Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Food Safety Knowledge and Attitudes of Managers of Residential Childcare Institutions (RCCI) in the Northeast

A needs assessment survey was designed and performed to measure both food safety knowledge of and attitudes toward food safety issues of key foodservice personnel of Residential Childcare Institutions (RCCIs) in the Northeast region. A total of 1,230 surveys were distributed and received by individual RCCI site addresses;186 were included in the analysis, for a 15.1% return rate. Respondents answered 44 questions on food safety topics in food safety content areas of cook/prepare, chill/ cold storage, clean/hygiene, receiving/general storage, food handling and allergens. The response for the questions was agree, disagree, don’t know or not applicable. A Likert scale response format was used for attitude questions. Descriptive one-way ANOVA and t-tests were run. Using 80% as the standard for subject mastery, only 27 of the 44 items (55%) met the proficiency standard, with cook/prepare (66%) and chill/cold storage (67%) having the lowest mean correct scores. Facilities with ≤ 20 residents scored significantly lower in total knowledge (P < 0.05) than larger institutions, with scores of 71% and 80%, respectively. Smaller facilities received significantly lower scores in 5 of the 6 content categories and were less likely to have food safety plans (67% versus 83% for larger) or recipes based on HACCP implementation (28% versus 64% for larger). Overall attitude scores reflected a positive belief about responsibilities for general food safety practices and implementation of food safety practices, policies, inspections and training. Eighty percent (80%) indicated that they would like to see food safety training provided for staff and/or residents. Assessment of Food Safety Knowledge and Attitudes of Managers of Residential Childcare Institutions (RCCI) in the Northeast
Social capabilities preserved in alzheimer patients

Alzheimer patients in the early stage of the disease were asked to participate in the Dictator game, a game in which each subject has to decide how to allocate a certain amount of money between himself and another person. The game allows the experimenter to view the influence of social norms and preferences on the decision-making process. When the data from the experiment are compared with the results of an identical experiment involving two control groups with similar ages and social background, one group with Mild Cognitive Impairment patients, the other with healthy subjects, it appears that the results from the three groups are statistically undistinguishable. This is an indication that Stage I AD patients are as capable of making decisions involving social norms and preferences as any person of their age, and that whatever brain structures are affected by the disease, they do not include, at this stage, the neural basis of cooperation-enhancing social interactions.
Performance Criteria Research on PSO-PID Control Systems

Many results have emerged in design of controller based on numerical optimization techniques, along with various system performance criteria. This paper enumerates common cost function, within which four typical criteria are used as cost function to conduct simulation based on particle swarm optimization. The effects of different cost function cast on system performance are analyzed based on simulation results. The conclusion can be extended to other numeral optimization techniques, and possess high practical value.
Impairment in motion discrimination tasks is unrelated to amount of damage to superior temporal sulcus motion areas

The behavioral role of the middle temporal (MT/V5) area and its satellites in motion processing is still unclear, particularly the degree to which MT/V5 proper is critical for different types of motion processing. Therefore, effects of small and large lesions in the caudal part of the superior temporal sulcus of macaque monkeys were compared for two tasks requiring different types of motion processing: a direction and a kinetic orientation discrimination. The small lesion was restricted to the peripheral representation of MT/V5 but included V4t, whereas the large lesion included all of MT/V5 and the medial superior temporal (MST) area as well as substantial parts of the floor of the superior temporal (FST) area. Both lesions resulted in significant and long‐lasting impairment of direction discrimination but had a lesser effect on kinetic orientation discrimination. Thus the effects of small STS lesions on motion perception are much stronger than expected. J. Comp. Neurol. 420:539–557, 2000. © 2000 Wiley‐Liss, Inc.
Metric of affine shape and motion: the intuitive interpretation in terms of the factorization method

The factorization method has been sued for recovering both the shape of an object and the motion of a camera from sequential images. This method consist of two steps. The first step is to decompose measurement matrix into a product of two matrices. And the second step is to determine a non- singular matrix to revise these matrices. Mathematical consideration of this method is not paid much attention. In this paper, we elucidate the mathematical meaning of the second step. This gives intuitive interpretation of many facts of shape from motion problem. It makes clear to understand why we need three distinct affine projection images to determine the shape and motion of camera and what information we can get from two affine projection images. We also consider the factorization method for two images.
International commodity prices – volatility and global liquidity

