Miracle-dz/UniFAR-FTUs huggingface dataset:
Analyzing and testing the structure of China’s imports for cotton

China is the biggest importer of cotton in the world, and it is of great interest to analyze its import demand system for cotton. Noteworthy is that cotton is deemed an intermediate commodity for textile production instead of a direct consumption one, hence this thesis adopts a two-stage cost minimization procedure resembling the Armington Model to study China’s demand for cotton differentiated by their countries of production with a focus on the substitution effects and weak separability between various sources. The CDE functional form is utilized for the cost function to generalize the Armington settings. Unlike former works, this thesis estimates the demand system with the Bayesian Bootstrap Multivariate Regression, and report the posterior distributions of coefficients and Allen elasticities of substitution. The results demonstrate that the CDE functional form may still be too demanding to be completely consistent with the data. Three weak separable structures are tested, and it can be concluded that the assumption of different separable structures improves the consistency between the model and data to various extents. The U.S. cotton is the least sensitive to its own price changes while the cotton from Egypt and Sudan is the most sensitive. The overall substitution effects between various cotton import sources appear to be relatively small.
Decentralized Probabilistic World Modeling with Cooperative Sensing

Drawing on the projected increase in computing power, solid-state storage and network communication capacity to be available on personal mobile devices, we propose to build and maintain without prior knowledge a fully distributed decentralized large-scale model of the physical world around us using probabilistic methods. We envisage that, by using the multimodal sensing capabilities of modern personal devices, such a probabilistic world model can be constructed as a collaborative effort of a community of participants, where the model data is redundantly stored on individual devices and updated and refined through short-range wireless peer-to-peer communication. Every device holds model data describing its current surroundings, and obtains model data from others when moving into unknown territory. The model represents common spatio-temporal patterns as observed by multiple participants, so that rogue participants can not easily insert false data and only patterns of general applicability dominate. This paper aims to describe - at a conceptual level - an approach for building such a distributed world model. As one possible world modeling approach, it discusses compositional hierarchies, to fuse the data from multiple sensors available on mobile devices in a bottom-up way. Furthermore, it focuses on the intertwining between building a decentralized cooperative world model and the opportunistic communication between participants.
Staphylococcal Enterotoxin H Induced Apoptosis of Bovine Mammary Epithelial Cells in Vitro

Staphylococcal enterotoxins (SEs) are powerful superantigenic toxins produced by Staphylococcus aureus (S. aureus). They can cause food poisoning and toxic shock. However, their impact on bovine mammary epithelial cells (bMECs) is still unknown. In this study, the distribution of SE genes was evaluated in 116 S. aureus isolates from bovine mastitis, and the most prevalent genes were seh (36.2%), followed by sei (12.1%), seg (11.2%), ser (4.3%), sec (3.4%), sea (2.6%) and sed (1.7%). To better understand the effect of staphylococcal enterotoxin H (SEH) on bMECs, the seh gene was cloned and inserted into the prokaryotic expression vector, pET28a, and transformed into Escherichia coli BL21 (DE3). The recombinant staphylococcal enterotoxin H (rSEH) was expressed and purified as soluble protein. Bioactivity analysis showed that rSEH possessed the activity of stimulating lymphocytes proliferation. The XTT assay showed that 100 μg/mL of rSEH produced the cytotoxic effect on bMECs, and fluorescence microscopy and flow cytometry analysis revealed that a certain dose of rSEH is effective at inducing bMECs apoptosis in vitro. This indicates that SEs can directly lead to cellular apoptosis of bMECs in bovine mastitis associated with S. aureus.
Reform Theory into Practice: A Case Study Examination of West Virginia's Efforts To Promote Inclusive Schooling through Site-Based Partnership Decision-Making Practices.

A study examined the extent to which faculty senate involvement in strategic planning for inclusion influenced the implementation of inclusive practices in schools. Case studies in four West Virginia middle schools included examination of school strategic plans, observation, and teacher surveys and interviews. Analysis of findings across cases revealed some common themes: (1) actual changes in the structural model of schooling were related to how the larger system initially redefined teachers' positions within the school, not to faculty senate engagement in planning; (2) three schools restructured their service delivery model by redefining the special education teacher's role; (3) schools' unique characteristics affected how change was internalized; (4) faculty senates' inclusion plans gave limited attention to teachers' classroom practices; (5) special education enrollment and percentage did not impact the school's level of inclusion; (6) staffing patterns greatly impacted teacher collaboration levels and the extent of special education teachers' influence on regular classroom practices; and (7) a school's level of inclusion was related to the types of decisions made by its faculty senate. (Contains 41 references.) (SV) Reproductions supplied by EDRS are the best that can be made from the original document. U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) <his document has been reproduced as received from the person or organization originating it. Minor changes have been made to improve reproduction quality. Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. "PERMISSION TO REPRODUCE THIS MATERIAL HAS BEEN GRANTED BY
Nonnegative linear reconstruction measure based face recognition system

