Miracle-dz/UniFAR-FTUs huggingface dataset:
Production, Manufacturing and Logistics An integrated product returns model with logistics and marketing coordination

We develop an integrated approach for analyzing logistics and marketing decisions within the context of designing an optimal returns system for a retailer servicing two distinct market segments. At the operational level, we show that the optimal refund price is not unique. Moreover, it is such that if both market segments return a purchased product, then neither segment will receive a full money-back refund; and it is such that if one or both segments do not return a purchased product, then a refund premium over the purchase price is possible, but the refund premium will not be enough to offset a customers total net cost of purchase and return. We also show that any improvement to the returns system that results in increased logistical efficiency or marketing effectiveness will be accompanied by an increase in the selling price of the product. At the strategic level, we show that if the retailer does not coordinate its logistics and marketing efforts to improve the overall returns system, then it will tend to over-invest in one of the functions and under-invest in the other. Finally, we illustrate how our model can be generalized to the case in which a customer se x post valuation of the product falls along a continuum. 2003 Elsevier B.V. All rights reserved.
Daily Prediction of Major Stock Indices from Textual WWW Data

We predict stock markets using information contained in articles published on the Web. Mostly textual articles appearing in the leading and the most influential financial newspapers are taken as input. From those articles the daily closing values of major stock market indices in Asia, Europe and America are predicted. Textual statements contain not only the effect (e.g., stocks down) but also the possible causes of the event (e.g., stocks down because of weakness in the dollar and consequently a weakening of the treasury bonds). Exploiting textual information therefore increases the quality of the input. The forecasts are available real-time via www.cs. ust.hk/~beat/Predict daily at 7:45 am Hong Kong time. Hence all predictions are available before the major Asian markets start trading. Several techniques, such as rule-based, k-NN algorithm and neural net, have been employed to produce the forecasts. Those techniques are compared with one another. A trading strategy based on the system's forecast is suggested.
First-principles structure prediction of extreme nanowires

Low-dimensional systems are an important and intensely studied area of condensed matter physics. When a material is forced to adopt a low-dimensional structure, its behaviour is often dramatically different to that of the bulk phase. It is vital to predict the structures of low-dimensional systems in order to reliably predict their properties. To this end, the ab initio random structure searching (AIRSS) method, which has previously been used to identify the structures of bulk materials, has been extended to deal with the case of nanowires encapsulated inside carbon nanotubes. Such systems are a rapidly developing area of research with important nanotechnological applications, including information storage, energy storage and chemical sensing. The extended AIRSS method for encapsulated nanowires (ENWs) was implemented and used to identify the structures formed by germanium telluride, silver chloride, and molybdenum diselenide ENWs. In each of these cases, a number of novel nanowire structures were identified, and a phase diagram predicting the ground state nanowire structure as a function of the radius of the encapsulating nanotube was calculated. In the case of germanium telluride, which is a technologically important phase-change material, the potential use of GeTe ENWs as switchable nanoscale memory devices was investigated. The vibrational properties of silver chloride ENWs were also considered, and a novel scheme was developed to predict the Raman spectra of systems which can be decomposed into multiple weakly interacting subsystems. This scheme was used to obtain a close approximation to the Raman spectra of AgCl ENWs at a fraction of the computational cost that would otherwise be necessary. The encapsulation of AgCl was shown to produce substantial shifts in the Raman spectra of nanotubes, providing an important link with experiment.
Decoding visual information from a population of retinal ganglion cells.