Recent years have witnessed large fluctuations in international commodity prices. A boom in commodity prices until 2008 was followed by a sharp decline during the peak of the financial crisis. Since early 2009, prices of major groups of commodities rose to levels close to or even above the peak reached in 2008. For some commodities, the speed and amplitude of the recent price swings have been large by historical standards. There has been a persisting concern about the high and volatile behaviour of commodity prices in view of its likely impact on macroeconomic situation. The most prolonged global financial crisis since the Great Depression is not yet over and the loose monetary policy with very low interest rates and monetary easing through injection of liquidity by major advanced economy central banks continue. In this scenario, the subject of analyzing the impact of global liquidity on the commodity, consumer and asset prices has been receiving considerable attention.
Automated debugging of SLO violations in enterprise systems

A critical business requirement of today's enterprise applications is automated debugging of violation of Service Level Objectives (SLOs). However, the increasing scale and complexity of these systems present various challenges in building such solutions. This problem becomes challenging mainly because of two reasons: (1) availability of large number of metrics that can potentially be the causes, (2) availability of large number of data-points. The existing techniques are either highly compute-intensive and thus are not viable for use on large volumes of data or compromise on accuracy. To successfully balance these two objectives simultaneously, we propose to intelligently prune the search space. We apply feature selection to remove irrelevant and redundant metrics. We then identify temporal regions of interest to narrow down the analysis to a smaller set of data-points. We present a comparative study of the proposed approach with other existing approaches through experimental evaluation.
Protecting the Access Network : Efficient Algorithms for Survivable Topology ∗

It is important to prevent access network from bottlenecking the end-to-end survivability, especially as voice, video, and data traffic are all delivered through the same access network. With economic constraints and limited routing capability, the structure of an access network is typically a “fat tree”, where the terminal has to relay the traffic from another terminal of the same or higher level. New graph theory problems naturally arise from such features of access network models, different from those targeted towards survivable backbone (mesh) networks. We model the important problem of provisioning survivability to an existing single-level fat tree through two graph theory problem formulations: the Terminal Backup problem and the Simplex Cover problem, which we show to be equivalent. We then develop two polynomial-time approaches, indirect and direct, for the Simplex Cover problem. The indirect approach of solving the matching version of Simplex Cover is convenient in proving polynomial-time solvability though it is prohibitively slow in practice. In contrast, leveraging the special properties of Simplex Cover itself, we demonstrate that the direct approach can solve the Simplex Cover problem very efficiently even for large networks. Extensive numerical results of applying our algorithms are also reported for designing survivable access networks over different types of topologies. We also investigate the complexity and algorithm for the general case with a multi-level fat tree.
On stochastic receding horizon control with bounded control inputs

This paper is concerned with the problem of receding horizon control of discrete-time systems subject to possibly unbounded random noise inputs, while satisfying hard bounds on the control inputs. We use a nonlinear feedback policy with respect to noise measurements and show that the resulting mathematical program has a tractable convex solution. Moreover, under the assumption that the zero-input and zero-noise system is asymptotically stable, we show that the variance of the state, under the resulting receding horizon control policy, is bounded. Finally, we provide some numerical examples on how certain matrices in the underlying mathematical program can be calculated off-line.
Impact of the NGF Maturation and Degradation Pathway on the Cortical Cholinergic System Phenotype

Cortical cholinergic atrophy plays a significant role in the cognitive loss seen with aging and in Alzheimer's disease (AD), but the mechanisms leading to it remain unresolved. Nerve growth factor (NGF) is the neurotrophin responsible for the phenotypic maintenance of basal forebrain cholinergic neurons in the mature and fully differentiated CNS. In consequence, its implication in cholinergic atrophy has been suspected; however, no mechanistic explanation has been provided. We have previously shown that the precursor of NGF (proNGF) is cleaved extracellularly by plasmin to form mature NGF (mNGF) and that mNGF is degraded by matrix metalloproteinase 9. Using cognitive-behavioral tests, Western blotting, and confocal and electron microscopy, this study demonstrates that a pharmacologically induced chronic failure in extracellular NGF maturation leads to a reduction in mNGF levels, proNGF accumulation, cholinergic degeneration, and cognitive impairment in rats. It also shows that inhibiting NGF degradation increases endogenous levels of the mature neurotrophin and increases the density of cortical cholinergic boutons. Together, the data point to a mechanism explaining cholinergic loss in neurodegenerative conditions such as AD and provide a potential therapeutic target for the protection or restoration of this CNS transmitter system in aging and AD.
A New Mult-Finger Tactual Display

