Miracle-dz/UniFAR-FTUs huggingface dataset:
A wave theory of long adaptive filters

Long LMS filters of the tapped-delay line type are in widespread use, particularly in acoustic applications. For the limiting case of an infinite line length it is shown that the behavior of such filters is governed by remarkably simple laws. This is true for the steady state, where for small stepsizes the weight-error correlations become independent of the input signal, but also for the transient behavior, where the spatial Fourier transform of the weight-error distribution decays exponentially. Moreover, a necessary and (probably) sufficient stability bound for the stepsize is derived. The "wave theory" developed for the infinite line length also predicts the behavior of rather short filters with sufficient accuracy, particularly for a moderately colored input signal. No independence assumption is required and no assumption concerning the spectral distribution of the additive noise. Under steady-state conditions, the weight-error correlation between two line taps is solely determined by the noise autocorrelation, with the time delay replaced by the tap distance.
Climate change education for transformation: exploring the affective and attitudinal dimensions of children’s learning and action

Abstract In response to growing recognition for the mental health impacts of climate change, understanding the full range of children’s psychological experiences in climate change education (CCE) contexts is critical to developing approaches that support children’s constructive engagement and overall well-being. Through surveys and focus groups conducted with fifty-five children (ages 10–12), this mixed-methods study examined the affective and attitudinal impacts of a multi-site CCE program that encouraged children’s learning, reflection, and action. Findings suggest that, through the program, children acquired stronger pro-environmental attitudes, a deeper respect for nature, and a greater sense of urgency towards the need for climate action. Importantly, children’s negative emotions (e.g. fear, worry, anger, sadness) were mitigated by positive emotions grounded in youth-led climate action in family and community contexts. Findings are interpreted through theories of cognitive and affective transformation, which shed light on the beneficial micro- and macrolevel outcomes of children’s perspective shifts.
BIOMECHANICAL ANALYSIS OF THE DEFENSE TECHNIQUE IN TAI CHI PUSH HANDS

Developed from traditional Chinese martial arts, Tai Chi (TC) exercise includes different forms and Push Hands which are more advanced movements. No biomechanical analyses of interactive Push Hands have been found. To analyze the kinematic, kinetic and electromyographic characteristics of Tai Chi Push Hands, an experienced master was asked to defend pushing by another person for three trials. The movements were videotaped and digitized using a motion analysis system combining electromyography and force plate data. The results indicated that a certain postural adjustment was adopted by the master. A clear shift of body weight from the front to the rear foot and larger mediolateral displacement of the center of gravity (COG) was observed. Low activities were in the upper body muscle groups, while higher electromyographic values were in the right rectus femoris and substantially higher activity in the left rectus femoris during the defense. It is concluded that the TC defensive technique includes postural adjustment which slightly changes the pushing force direction, and allows the rear leg to resist the incoming force.
A damage diagnostic imaging algorithm based on the quantitative comparison of Lamb wave signals

With the objective of improving the temperature stability of the quantitative comparison of Lamb wave signals captured in different states, a damage diagnostic imaging algorithm integrated with Shannon-entropy-based interrogation was proposed. It was evaluated experimentally by identifying surface damage in a stiffener-reinforced CF/EP quasi-isotropic woven laminate. The variations in Shannon entropy of the reference (without damage) and present (with damage) signals from individual sensing paths were calibrated as damage signatures and utilized to estimate the probability of the presence of damage in the monitoring area enclosed by an active sensor network. The effects of temperature change on calibration of the damage signatures and estimation of the probability values for the presence of damage were investigated using a set of desynchronized signals. The results demonstrate that the Shannon-entropy-based damage diagnostic imaging algorithm with improved robustness in the presence of temperature change has the capability of providing accurate identification of damage in actual environments.
Survival of Campylobacter jejuni in Amoebae enhances subsequent invasion of mammalian cells

The ubiquitous unicellular eukaryote, Acanthamoeba, is known to play a role in the survival and dissemination of Campylobacter jejuni. C. jejuni is the leading cause of bacterial foodborne gastroenteritis world-wide and is a major public health problem. The ability of C. jejuni to interact and potentially invade epithelial cells is thought to be key for disease development in humans. We examined C. jejuni grown under standard laboratory conditions,11168HCBA with that harvested from within Acanthamoeba castellanii (11168HAC/CBA) or Acanthamoeba polyphaga (11168HAP/CBA), and compared their ability to invade different cell lines. C. jejuni harvested from within amoebae had a ∼3.7-fold increase in invasiveness into T84 human epithelial cells and a striking ∼11-fold increase for re-entry into A. castellanii cells. We also investigated the invasiveness and survivability of six diverse representative C. jejuni strains within Acanthamoeba spp. , our results confirm that invasion and survivability is likely host cell dependent. Our survival assay data led us to conclude that Acanthamoeba spp. are a transient host for C. jejuni and that survival within amoebae pre-adapts C. jejuni and enhances subsequent cell invasion. This study provides new insight into C. jejuni interactions with amoebae and its increased invasiveness potential in mammalian hosts.
Organizational Barriers To Chef Health Behaviors In Restaurant Kitchens In Suburban New Jersey: A Qualitative Pilot Study