Decoding visual information from a population of retinal ganglion cells. J. Neurophysiol. 78: 2336-2350, 1997. This work investigates how a time-dependent visual stimulus is encoded by the collective activity of many retinal ganglion cells. Multiple ganglion cell spike trains were recorded simultaneously from the isolated retina of the tiger salamander using a multielectrode array. The stimulus consisted of photopic, spatially uniform, temporally broadband flicker. From the recorded spike trains, an estimate was obtained of the stimulus intensity as a function of time. This was compared with the actual stimulus to assess the quality and quantity of visual information conveyed by the ganglion cell population. Two algorithms were used to decode the spike trains: an optimized linear filter in which each action potential made an additive contribution to the stimulus estimate and an artificial neural network trained by back-propagation to match spike trains with stimuli. The two methods performed indistinguishably, suggesting that most of the information about this stimulus can be extracted by linear operations on the spike trains. Individual ganglion cells conveyed information at a rate of 3.2 +/- 1.7 bits/s (mean +/- SD), with an average information content per spike of 1.6 bits. The maximal possible rate of information transmission compatible with the measured spiking statistics was 13.9 +/- 6.3 bits/s. On average, ganglion cells used 22% of this capacity to encode visual information. When a decoder received two spike trains of the same response type, the reconstruction improved only marginally over that obtained from a single cell. However, a decoder using an ON and an OFF cell extracted as much information as the sum of that obtained from each cell alone.Thus cells of opposite response type encode different and nonoverlapping features of the stimulus. As more spike trains were provided to the decoder, the total information rate rapidly saturated, with 79% of the maximal value obtained from a local cluster of just four neurons of different functional types. The decoding filter applied to a given neuron's spikes within such a multiunit decoder differed substantially from the filter applied to that same neuron in a single-unit decoder. This shows that the optimal interpretation of a ganglion cell's action potential depends strongly on the simultaneous activity of other nearby cells. The quality of the stimulus reconstruction varied greatly with frequency: flicker components below 1 Hz and above 10 Hz were reconstructed poorly, and the performance was optimal near 2.5 Hz. Further analysis suggests that temporal encoding by ganglion cell spike trains is limited by slow phototransduction in the cone photoreceptors and a corrupting noise source proximal to the cones.
The storage and querying of 3D objects for the dynamic composition of VRML worlds

The composition of 3D presentations is a complicated procedure partly facilitated by the introduction of VRML. VRML does not yet support 3D object storage and querying, thus introducing limitations to object reusability. Presentations have to be built from scratch while the necessary information already exists from previous work. This paper presents a method to address this issue by providing the functionality for (re)composing 3D interactive presentations. The participating objects are selected through spatiotemporal criteria. The temporal element is included so as to provide a global treatment to virtual (3D space+time) objects. The objects retrieved this way form a repository, and are further transformed in order to satisfy the requirements of the composed presentation. The entire framework complies with the VRML standard.
Predicting response in mobile advertising with hierarchical importance-aware factorization machine

Mobile advertising has recently seen dramatic growth, fueled by the global proliferation of mobile phones and devices. The task of predicting ad response is thus crucial for maximizing business revenue. However, ad response data change dynamically over time, and are subject to cold-start situations in which limited history hinders reliable prediction. There is also a need for a robust regression estimation for high prediction accuracy, and good ranking to distinguish the impacts of different ads. To this end, we develop a Hierarchical Importance-aware Factorization Machine (HIFM), which provides an effective generic latent factor framework that incorporates importance weights and hierarchical learning. Comprehensive empirical studies on a real-world mobile advertising dataset show that HIFM outperforms the contemporary temporal latent factor models. The results also demonstrate the efficacy of the HIFM's importance-aware and hierarchical learning in improving the overall prediction and prediction in cold-start scenarios, respectively.
Integrating Biosystem Models Using Waveform Relaxation

Modelling in systems biology often involves the integration of component models into larger composite models. How to do this systematically and efficiently is a significant challenge: coupling of components can be unidirectional or bidirectional, and of variable strengths. We adapt the waveform relaxation (WR) method for parallel computation of ODEs as a general methodology for computing systems of linked submodels. Four test cases are presented: (i) a cascade of unidirectionally and bidirectionally coupled harmonic oscillators, (ii) deterministic and stochastic simulations of calcium oscillations, (iii) single cell calcium oscillations showing complex behaviour such as periodic and chaotic bursting, and (iv) a multicellular calcium model for a cell plate of hepatocytes. We conclude that WR provides a flexible means to deal with multitime-scale computation and model heterogeneity. Global solutions over time can be captured independently of the solution techniques for the individual components, which may be distributed in different computing environments.
Determination of Surgical Strategies for Burn-Induced Conjunctivalized Corneas Using Optical Coherence Tomography