Nonnegative linear reconstruction measure (NLRM) can produce the sparse nonnegative representation coefficients which concentrate on the similar training samples. The samples with the same class-label are generally more similar than that with different class-labels. Based on this, we develop a NLRM based classifier (NLRMC). Using the decision rule of NLRMC, we continue to design a feature extractor, called nonnegative linear reconstruction projection (NLRP), such that NLRMC can achieve the optimal performance in the NLRP transformed subspace. NLRP combines with NLRMC to form the recognition system, which performs better than NLRP with other classifiers. Experiments are done on the Yale and AR face databases, and results demonstrate the recognition system of NLRP + NLRMC is more effective than other combinations.
Impact of Strategic Ambidexterity on Organizational Success: Strategic Scenario as Moderating Variable

The primary objective of the present study is to provide the deeper insights into one of the emerging paradigm of strategic ambidexterity and to explore possible relationship between strategic ambidexterity and organizational success in recent competitive milieu. This study is conducted to probe the moderating impact of strategic scenario on the relationship of strategic ambidexterity and organizational success. The study is carried out by collecting data through structured questionnaire, the questionnaire was adapted from Gibson & Birkinshaw (2004), Wulf, Christian, and Meissner (2010) and Ilyas and Rafiq (2012). This study explains the strategic ambidexterity and its role for organizational success. Researcher have discussed the effectiveness of strategic ambidexterity for organizational success in the context of Iraq.
A Family of Discriminative Manifold Learning Algorithms and Their Application to Speech Recognition

This paper presents a family of discriminative manifold learning approaches to feature space dimensionality reduction in noise robust automatic speech recognition (ASR). The specific goal of these techniques is to preserve local manifold structure in feature space while at the same time maximizing the separability between classes of feature vectors. In the manifold space, the relationships among the feature vectors are defined using nonlinear kernels. Two separate distance measures are used to characterize the kernels, namely the conventional Euclidean distance and a cosine-correlation based distance. The performance of the proposed techniques is evaluated on two task domains involving noise corrupted utterances of connected digits and read newspaper text. Performance is compared to existing approaches used for feature space transformations, including linear discriminant analysis (LDA) and locality preserving linear projections (LPP). The proposed approaches are found to provide a significant reduction in word error rate (WER) with respect to the more well-known techniques for a variety of noise conditions. Another contribution of the paper is to quantify the interaction between acoustic noise conditions and the shape and size of local neighborhoods which are used in manifold learning to define local relationships among feature vectors. Based on this analysis, a procedure for reducing the impact of varying acoustic conditions on manifold learning is proposed .
Cryptochrome-Dependent and -Independent Circadian Entrainment Circuits in Drosophila

Entrainment to environmental light/dark (LD) cycles is a central function of circadian clocks. In Drosophila, entrainment is achieved by Cryptochrome (CRY) and input from the visual system. During activation by brief light pulses, CRY triggers the degradation of TIMELESS and subsequent shift in circadian phase. This is less important for LD entrainment, leading to questions regarding light input circuits and mechanisms from the visual system. Recent studies show that different subsets of brain pacemaker clock neurons, the morning (M) and evening (E) oscillators, have distinct functions in light entrainment. However, the role of CRY in M and E oscillators for entrainment to LD cycles is unknown. Here, we address this question by selectively expressing CRY in different subsets of clock neurons in a cry-null (cry0) mutant background. We were able to rescue the light entrainment deficits of cry0 mutants by expressing CRY in E oscillators but not in any other clock neurons. Par domain protein 1 molecular oscillations in the E, but not M, cells of cry0 mutants still responded to the LD phase delay. This residual light response was stemming from the visual system because it disappeared when all external photoreceptors were ablated genetically. We concluded that the E oscillators are the targets of light input via CRY and the visual system and are required for normal light entrainment.
Consumption of dairy products and the 15-year incidence of age-related macular degeneration

