Miracle-dz/UniFAR-FTUs huggingface dataset:
Trajectory of Sewerage System Development Optimization

The transition to market relations has determined a new technology for our country to manage the development of urban engineering systems. This technology has shifted to the municipal level and it can, in large, be presented in two stages. The first is the development of a scheme for the development of the water supply and sanitation system, the second is the implementation of this scheme on the basis of investment programs of utilities. In the investment programs, financial support is provided for the development and reconstruction of water disposal systems due to the investment component in the tariff, connection fees for newly commissioned capital construction projects and targeted financing for selected state and municipal programs, loans and credits. Financial provision with the development of sewerage systems becomes limited and the problem arises in their rational distribution between the construction of new water disposal facilities and the reconstruction of existing ones. The paper suggests a methodology for developing options for the development of sewerage systems, selecting the best of them by the life cycle cost criterion, taking into account the limited investments in their construction, models and methods of analysis, optimizing their reconstruction and development, taking into account reliability and seismic resistance.
A Recommendation Model for Social Resource Sharing Systems Based on Tripartite Graph Clustering

The use of folksonomies to recommend web pages and tags assigned to these pages, is an important research direction in web recommendation. In this study, we implement a model that fits tripartite structure of folksonomies and extracts valuable information for generating recommendations. Then we developed two types of recommendation systems that take advantage of this information, web page recommendation and tag recommendation. We compared our recommendation results with the results using bipartite clustering of web pages and tags. The experiments are conducted on the data set obtained from Delicious web site. The results show that this model generates better accuracy results for web page recommendation while extracting more useful information simultaneously which could be an extra to generate different types of recommendations.
Colour and furniture brand identity: Exploring the strategic value of brand’s iconic colour

This research explores the intersection of colour marketing and brand identity, focusing on the role of iconic colour in furniture branding. A comprehensive framework for crafting a furniture brand’s iconic colour was developed, and structural equation modeling was used to analyze data from three offline experiments with a total sample size of 111 subjects. The findings highlight the crucial influence of iconic colour on brand identity, revealing that both the referential meaning of hue and gender significantly impact brand perception. Contrary to conventional beliefs, variations in saturation and value are not solely detrimental; they can also enrich brand identity. The iconic colour serves as a cornerstone for ensuring consistency across internal and external brand dimensions, solidifying the brand’s core identifiers, and resonating with consumers’ minds. This research underscores the pivotal role of iconic colour in forging a coherent and distinct brand identity, offering valuable insights for marketers and brand strategists in the furniture industry and beyond.
Automatic Acquisition of Phrase Grammars for Stochastic Language Modeling

Phrase(cid:0)based language models have been recognized to have an advantage over word(cid:0)based language models since they allow us to capture long span(cid:0) ning dependencies(cid:1) Class based language models have been used to improve model generalization and overcome problems with data sparseness(cid:1) In this pa(cid:0) per(cid:2) we present a novel approach for combining the phrase acquisition with class construction process to automatically acquire phrase(cid:0)grammar fragments from a given corpus(cid:1) The phrase(cid:0)grammar learning is decomposed into two sub(cid:0)problems(cid:2) namely the phrase acquisition and feature selection(cid:1) The phrase acquisition is based on entropy minimizationand the feature selection is driven by the entropy reduction principle(cid:1) We further demonstrate that the phrase(cid:0) grammarbased n(cid:0)gram language model signi(cid:3)cantly outperforms a phrase(cid:0)based n(cid:0)gram language model in an end(cid:0)to(cid:0)end evaluation of a spoken language application(cid:1) (cid:0)
Mineral Acquisition Rates in Developing Enamel on Maxillary and Mandibular Incisors of Rats and Mice: Implications to Extracellular Acid Loading as Apatite Crystals Mature