Purpose: To evaluate the clinical use of optical coherence tomography (OCT) in optimizing surgical treatment strategies for conjunctivalized corneas secondary to ocular burns. Methods: This noncomparative observational study included 25 patients with stable ocular burns and conjunctivalized corneas. OCT was performed on each eye. The thickness of corneal opacity or pseudopterygium and the underlying healthy stroma were measured. Individual surgical strategies were performed based on clinical examination and OCT images. Results: Three types of conjunctivalized corneas were evaluated, including conjunctival pannus (4 of 25), pseudopterygium (10 of 25), and a white fibrovascular membrane (11 of 25). All 25 patients received a procedure of allograft limbal stem cell transplantation. In addition, with information provided in OCT images, 8 patients had combined lamellar keratoplasties; 3 patients had deep anterior lamellar keratoplasties, and 2 patients received penetrating keratoplasties. The remaining 12 patients received limbal stem cell transplantation alone. All fibrovascular tissues were successfully removed from the cornea in all patients. Conclusions: OCT is a valuable method in the evaluation of conjunctivalized corneas. This is helpful in determining the surgical treatments for individual patients, allowing for less corneal graft rejection and making good use of corneal donors.
Anti-Inflammatory Lactobacillus rhamnosus CNCM I-3690 Strain Protects against Oxidative Stress and Increases Lifespan in Caenorhabditis elegans

Numerous studies have shown that resistance to oxidative stress is crucial to stay healthy and to reduce the adverse effects of aging. Accordingly, nutritional interventions using antioxidant food-grade compounds or food products are currently an interesting option to help improve health and quality of life in the elderly. Live lactic acid bacteria (LAB) administered in food, such as probiotics, may be good antioxidant candidates. Nevertheless, information about LAB-induced oxidative stress protection is scarce. To identify and characterize new potential antioxidant probiotic strains, we have developed a new functional screening method using the nematode Caenorhabditis elegans as host. C. elegans were fed on different LAB strains (78 in total) and nematode viability was assessed after oxidative stress (3 mM and 5 mM H2O2). One strain, identified as Lactobacillus rhamnosus CNCM I-3690, protected worms by increasing their viability by 30% and, also, increased average worm lifespan by 20%. Moreover, transcriptomic analysis of C. elegans fed with this strain showed that increased lifespan is correlated with differential expression of the DAF-16/insulin-like pathway, which is highly conserved in humans. This strain also had a clear anti-inflammatory profile when co-cultured with HT-29 cells, stimulated by pro-inflammatory cytokines, and co-culture systems with HT-29 cells and DC in the presence of LPS. Finally, this Lactobacillus strain reduced inflammation in a murine model of colitis. This work suggests that C. elegans is a fast, predictive and convenient screening tool to identify new potential antioxidant probiotic strains for subsequent use in humans.
Virtual sensors: using data mining techniques to efficiently estimate remote sensing spectra