A multi-finger positional display (the TACTUATOR) was developed to study communication through the kinesthetic and vibrotactile aspects of the tactual sensory system of the hand. The display consists of three independent single contact-point actuators interfaced (individually) with the fingerpads of the thumb, the index finger, and the middle finger. Each actuator utilizes a disk-drive head-positioning motor augmented with angular position feedback from a precision rotary variable differential transformer (RVDT). A floatingpoint DSP system provides real-time positional control using a digital PID controller. Stimuli from threshold to about 50 dB SL can be delivered throughout the frequency range from near DC to above 300 Hz, thereby encompassing the perceptual range from gross motion to vibration. Actuator frequency and step responses are well modeled as a second-order linear system. Distortion is low allowing delivery of arbitrary stimulus waveforms, e.g., 25 mm low-frequency motion with superimposed high-frequency vibration. System noise and inter-channel crosstalk are also small. As one example of behavioral performance verification, absolute thresholds measured with the stimulator are in general agreement with values in the literature. Overall, the TACTUATOR accurately follows its drive waveforms and is well suited for a variety of multi-finger tactual perceptual studies.
Wage Growth and Job Mobility in the Early Career: Testing a Statistical Discrimination Model of the Gender Wage Gap

The paper focuses on the early career patterns of young male and female workers. It investigates potential dynamic links between statistical discrimination, mobility, tenure and wage profiles. The model assumes that it is more costly for an employer to assess female workers' productivity and that the noise/signal ratio tapers off more rapidly for male workers. These two assumptions yield numerous theoretical predictions pertaining to gender wage gaps. These predictions are tested using data from the 1979 cohort of the National Longitudinal Survey of Youth. As predicted by our statistical discrimination model, we find that men and women have the same wage at the start of their career, but that female wages grow at a slower rate, creating a gender wage gap. Also consistent with our model, we find that mean wages are higher for workers who keep their job, while wage growth is stronger for workers who change job.
Hierarchical Small-World P2P Networks

In order to increase the efficiency of routing and querying, decrease the maintenance cost of structure P2P network, a hierarchical small-world P2P networks (HSN) with low maintenance cost is proposed in this paper, which describe the methods about how to create and maintenance a P2P network. To demonstrate the value of HSN, this paper simulates Chord and HSN with different networks size and system parameters, and the result shows that (1) the route latency of HSN is smaller than O(logN) , where is the number of nodes in the P2P networks, (2) HSN maintenance cost decreased nearly the half of the Chord.
Day-Of-The-Week Effects in Overnight Interest Rates: Evidence from Turkish Money Markets

This study examines the daily seasonalities in Turkish Money Markets. Day-of-the week effects in overnight interest rates in the Central Bank Interbank Money and Istanbul Stock Exchange Repo Markets are investigated. Results show that overnight interest rates significantly fall on Wednesdays and increase on Mondays relative the previous days which indicated the existence of significant day-of-the-week-effect in overnight interest rates. There are also two other strong trends in interest rates indicate the decrease on Tuesdays and increase on Fridays. Some evidences are documented for the relationship between the existence of day effect in overnight interest rates and Treasury Public Borrowing Auctions, institutional practices, strategies of market participants and the other factors which effect the liquidity conditions of the market and create the seasonality in liquidity. Findings are consistent with the liquidity conditions of the market, the liquidity and so money policy of the Central Bank and Treasury Auction-related practices for the day-of-the-week effect in overnight interest rates which shows that regulatory bodies of the markets and public authorities have an important creative impact on the seasonalities in interest rates.
A Main Directional Mean Optical Flow Feature for Spontaneous Micro-Expression Recognition

Micro-expressions are brief facial movements characterized by short duration, involuntariness and low intensity. Recognition of spontaneous facial micro-expressions is a great challenge. In this paper, we propose a simple yet effective Main Directional Mean Optical-flow (MDMO) feature for micro-expression recognition. We apply a robust optical flow method on micro-expression video clips and partition the facial area into regions of interest (ROIs) based partially on action units. The MDMO is a ROI-based, normalized statistic feature that considers both local statistic motion information and its spatial location. One of the significant characteristics of MDMO is that its feature dimension is small. The length of a MDMO feature vector is 36 × 2 = 72, where 36 is the number of ROIs. Furthermore, to reduce the influence of noise due to head movements, we propose an optical-flow-driven method to align all frames of a micro-expression video clip. Finally, a SVM classifier with the proposed MDMO feature is adopted for micro-expression recognition. Experimental results on three spontaneous micro-expression databases, namely SMIC, CASME and CASME II, show that the MDMO can achieve better performance than two state-of-the-art baseline features, i.e., LBP-TOP and HOOF.
A Hybrid 2/3 Level Converter With Minimum Switch Count