The formation rates of mineral in developing enamel were determined by microweighing of incisors of mice and rats. Computations indicated that a large excess of hydrogen ions would result from creating apatite at the calculated rates. Enamel organ cells (ameloblasts), therefore, likely excrete bicarbonate ions to prevent pH in fluid bathing enamel from becoming too acidic.
The new form of electrothermal model of MA7805 positive voltage regulator

This paper presents the problem of modelling the linear 3-terminal positive-voltage regulator MA7805 (IC) with selfheating taken into account. In the construction of the ElectroThermal Macromodel (ETM) the modified electrical SPICE-library model of the considered device has been used. This macromodel has been implemented to SPICE with the use of the ABM option. The proposed macromodel was verified experimentally and a good agreement between the calculation and measurement results was obtained.
ISOP-Yield: Yield-Aware Stack-Up Optimization for Advanced Package using Machine Learning

High-speed cross-chip interconnects and packaging are critical for the overall performance of modern heterogeneous integrated computing systems. Recent studies have developed automatic stack-up design optimization methods for high-density interconnect (HDI) printed circuit board (PCB). However, few have considered the impact of manufacturing variation and the resulting yield issue in high-volume manufacturing (HVM). In this paper, we propose a novel framework for automatic stack-up design, optimizing the interconnect performance with a given yield requirement. The proposed framework utilizes the smooth and gradient-available machine learning surrogate model, employing a first-order Taylor expansion to approximate the output performance distribution. Experimental results demonstrate that our method effectively boosts the yield rate compared to the existing stack-up optimization framework. In addition, the proposed yield-aware algorithm shows an average of 49.96% efficiency improvement in yield-aware figure of merits compared to the state-of-the-art input noise-aware Bayesian optimization algorithm for high yield targets.
Lake phytoplankton composition and biomass along horizontal and vertical gradients

Phytoplankton biomass and compositton within a lake may be highly variable spatially, both vertically and horizontally (BOWERS 1980, SCHELSKE & STOERMER 1971, HALL et al. 2003). For example, phytoplankton communities in lake embayments are often markedly different from those in the main lake basin (GRAY 1987). Embayments may be affected differently by inflows and outflows and have different transport rates and nutrient levels, resulting in susceptibility to algal blooms (TADA et al. 2001). Responses of phytoplankton in the middle o f large lakes may not accurately reflect these embayments. Algal biomass is often estimated from one mid-lake station, and intra-lake variation is over-looked (FEE 1976, STAUFFER 1988) resulting in consequential errors in lake-wide phytoplankton biomass estimates. In this study spatial variations in phytoplankton biomass were examined in a large New Zealand lake in the central lake and in several embayments. Vertical gradients in phytoplankton biomass exist in the lake during summer with the development of a deep chlorophyll maximum (DCM). Our objectives were to quantifY spatial and temporal variations in phytoplankton biomass between embayments and the main lake, demonstrate the effects on the underwater light climate, and resolve whether a mid-lake station i s adequate for determining surface and DCM levels through-out the lake.
Fitting In but Getting Fat

In two experiments, we tested the hypothesis that pressure felt by U.S. immigrant groups to prove they belong in America causes them to consume more prototypically American, and consequently less healthy, foods. Asian Americans were three times more likely to report a prototypically American food as their favorite after being asked whether they spoke English than when they had not been asked; in contrast, questioning the English abilities of White Americans had no effect on their reports (Experiment 1). Also, Asian Americans ordered and ate dishes that were more American and contained an average of 182 additional calories and 12 extra grams of fat when their American identity was directly challenged than when their American identity was not challenged (Experiment 2). Identity-based psychological processes may help explain why the diets of U.S. immigrant groups tend to decline in nutritional value with longer residence in the United States and over generations.
Capacity Region of Finite State Multiple-Access Channels With Delayed State Information at the Transmitters

A single-letter characterization is provided for the capacity region of finite-state multiple access channels. The channel state is a Markov process, the transmitters have access to delayed state information, and channel state information is available at the receiver. The delays of the channel state information are assumed to be asymmetric at the transmitters. We apply the result to obtain the capacity region for a finite-state Gaussian MAC, and for a finite-state multiple-access fading channel. We derive power control strategies that maximize the capacity region for these channels.
Direct proof that the primary site of action of cytochalasin on cell motility processes is actin