Using a qualitative approach, this pilot study was conducted to identify organizational barriers in the kitchen environment that may be associated with negative health behaviors (dietary and lifestyle habits) among a select group of restaurant chefs. Data was collected using non-participant observations of six full-service restaurant kitchens located in the suburbs of northern New Jersey. Analysis of the observation templates and field notes revealed two major categories and several themes that provided insights into the role of multiple barriers in the kitchen environment influencing chef health including the design and layout of the kitchen, spatial organization, lighting, noise level, role definition, task delegation, and the level of social interactions between the chefs and their staff. The relevance of these findings to developing appropriate nutrition intervention programs for this population is discussed.
ALBATROSS: Multiagent, Rule-Based Model of Activity Pattern Decisions

The development of ALBATROSS: A Learning-Based, Transportation-Oriented Simulation System is summarized. This activity-based model of activity-travel behavior is derived from theories of choice heuristics that consumers apply when making decisions in complex environments. The model, one of the most comprehensive of its kind, predicts which activities are conducted when, where, for how long, and with whom, and the transport mode involved. In addition, various logical, temporal, spatial, spatial-temporal, and institutional constraints are incorporated in the model. The conceptual underpinnings of the model, its architecture, the functionality of its key agents, data collection, and model performance are discussed.
Reconstruction Domain Adaptation Transfer Network for Partial Transfer Learning of Machinery Fault Diagnostics

In industrial applications of machinery fault diagnostics, transfer learning is often used to transfer the knowledge learned from the source domain including labeled data to the target domain containing unlabeled data. This method follows the assumption that the label space in the source and target domain is the same. However, the label space of the target domain may be unknown in reality. For ensuring the integrity of knowledge, labeled data with all common fault types are considered as the source domain. However, if the label space of the target domain is less than that of the source domain, the negative effect from outlier classes will influence the performance. For solving this problem, a reconstruction domain adaptation transfer network (RDATN) is proposed. RDATN mainly contains health condition recognition and domain adaptation. The former is constructed for health condition recognition, while another one contributes to extracting domain-invariant features. Additionally, for reducing negative effects from outlier classes, a class-level weight and a sample-level weight are applied in the loss function. To improve the performance, particle swarm optimization (PSO) is applied to search for initial parameters for RDATN. The superiority of the proposed model is verified through three bearing datasets in two experiments.
Biogenic synthesis of silver-nanoparticles with the brackish water cyanobacterium Nostoc sphaeroides and assessment of antibacterial activity against urinary tract infecting bacteria

The aim of this study was to isolate a filamentous nitrogen-fixing cyanobacterium Nostoc sphaeroides (NS) from brackish water of Chilika Lake, Odisha coast, and exploration of its use in the biosynthesis of silver-nanoparticles (AgNPs) against the urinary tract–infecting bacterial strains. The synthesized NS-AgNPs were structurally characterized by analytical techniques such as UV-visible-spectrophotometry, FTIR, XRD, SEM and SEM-EDX. The antibacterial efficacy of synthesized AgNPs had remarkable in vitro activities with the MIC value of 50 mg/ml. Moreover, Nostocine A, the inherent bioactive compound of Nostoc sp. was further investigated for molecular docking studies against the targeted bacterial DNA gyrase (Escherichia coli) and the obtained docking score was −7.9 kCal/mol as compared with the standard drug, Ciprofloxacin of a docking score −7.8 kCal/mol. The concordance between molecular docking and experimental results is excellent. Thus, the biogenic-synthesized “N. sphaeroides-AgNPs” would be used as an antibacterial agent in future.
ADVANCES IN PLASTIC ANISOTROPY AND FORMING LIMITS IN SHEET METAL FORMING

In the last decades, numerical simulation has gradually extended its applicability in the field of sheet metal forming. Constitutive modelling and formability are two domains closely related to the development of numerical simulation tools. This paper is focused, on the one hand, on the presentation of new phenomenological yield criteria developed in the last decade, which are able to describe the anisotropic response of sheet metals, and, on the other hand, on new models and experiments to predict/determine the forming limit curves.Copyright © 2015 by ASME
Decoupled Power Control of Doubly-Fed Induction Generator Based on an Implicit Position and Speed Estimation Algorithm without the Flux Computation