Various instruments are used to create images of the earth and other objects in the universe in a diverse set of wavelength bands with the aim of understanding natural phenomena. Sometimes these instruments are built in a phased approach, with additional measurement capabilities added in later phases. In other cases, technology may mature to the point that the instrument offers new measurement capabilities that were not planned in the original design of the instrument. In still other cases, high-resolution spectral measurements may be too costly to perform on a large sample, and therefore, lower resolution spectral instruments are used to take the majority of measurements. Many applied science questions that are relevant to the earth science remote sensing community require analysis of enormous amounts of data that were generated by instruments with disparate measurement capabilities. This work addresses this problem using virtual sensors: a method that uses models trained on spectrally rich (high spectral resolution) data to "fill in" unmeasured spectral channels in spectrally poor (low spectral resolution) data. The models we use Are multilayer perceptrons, support vector machines (SVMs) with radial basis function kernels, and SVMs with mixture density Mercer kernels. We demonstrate this method by using models trained on the high spectral resolution Terra Moderate Resolution Imaging Spectrometer (MODIS) instrument to estimate what the equivalent of the MODIS 1.6-/spl mu/m channel would be for the National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (AVHRR/2) instrument. The scientific motivation for the simulation of the 1.6-/spl mu/m channel is to improve the ability of the AVHRR/2 sensor to detect clouds over snow and ice.
PR EP RI NT Interactive Abstractive Summarization for Event News Tweets

We present a novel interactive summarization system that is based on abstractive summarization, derived from a recent consolidated knowledge representation for multiple texts. We incorporate a couple of interaction mechanisms, providing a bullet-style summary while allowing to attain the most important information first and interactively drill down to more specific details. A usability study of our implementation, for event news tweets, suggests the utility of our approach for text exploration.
Cooperative Localization and Tracking of Mobile Ad Hoc Networks

Cooperative localization and tracking technique relies on pairwise measurements to jointly estimate the positions and the velocities of multiple nodes in a mobile ad hoc network. The pairwise measurements include the range and the radial velocity between the transmitting and receiving nodes. For a large-scale network, we formulate the state-space models for the subsystems and develop the distributed extended Kalman filters for cooperative localization and tracking. The decentralized approach takes into account the limited resources of node memory, embedded computation, and communication bandwidth. The algorithm works well in a sparsely connected mobile network and can adapt to changes in network connectivity. Numerical results show that the performances of the decentralized cooperative localization and node velocity estimation are close to the posterior Cramér-Rao lower bounds of the centralized approach.
GPSS World: A brief preview

GPSS (general purpose simulation system) World is a complete redesign and reimplementation of the popular GPSS/PC simulation environment. The limitations of the old PC DOS environment and the emerging trends in desktop computing have combined to motivate drastic changes which are planned for the new environment to be made available, beginning in 1992. The inclusion of windowing, virtual memory, animation and hierarchical modeling is discussed. <<ETX>>
Micro-mechanics modelling of smart materials

Metal Matrix ceramic-reinforced composites are rapidly becoming strong candidates as structural materials for many high temperature and engineering applications. Metal matrix composites (MMC) combine the ductile properties of the matrix with a brittle phase of the reinforcement, leading to high stiffness and strength with a reduction in structural weight. The main objective of using a metal matrix composite system is to increase service temperature or improve specific mechanical properties of structural components by replacing existing super alloys.The purpose of the study is to investigate, develop and implement second phase reinforcement alloy strengthening empirical model with SiCp reinforced A359 aluminium alloy composites on the particle-matrix interface and the overall mechanical properties of the material.To predict the interfacial fracture strength of aluminium, in the presence of silicon segregation, an empirical model has been modified. This model considers the interfacial energy caused by segregation of impurities at the interface and uses Griffith crack type arguments to predict the formation energies of impurities at the interface. Based on this, model simulations were conducted at nano scale specifically at the interface and the interfacial strengthening behaviour of reinforced aluminium alloy system was expressed in terms of elastic modulus.The numerical model shows success in making prediction possible of trends in relation to segregation and interfacial fracture strength behaviour in SiC particle-reinforced aluminium matrix composites. The simulation models using various micro scale modelling techniques to the aluminum alloy matrix composite, strengthenedwith varying amounts of silicon carbide particulate were done to predict the material state at critical points with properties of Al-SiC which had been heat treated.In this study an algorithm is developed to model a hard ceramic particle in a soft matrix with a clear distinct interface and a strain based relationship has been proposed for the strengthening behaviour of the MMC at the interface rather than stress based, by successfully completing the numerical modelling of particulate reinforced metal matrix composites.
3,4-Dihydroxybenzaldehyde 4-phenylthiosemicarbazone