We have previously described the isolation of a mutant KB cell (Cyt 1 mutant) resistant to the cytotoxic effect of cytochalasin B (CB). The Cyt 1 mutant carries an altered form of beta-actin (beta'-actin) and lacks normal beta-actin (Toyama, S., and S. Toyama. 1984. Cell. 37:609- 614). Increased resistance of the Cyt 1 mutant to CB in vivo is reflected in altered properties of beta'-actin in vitro (Toyama, S., and S. Toyama. 1988. J. Cell Biol. 107:1499-1504). Here, we show that the mutation in beta-actin is solely responsible for the cytochalasin- resistant phenotype of the Cyt mutant. We have isolated a cDNA clone encoding beta'-actin from Cyt 1 cells. Sequence analysis reveals two mutations in the coding region that substitute two amino acid residues (Val139----Met and Ala295----Asp). Expression of the beta'-actin cDNA confers cytochalasin resistance upon transformed cytochalasin-sensitive KB cells. Levels of resistance to CB in the transformed cell clones correlate well with amounts of beta'-actin polypeptide. Both of the two mutations in beta'-actin are necessary for the high level expression of cytochalasin resistance. Overall, we conclude that the primary site of action of cytochalasin on cell motility processes in vivo is actin.
Minimum Latency Submodular Cover

We study the Minimum Latency Submodular Cover (MLSC) problem, which consists of a metric (V, d) with source r ∈ V and m monotone submodular functions f1, f2, …, fm: 2V → [0, 1]. The goal is to find a path originating at r that minimizes the total “cover time” of all functions. This generalizes well-studied problems, such as Submodular Ranking [Azar and Gamzu 2011] and the Group Steiner Tree [Garg et al. 2000]. We give a polynomial time O(log 1/ε ċ log2+δ|V|)-approximation algorithm for MLSC, where ε > 0 is the smallest non-zero marginal increase of any {fi}mi = 1 and δ > 0 is any constant. We also consider the Latency Covering Steiner Tree (LCST) problem, which is the special case of MLSC where the fis are multi-coverage functions. This is a common generalization of the Latency Group Steiner Tree [Gupta et al. 2010; Chakrabarty and Swamy 2011] and Generalized Min-sum Set Cover [Azar et al. 2009; Bansal et al. 2010] problems. We obtain an O(log 2|V|)-approximation algorithm for LCST. Finally, we study a natural stochastic extension of the Submodular Ranking problem and obtain an adaptive algorithm with an O(log 1/ε)-approximation ratio, which is best possible. This result also generalizes some previously studied stochastic optimization problems, such as Stochastic Set Cover [Goemans and Vondrák 2006] and Shared Filter Evaluation [Munagala et al. 2007; Liu et al. 2008].
An Intuitionistic Logic that Proves Markov's Principle

We design an intuitionistic predicate logic that supports a limited amount of classical reasoning, just enough to prove a variant of Markov's principle suited for predicate logic. At the computational level, the extraction of an existential witness out of a proof of its double negation is done by using a form of statically-bound exception mechanism, what can be seen as a direct-style variant of Friedman's A-translation.
Study on Buyback Contract in Supply Chain With a Loss-Averse Supplier and Multiple Loss-Averse Retailers Under Stockout Loss Situation

According to the prospect theory and the loss-aversion function, this paper developers the buyback contract model in a two-stage supply chain with a loss-averse supplier and multiple loss-averse retailers. Under the stockout loss setting, we analyze the effect of the loss aversion on the behavior from the retailers and the supplier, and then the buyback contract has been shown to be able to coordinate the supply chain. Furthermore, the number of retailers and loss aversion coefficient meet a certain range, there will be a unique optimal buyback price to achieve supply chain coordination.
A 220-kD undercoat-constitutive protein: its specific localization at cadherin-based cell-cell adhesion sites