Owing to the increased attention on the need for deployment of renewable energy sources such as the wind energy, there is a growing interest in Doubly Fed Induction Generators (DFIG) which are suitable for variable speed constant frequency generation. Accurate information of the rotor position with respect to the stator is central to the effective decoupled control of real and reactive power in the DFIG. Typically sensorless estimation of the rotor position involves complex signal processing. This paper presents the implementation of a simple and implicit sensorless algorithm for estimating the rotor position and speed for decoupled control of the doubly-fed induction generator. The proposed algorithm does not involve the computation of stator magnetic flux directly or indirectly using the voltage integration, recursive techniques, re-computations or programmable low pass filters etc. Instead, it employs simple analytical equivalents for the resolved components of the stator flux which are derived from the basic equations governing the machine operation. Since the flux terms are replaced with other equivalent terms, the estimation process is devoid of computing any flux terms and requires only the measured stator voltage and the currents in stator and rotor windings apart from the machine parameters. Starting on the fly, accurate estimation near synchronous speed, immunity against variation in stator and rotor resistances or in the magnetizing inductance are the principal advantages of the algorithm. Reduced complexity and the computational burden facilitate the easy implementation of the algorithm on a low cost fixed point processor. Excellent agreement between the simulation and test results on a laboratory doubly-fed induction machine validates the proposed estimation algorithm. Further MATLAB/Simulink based simulation results are presented to validate the efficacy of the position estimation algorithm based vector control of a doubly-fed induction generator.
Can motorcyclist behavior in traffic conflicts be modeled? A deep reinforcement learning approach for motorcycle-pedestrian interactions

Traffic simulation models have been utilized recently in safety evaluations by calculating traffic conﬂict indicators from simulated road user trajectories. However, existing simulation models (1) do not accurately capture road users’ behaviour and evasive actions, and (2) do not consider road users’ intelligence and rationality. This study proposes a safety-oriented microsimulation framework for modeling conflict interactions between motorcyclists and pedestrians in mixed traffic conditions. Motorcyclists are modeled as utility-based rational and intelligent decision-makers using a Markov Decision Process (MDP). Continuous Inverse Reinforcement Learning (IRL) is proposed to recover the motorcyclists’ reward function using their actual trajectories. The recovered motorcyclists’ reward function provides inferences into their behavior in conflict interactions. The motorcyclists’ optimal policies (sequences of decisions) are estimated using the Actor-Critic Deep Reinforcement Learning. The results show that the model simulated motorcyclist trajectories and the evasive actions with high accuracy. Moreover, the predicted PETs correlated well with corresponding field-measured conflicts.
A Low-Cost Launch Assistance System for Orbital Launch Vehicles

The author reviews the state of art of nonrocket launch assistance systems (LASs) for spaceflight focusing on air launch options. The author proposes an alternative technologically feasible LAS based on a combination of approaches: air launch, high-altitude balloon, and tethered LAS. Proposed LAS can be implemented with the existing off-the-shelf hardware delivering 7 kg to low-earth orbit for the 5200 USD per kg. Proposed design can deliver larger reduction in price and larger orbital payloads with the future advances in the aerostats, ropes, electrical motors, and terrestrial power networks.
Energy intake misreport: how different methods affect its prevalence and nutrient intake estimates

Abstract Background Although different methods for the evaluation of energy intake (EI) misreport have been described, it is unclear which one is the most appropriate. Aim To assess the performance of these methods in the prevalence of EI misreports and accuracy of nutrient intake estimates. Methods Reports of 3,639 adults from the Portuguese National Food, Nutrition and Physical Activity Survey 2015–2016 were classified using univariate (Willett; interquartile range) and multivariate (Goldberg; predicted total energy expenditure [pTEE], testing different standard deviations [SD]) methods. Self-reported intakes were compared to their respective estimates by urinary excretion in a sub-sample of 80. The effect of the exclusion of misreporters on nutrient estimates was assessed by the differences in linear regression coefficients between plausible and total sample. Results The highest prevalence of EI misreport was observed using pTEE 1SD (63.9%). Differences in the associations between nutrient self-reported intake and estimated intake using urinary biomarkers were verified with misreporters’ exclusion by pTEE 1SD method (β-protein = 0.209; 95% CI = 0.074–0.529; β-potassium = 0.276; 95% CI = 0.060–0.560) and Goldberg 2SD (β-protein = 0.080; 95% CI = 0.025–0.235; β-potassium = 0.106; 95% CI = −0.048–0.246). Conclusions Multivariate methods lead to a higher prevalence of misreports and larger differences in nutrient estimates. The application of the pTEE 1SD and Goldberg 2SD methods resulted in more accurate nutrient estimates.
A Method to Determine the Potential Toxicity of Smoke from Burning Polymers: I. Experiments with Douglas Fir