Habitual consumption of dairy products has been shown to play an important role in the prevention of several chronic diseases. We aimed to prospectively assess the relationship between the change in dairy product consumption (both regular fat and low/reduced fat) and the 15-year incidence of age-related macular degeneration (AMD). In the Blue Mountains Eye Study, 2037 participants aged 49 years or above at baseline were re-examined at follow-up in 1997–9, 2002–4 and/or 2007–9. AMD was assessed from retinal photographs. Dietary data were collected using a semi-quantitative FFQ, and servings of dairy product consumption calculated. Over the 15-year follow-up, there were 352, 268 and eighty-four incident cases of any, early and late AMD, respectively. After adjusting for age, sex, current smoking, white cell count and fish consumption, a significant linear trend (P for trend = 0·003) was observed with decreasing consumption of total dairy foods and the 15-year incidence of late AMD, comparing the lowest v. highest quintile of intake (OR 2·80, 95 % CI 1·21, 3·04). Over the 15 years, decreased consumption of reduced-fat dairy foods was associated with an increased risk of incident late AMD, comparing the lowest to highest quintile of intake (OR 3·10, 95 % CI 1·18, 8·14, P for trend = 0·04). Decreasing total dietary Ca intake over the 15 years was also associated with an increased risk of developing incident late AMD (multivariable-adjusted P for trend = 0·03). A lower consumption of dairy products (regular and low fat) and Ca was independently associated with a higher risk of developing incident late AMD in the long term. Additional cohort studies are needed to confirm these findings.
Secure communications using quantum cryptography

The secure distribution of the secret random bit sequences known as `key' material, is an essential precursor to their use for the encryption and decryption of confidential communications. Quantum cryptography is an emerging technology for secure key distribution with single-photon transmissions: Heisenburg's uncertainty principle ensures that an adversary can neither successfully tap the key transmissions, nor evade detection (eavesdropping raises the key error rate above a threshold value). We have developed experimental quantum cryptography systems based on the transmission of non-orthogonal single-photon states to generate shared key material over multi-kilometer optical fiber paths and over line-of-sight links. In both cases, key material is built up using the transmission of a single- photon per bit of an initial secret random sequence. A quantum-mechanically random subset of this sequence is identified, becoming the key material after a data reconciliation stage with the sender. In our optical fiber experiment we have performed quantum key distribution over 24-km of underground optical fiber using single-photon interference states, demonstrating that secure, real-time key generation over `open' multi-km node-to-node optical fiber communications links is possible.
Iterative Smoothing Technique for Improving the Stability of Recommender Systems

on the measure of recommendation stability, which reflects the consistency of recommender system predictions. Stability is a desired property of recommendation algorithms and has important implications on users' trust and acceptance of recommendations. Prior research has reported that some popular recommendation algorithms can suffer from a high degree of instability. In this study we propose a scalable, general-purpose iterative smoothing approach that can be used in conjunction with different traditional recommendation algorithms to improve their stability. Our experimental results on real-world rating data demonstrate that the proposed approach can achieve substantially higher stability as compared to the original recommendation algorithms. Importantly, the proposed approach not only does not sacrifice the predictive accuracy in order to improve recommendation stability, but is actually able to provide additional accuracy improvements at the same time.
Qualitative and Quantitative Evaluation of Six Algorithms for Correcting Intensity Nonuniformity Effects

The desire to correct intensity nonuniformity in magnetic resonance images has led to the proliferation of nonuniformity-correction (NUC) algorithms with different theoretical underpinnings. In order to provide end users with a rational basis for selecting a given algorithm for a specific neuroscientific application, we evaluated the performance of six NUC algorithms. We used simulated and real MRI data volumes, including six repeat scans of the same subject, in order to rank the accuracy, precision, and stability of the nonuniformity corrections. We also compared algorithms using data volumes from different subjects and different (1.5T and 3.0T) MRI scanners in order to relate differences in algorithmic performance to intersubject variability and/or differences in scanner performance. In phantom studies, the correlation of the extracted with the applied nonuniformity was highest in the transaxial (left-to-right) direction and lowest in the axial (top-to-bottom) direction. Two of the six algorithms demonstrated a high degree of stability, as measured by the iterative application of the algorithm to its corrected output. While none of the algorithms performed ideally under all circumstances, locally adaptive methods generally outperformed nonadaptive methods.
Performance Analysis of Sc-FDMA and OFDMA in LTE Frame Structure