Recently we developed an isolation procedure for the cell-to-cell adherens junctions (AJ; cadherin-based junctions) from rat liver (Tsukita, Sh. and Sa. Tsukita. 1989. J. Cell Biol. 108:31-41). In this study, using the isolated AJ, we have obtained two mAbs specific to the 220-kD undercoat-constitutive protein. Immunofluorescence and immunoelectron microscopy with these mAbs showed that this 220-kD protein was highly concentrated at the undercoat of cell-to-cell AJ in various types of tissues and that this protein was located in the immediate vicinity of the plasma membrane in the undercoat of AJ. In the cells lacking typical cell-to-cell AJ, such as fibroblasts, the 220- kD protein was immunofluorescently shown to be coconcentrated with cadherin molecules at cell-cell adhesion sites. These localization analyses appeared to indicate the possible direct or indirect association of the 220-kD protein with cadherin molecules. Furthermore, it was revealed that the 220-kD protein and alpha-spectrin were coimmunoprecipitated with the above mAbs in both the isolated AJ and the brain. The affinity-purified 220-kD protein molecule looked like a spherical particle, and its binding site on the spectrin molecule was shown to be in the position approximately 10-20 nm from the midpoint of spectrin tetramer by low-angle rotary-shadowing electron microscopy. Taking all these results together with biochemical and immunological comparisons, we are persuaded to speculate that the 220-kD protein is a novel member of the ankyrin family. However, the possibility cannot be excluded that the 220-kD protein is an isoform of beta-spectrin. The possible roles of this 220-kD protein in the association of cadherin molecules with the spectrin-based membrane skeletons at the cadherin- based cell-cell adhesion sites are discussed.
Designing force reflecting teleoperators with large time delays to appear as virtual tools

We examine the behavior of force reflecting teleoperators which are subjected to large time delays up to several seconds. While stability is guaranteed by the use of passive transmission procedures, such systems can demonstrate particular dynamics which interfere with normal operation. Using the notion of wave variables for the analysis and implementation, and making appropriate design choices, we can construct a telerobot system with consistent and predictable behavior. This follows the design goal of a virtual tool accounting for the implicit limitations imposed by the delay.
Global Network Alignment

Finding the common ancestries of different proteins across species is an important task. Homologs is the basic definition which denotes two genes that have descended from some common ancestral. For a more focused notation, we define Paralogs if the last evolutionary event separating the genes was duplication, and similarly we define Orthologs if the last evolutionary event separating the genes was speciation. Understating the hierarchy of given genes is an important task. The most basic implementations of such knowledge can be understanding the evolutionary principles of the specific subject. Moreover, predicting/annotating the protein functions or interactions can be done with this information. Most of the methods of dealing with this problem are sequence-based models, thus sequence of proteins from different species was compared, in order to find a group of proteins that have the same homologs. Two such methods are COG (Clusters of Orthologous Groups) (Tatusov et al. [8]) and Inparanoid ([5]). The COG approach defines orthologs using sets of proteins that contain reciprocal best BLAST matches across a minimum of three species. The Inparanoid approach is a sequence-based method of finding functional annotation. It uses clustering in order to derive orthology families, leaving some of the orthology relations ambiguous. For more information see [5].
Multiple time scale analysis of CO₂ exchange between the Harvard Forest and the atmosphere

