 18% are obtained on both languages over the best performing techniques.
Rate coding vs. temporal coding - is optimum between?

In this paper, we consider a novel approach to information representation in spiking neural networks. In a certain sense it is a combination of two well-known coding schemes - rate coding and temporal coding. Namely, it is based on asynchronous activity of ensembles of polychronous neuronal groups - groups of neurons firing in determined order with strictly fixed relative temporal delays. We demonstrate how a rate-coded input signal may be converted into this representation form by network structures which are formed as a result of network self-organization process based on STDP-style synaptic plasticity.