Long Term Evolution (LTE) is consents pliable spectrum distribution which renders enriched wireless data services to users at lower latency and multi-megabit throughput. LTE uses Orthogonal Frequency Division Multiple Access (OFDMA) and Single Carrier Frequency Division Multiple Access (Sc-FDMA) for downlink and Uplink transmission where OFDMA has been acquired in LTE for downlink transmission which diminishes the terminal cost and power consumption and Sc-FDMA has been allocates multiple users to a shared communication resources. Frequency Division Duplex (FDD) and Time Division Duplex (TDD) are the prevailing duplexing scheme in LTE that provides deployable tractability according to spectrum assignation. In this paper, we analyze the performance of SC-FDMA and OFDMA in LTE Frame Structure based on Peak to Average Power Ratio (PAPR) analysis. ITU Pedestrian A channel and ITU Vehicular A channel and also Additive White Gaussian Noise (AWGN) channel are used for analyzing the error performance between SC-FDMA and OFDMA. General Terms LTE, SNR, minimum BER, AWGN, FDD, TDD
Learning to Like What You Have - Explaining the Endowment Effect

The endowment effect describes the fact that people demand much more to give up an object than they are willing to spend to acquire it. The existence of this effect has been documented in numerous experiments. We attempt to explain this effect by showing that evolution favors individuals whose preferences embody an endowment effect. The reason is that an endowment effect improves one's bargaining position in bilateral trades. We show that for a general class of evolutionary processes almost all individuals will have a strictly positive and finite endowment effect.
Algorithm for Efficient Multilevel Association Rule Mining

over the years, a variety of algorithms for finding frequent item sets in very large transaction databases have been developed. The problems of finding frequent item sets are basic in multi level association rule mining, fast algorithms for solving problems are needed. This paper presents an efficient version of apriori algorithm for mining multi-level association rules in large databases to finding maximum frequent itemset at lower level of abstraction. We propose a new, fast and an efficient algorithm (SC-BF Multilevel) with single scan of database for mining complete frequent item sets. To reduce the execution time and increase throughput in new method. Our proposed algorithm works well comparison with general approach of multilevel association rules.
Chapter 1 MODEL-GUIDED PROOF PLANNING

Proof planning is a form of theorem proving in which the proving procedure is viewed as a planning process. The plan operators in proof planning are called methods. In this paper we propose a strategy for heuristically restricting the set of methods to be applied in proof search. It is based on the idea that the plausibility of a method can be estimated by comparing the model class of proof lines newly generated by the method with that of the assumptions and of the theorem. For instance, in forward reasoning when a method produces a new assumption whose model class is not a superset of the model class of the given premises, the method will lead to a situation which is semantically not justified and will not lead to a valid proof in later stages. A semantic restriction strategy is to reduce the search space by excluding methods whose application results in a semantic mismatch. A semantic selection strategy heuristically chooses the method that is likely to make most progress towards filling the gap between the assumptions and the theorem. Each candidate method is evaluated with respect to the subset and superset relation with the given premises. All models considered are taken from a finite reference subset of the full model class. In this contribution we present the model-guided approach as well as first experiments with it.
Low latency packet processing in software routers

Commodity hardware can be used to build a software router that is capable of high-speed packet processing while being programmable and extensible. Therefore, software routers provide a cost-efficient alternative to expensive, special hardware routers. The efficiency of packet processing in resource-constrained nodes (e.g. software routers) can be strongly increased through parallel processing with commodity hardware based on multi-core processors. However, intra-node resource contention can have a strong negative impact on the corresponding network node. We describe how multi-core software routers can be optimized for low latency support by utilizing the technologies available in commodity PC hardware. For the analysis we used our approach for modeling of resource contention in resource-constrained nodes which is also implemented as the resource-management extension module for ns-3. Based on that, we derived a specific software router model which we used to optimize the performance. Our measurements show that the configuration of a software router has significant influence on the performance. The results can be used for parameter tuning in such systems.
Fault reparation time estimation based on exponential distribution function and software instability metric

Software maintenance phase contains modifying, training and help supporting. In this phase when faults occur, users will notify the problem to software maintenance team. The team has to provide the users the estimated fault reparation time and then fix the problems. Fault reparation time of different kinds of faults may be varied due to fault types and program instability. In this research, an estimation model for fault reparation time is proposed. The exponential probability density function and an instability metric are mainly used to construct the estimation model. The estimation model is exercised with some open source software projects. The experiment result shows the model constructed by applying both theory of exponential distribution and instability metric is significantly better than the model constructed by applying only theory of exponential distribution.
Principles of Public Relations.

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