A small scale apparatus has been developed using a radiant source to burn Douglas fir specimens. Three irradiance levels were selected: 21, 35 and 50 kW/m2. Burning took place within an enclosure which was ventilated under known airflows, from levels just sufficient to maintain flaming combus tion to higher levels providing for more efficient flaming combustion. For each experiment flaming combustion was maintained for 30 minutes. The following variables were measured in each experiment: time to ignition, mass loss rate, flame height, O2 consumed, CO2 and CO produced and heat release. From CO measurements potential lethal conditions for mice or humans were evaluated using either CO production in ppm-min or using an equation to calculate COHb levels in blood. Within the range of irradiance levels and airflow levels evaluated the smoke produced by Douglas fir under flaming conditions can be below lethal potential to rapidly incapacitating and lethal. This new small- scale combustion module/animal exposure chamber system, termed the University of Pittsburgh II method (UPitt II) is a significant departure from previous attempts to evaluate toxicity of smoke from burning polymeric mate rials. It is also a significant improvement over previous systems because well defined burning conditions can be established over a wide range of irradiance and ventilation levels, not possible to examine with previous methods. Further more, performance of the specimens can be given in terms of time to ignition, flame height and heat release.
A Study of Student Work in FIDER–Reviewed First Professional Degree Programs

Findings from the content analysis of FIDER Accreditation Reports to 91 first–professional degree programs in interior design are presented. The objectives of the study were to identify differences in FIDER evaluations of student work in relation to 1) academic setting (architecture, fine–arts, home economics/human ecology), 2) accreditation status, and 3) baccalaureate and professional school programs. The findings show that evaluation of student work is based on specific and professional concerns for effective interior design practice, and provide reliable indications of the Foundation's decision to award or deny accreditation.
Is lean a theory? Viewpoints and outlook

PurposeLean remains popular in a wide range of private and public sectors and continues to attract a significant amount of research. However, most of this research is not grounded in theory. This paper presents and discusses different expert viewpoints on the role of theory in lean research and practice and provides guidelines for future research.Design/methodology/approachSeven experienced lean authors independently provide their views to the question “is Lean a theory? ” before Rachna Shah summarizes the viewpoints and provides a holistic outlook for lean research.FindingsAuthors agree, disagree and sometimes agree to disagree. However, a close look reveals agreement on several key points. The paper concludes that Lean is not a theory but has plenty of theoretical underpinnings. Many lean-related theories provide promising opportunities for future research.Originality/valueAs researchers, we are asked to justify our research drawing on “theory,” but what does that mean for a practice-driven phenomenon such as lean? This paper provides answers and directions for future research.
Developing a specific predetermined time study approach: an empirical study in a car industry

Determining accurate assembly cycle times in the car industry is an integral part of efficient production, human and facility planning. Three types of methods are available for determining cycle time for manual processes, including: estimating methods, direct observation method (stopwatch), and predetermined motion time systems (PMTSs). Estimating methods cannot determine accurate times. The direct observation method cannot be used for non-existent stations; in addition, this method is very tedious. Although PMTSs are able to properly determine assembly cycle times, some problems have decreased their usage. This paper presents the results of a project accomplished in the Iran-Khodro Car Company (IKCO), the most famous vehicle manufacturing factory in Iran and the Middle East. A particular predetermined time study approach is developed in this company which covers all body shop operations. Besides, some special time tables are developed by the combination of MOST and work time table standards. Finally, an easy-to-use worksheet is designed which can be filled out by moderately educated practitioners. The potential errors will be minimised in the proposed approach to compare with existing ordinary methods.
Using biomarkers to allocate patients in a response-adaptive clinical trial

Abstract In this paper, we discuss a response adaptive randomization method, and why it should be used in clinical trials for rare diseases compared to a randomized controlled trial with equal fixed randomization. The developed method uses a patient’s biomarkers to alter the allocation probability to each treatment, in order to emphasize the benefit to the trial population. The method starts with an initial burn-in period of a small number of patients, who with equal probability, are allocated to each treatment. We then use a regression method to predict the best outcome of the next patient, using their biomarkers and the information from the previous patients. This estimated best treatment is assigned to the next patient with high probability. A completed clinical trial for the effect of catumaxomab on the survival of cancer patients is used as an example to demonstrate the use of the method and the differences to a controlled trial with equal allocation. Different regression procedures are investigated and compared to a randomized controlled trial, using efficacy and ethical measures.
On six African species of Lyomyces and Xylodon

We studied a number of sub-Saharan collections of corticioid Xylodon and Lyomyces species, including several types. Morphological descriptions and molecular analyses based on the ribosomal DNA loci nuc rDNA ITS1-5.8S-ITS2 and when possible nuc 28S rDNA, allow us to introduce four new species: L. densiusculus, X. angustisporus, X. dissiliens, and X. laxiusculus. DNA barcodes for X. submucronatus and X. pruniaceus are published for the first time and X. pruniaceus is re-described.