Molecules of the title compound, C14H13N3O2S, are linked by intermolecular O—H⋯O hydrogen bonds into centrosymmetric dimers forming R 2 2(4) rings which are further linked by O—H⋯S hydrogen bonds and weaker N—H⋯S and N—H⋯O hydrogen bonds to form a three-dimensional network.
Clinical Efficacy of EH 0202 , a Kampo Formula , on the Health of Middle-Aged Women

To investigate the clinical effects of EH0202, a Japanese herbal supplement, on the menopausal symptoms and physical status of periand post-menopausal women. Thirty-two post-menopausal women (53.0 ± 5.1 years) presented with menopausal complaints were enrolled in the clinical study. Patients were administered an herbal supplement, EH0202 (6 g/day for 6 months), and were assessed for improvement of their overall symptoms using the Greene Climacteric Scale and the Visual Analog Scale (VAS). Blood pressure, skin surface blood flow and plasma lipid profiles were measured before and 1, 3 and 6 months after EH0202 administration. There was a significant decrease in the climacteric scale score (P < 0.001) and VAS (P < 0.0001) after 6 months of EH0202 treatment. There was a significant decrease in systolic (P < 0.001) and diastolic (P < 0.05) blood pressure, and a significant decrease in facial skin surface blood flow (P < 0.05) after 3 months of EH0202 administration. We observed a significant decrease in plasma TG and LDL-cholesterol concentrations after 3 months of EH0202 administration (P < 0.05). EH0202 (MACH) reduced blood pressure, excess facial Correspondence to: Dr. Takahisa Ushiroyama, Department of Obstetrics and Gynecology, Osaka Medical College, 2-7 Daigaku-machi, Takatsuki, Osaka 569-8686, Japan. Tel: (+81) 72-683-1221, Fax: (+81) 72-681-3723, E-mail: gyn003@poh.osaka-med.ac. jp 00231.p65 09/23/2004, 5:16 PM 755 756 T. USHIROYAMA et al. skin blood flow (flushing) and abnormal lipid levels, as well as clinically improved menopausal symptoms in post-menopausal women. In post-menopausal women, this product appears to help maintain normal biological function and improves quality of life.
Does subclinical inflammation contribute to impairment of function of knee joints in aged individuals? High prevalence of ultrasound inflammatory findings.

OBJECTIVES To investigate the prevalence of knee US findings of inflammation and structural damage in aged individuals (≥60 years) of a long-term population-based cohort and to correlate these findings with demographic, clinical and laboratory parameters. METHODS Cross-sectional clinical and US investigation of both knee joints during the 2010 follow-up of the prospective population-based Bruneck Study. Demographic variables, physical activity, comorbidities, medications, pain, and functional scales related to the knee joints were recorded. US-assessed parameters were synovial hypertrophy, power Doppler signal, joint effusion, cartilage abnormalities, osteophytes, enthesopathy and bursitis. Statistics included univariate and multivariate regression analysis. RESULTS A total of 488 subjects (mean age 72.5 years; 53.5% females, 46.5% males) were examined by clinical assessment, and 433 of these underwent US examination of both knees. Both inflammatory and structural abnormalities were found in 296 (68.8%) subjects. Inflammatory abnormalities were significantly associated with age in years, male gender, diabetes and the presence of knee joint symptoms. In the multivariate analysis, age, male gender and knee swelling emerged as independent predictors of inflammation [odds ratio (OR) (95% CI) = 1.06 (1.03, 1.09), 2.55 (1.55, 4.21) and 5.92 (1.99, 17.58), respectively]. CONCLUSION The present study showed a high prevalence of US inflammatory abnormalities in the knee joints of a normal aged population. These data suggest a substantial contribution of inflammation in progressive impairment of joint function with age.