Multilevel topologies have emerged as a viable technique for medium and high voltage inverters but in the low voltage range they have failed to attract much interest due to their increased cost associated with the additional components and complicated control. This paper proposes a new hybrid converter that combines features from both two- and three-level converters with a reduced number of extra semiconductors. It is shown that for a very wide modulation index this converter can switch the maximum and the minimum phase voltages as a three-level converter while the third phase voltage is switched as a two-level converter. Only for a very narrow band in the modulation index range this topology behaves as a two-level converter. The proposed approach is implemented on a 16-bit fixed point DSP (ADSP 21992) and tested on a three-phase 20 kW IGBT-based PWM inverter
Online Structure Learning for Sum-Product Networks with Gaussian Leaves

Sum-product networks have recently emerged as an attractive representation due to their dual view as a special type of deep neural network with clear semantics and a special type of probabilistic graphical model for which inference is always tractable. Those properties follow from some conditions (i.e., completeness and decomposability) that must be respected by the structure of the network. As a result, it is not easy to specify a valid sum-product network by hand and therefore structure learning techniques are typically used in practice. This paper describes the first online structure learning technique for continuous SPNs with Gaussian leaves. We also introduce an accompanying new parameter learning technique.
Factorization of Finite-State Transducers

Finite-state transducers and finite-state automata are efficient and natural representations for a large variety of problems. We describe a new algorithm for turning a finite-state transducer into the composition of two deterministic finite-state transducers such that the combined size of the derived transducers can be exponentially smaller than other known deterministic constructions. As a consequence, this can also be used to build deterministic representations of finite-state automata smaller than the minimal finite-state automata computed by the classic determinization and minimization algorithms. We also report experimental results on large scale dictionaries and rule-based systems. This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Copyright c ©Mitsubishi Electric Research Laboratories, Inc., 1995 201 Broadway, Cambridge, Massachusetts 02139
Coalgebraic Quantum Computation

Coalgebras generalize various kinds of dynamical systems occuring in mathematics and computer science. Examples of systems that can be modeled as coalgebras include automata and Markov chains. We will present a coalgebraic representation of systems occuring in the field of quantum computation, using convex sets of density matrices as state spaces. This will allow us to derive a method to convert quantum mechanical systems into simpler probabilistic systems with the same probabilistic behaviour.
Employees' Perceptions of Performance Appraisal

ABSTRACT In spite of the importance of performance appraisal for hotels to evaluate their employees, the existing hospitality literature largely covers studies in Western countries only. Prior studies have rarely investigated the issue of performance appraisal in the context of China, the world's largest potential market for generating tourists and receiving tourists. This paper reports on a study that used focus group interviews with employees in an upscale hotel in Hong Kong, a special administrative region in China, on their views of the appraisal system that has been used. Research findings reveal that the system could be further improved.
The Premises And The Evolution Of Electronic Commerce

Inevitably, the boom in technology and informational technology have had an impact on the business world since the late '80s, when the Internet began to penetrate the lives of millions of users around the globe. Currently, concepts such as e-business or e-commerce have found their place and applicability inside the global economy with ease, knowing it promoted models exhibiting an accelerated rate of development, well above the usual average growing rate of the traditional economy. Although the industry (especially the American one) saw a critical moment in the early 2000s, the obstacles have been overcome, confirming a continuous rise of electronic commerce in the last twenty years. The purpose of this article is to highlight some of the characteristics of electronic commerce, the global implementation stage, reviewing in the process the main steps taken in this area up to the present and last but not least to identify possible development trends for the future.
Integrated Parallel Sentence and Fragment Extraction from Comparable Corpora: A Case Study on Chinese--Japanese Wikipedia

Parallel corpora are crucial for statistical machine translation (SMT); however, they are quite scarce for most language pairs and domains. As comparable corpora are far more available, many studies have been conducted to extract either parallel sentences or fragments from them for SMT. In this article, we propose an integrated system to extract both parallel sentences and fragments from comparable corpora. We first apply parallel sentence extraction to identify parallel sentences from comparable sentences. We then extract parallel fragments from the comparable sentences. Parallel sentence extraction is based on a parallel sentence candidate filter and classifier for parallel sentence identification. We improve it by proposing a novel filtering strategy and three novel feature sets for classification. Previous studies have found it difficult to accurately extract parallel fragments from comparable sentences. We propose an accurate parallel fragment extraction method that uses an alignment model to locate the parallel fragment candidates and an accurate lexicon-based filter to identify the truly parallel fragments. A case study on the Chinese--Japanese Wikipedia indicates that our proposed methods outperform previously proposed methods, and the parallel data extracted by our system significantly improves SMT performance.