CO2 fluxes between the biosphere and the atmosphere are strongly related to plant photosynthesis and respiration. Northern hemisphere forests invoke a strong seasonality in these fluxes as photosynthesis drives summertime uptake of carbon from the atmosphere and respiration drives wintertime release. The objectives of this research were 1) to examine how CO2 fluxes vary with different climate variables, 2) to compare responses of CO2 fluxes at daily, seasonal and year-to-year time scales and 3) to study the scaling of variability in forcing and response of the carbon system, using data from the Harvard Forest in Massachusetts. The data for this research was collected at a Long Term Ecological Research (LTER) site, and includes time-series measurements of Net Ecosystem Exchange (NEE) or CO2 fluxes, Photosynthetically Available Radiation (PAR), air temperature (Tair), soil temperature (Tsoil), vapor pressure deficit (vpd) and precipitation (ppt). A correlation of the original time series was first performed to understand the interrelationships between the climate variables and NEE. The correlations showed that all the climate variables were negatively correlated to NEE, except ppt, which was positively correlated. The data were also analyzed using wavelet decomposition analysis, a relatively new method for processing signals. Wavelet decomposition was used in this research to distinguish signals at the highest (daily cycle) and lowest frequencies (seasonal cycle). The wavelet decomposition analysis showed that all but precipitation affect the NEE within both the daily and seasonal cycles. More research is needed to separate and quantify the effect of each forcing on the CO2 fluxes, and ultimately to better understand the role that each plays in sequestering carbon from the atmosphere. This work was done under the auspices of the Significant Opportunities in Atmospheric Research and Science (SOARS®) Program of the University Corporation for Atmospheric Research, with funding from the National Science Foundation, the U.S. Department of Energy, the National Oceanic and Atmospheric Administration, and the Goddard Space Flight Center, NASA. SOARS® 2002, Atzel Drevon, 1
Dynamic Optimization Method of Distributed Harmonic Compensation Based on Active Device Margin Calculation Model of APF

With rapid development of power electronics industry, a number of nonlinear devices are connected to the power grid, and the grid voltage suffers from severe harmonic pollution. For the treatment of harmonic voltage, the equipment adopted is Active Power Filter(APF), which can detect the harmonics at the installation point. However, the harmonic sources at each node will vary with time, requiring the injection of new harmonic compensation commands, while also considering the surplus of APF active devices to ensure efficient and stable operation of APF. This paper aims to propose a dynamic adjustment method of distributed harmonic compensation based on the calculation model of active device margin of APF. Firstly, the APF active device loss and injection temperature model is established under different harmonic combinations to calculate in real time whether the harmonic injection command meets the active device margin. Moreover, for the power grid with the harmonic source changes, the particle swarm optimization algorithm is used to obtain new harmonic injection commands, which on one hand reduces the total voltage harmonic distortion rate of the power grid, and on the other hand meets the active device margin to ensure stable operation of APF.
Performance of ML Range Estimator in Radio Interferometric Positioning Systems

The radio interferometric positioning system (RIPS) is a novel positioning solution used in wireless sensor networks. This letter explores the ranging accuracy of RIPS in two configurations. In the linear step-frequency configuration, we derive the mean squared error (MSE) of the maximum likelihood (ML) estimator. In the random step-frequency configuration, we introduce average MSE to characterize the performance of the ML estimator. The simulation results fit well with theoretical analysis.
Intrinsic and Atmospherically Forced Variability of the AMOC: Insights from a Large-Ensemble Ocean Hindcast

AbstractThis study investigates the origin and features of interannual-to-decadal AMOC variability from several ocean simulations, including a large (50-member) ensemble of global, eddy-permitting (1/4°) ocean/sea-ice hindcasts. After an initial stochastic perturbation, each member is driven by the same realistic atmospheric forcing over 1960-2015. The magnitude, spatio-temporal scales and patterns of both the atmospherically-forced and intrinsic/chaotic interannual AMOC variability are then characterised from the ensemble mean and ensemble spread, respectively. The analysis of the ensemble-mean variability shows that the AMOC fluctuations north of 40°N are largely driven by the atmospheric variability, which forces meridionally-coherent fluctuations reaching decadal time-scales. The amplitude of the intrinsic interannual AMOC variability never exceeds the atmospherically-forced contribution in the Atlantic basin, but it reaches up to 100% of the latter around 35°S, and 60% in the northern mid-latitudes.