Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards The Flexible Form: How To Remain Vital in Hypercompetitive Environments

textabstractHypercompetition has received much attention, by an important question has not been answered: What organizational forms lead to success in hypercompetitive environments? Hypercompetition forces firms to move more quickly and boldly and to experiment in ways that do not conform to traditional administrative theory. Bureaucratic vertical forms I severely hamper the ability to respond to accelerating competition. Flexible forms, in contrast, can respond to a wide variety ot changes in the competitive environment in an appropriate and timely way. The author examines several alternative flexible forms for coping with hypercompetitive environments. Flexibility derives from the repertoire of managerial capabilities (management challenge) and the responsiveness of the organization (organization design challenge). On the basis of theories of control, the author argues that organizational flexibility is inherently paradoxical and requires a constructive friction between change and preservation. The paradox of flexibility is portrayed in a conceptual model that relates competitive environments, certain types of flexibility, and organizational conditions. The author develops a rich typology of organizational forms for coping with hypercompetition, each of which reflects a particular way of addressing change and preservation. Furthermore, he explores different trajectories of organizational development over time, especially those relating to revitalization. The implications of the typology for strategy and organization design research in hypercompetitive environments are profound.
An Improved Model Free Predictive Current Control for PMSM with Current Prediction Error Variations

The conventional model predictive current control is a model-based control method, and the accuracy of the predicted currents is affected by motor parameters such as flux linkage, inductance, and resistance. To get rid of model parameters dependencies, a model-free predictive current control (MFCC) was proposed before, which can improve the parameter robustness without utilizing any knowledge of the initial motor parameters. However, the stagnant current update detection is one of the main problems that limit the current predictive performance. To solve this problem, a current prediction error model according to the contiguous instant current error variations is proposed to reconstruct the surface-permanent magnet synchronous motor (SPMSM) model in this paper. Afterwards, a novel MFCC method with the online parameter identification is developed. This method takes advantage of mathematical relationships in the current prediction error model, and the motor parameters can be updated within each period to improve prediction accuracy. Simulation and experimental results verify that this proposed MFCC method can significantly reduce the stagnation effect and improve MFCC performance under different parameter disturbances.
Value of Flexibility - Phase 1

Abstract : This report provides findings from the research conducted under the Phase 1 of RT-18-Valuing Flexibility. The primary goal of this research project is to identify, develop and validate sound quantitative methods, processes, and tools that will enable DoD leadership and program managers to make a convincing case for investments in system flexibility when acquisition decisions are made. The research during this period focused on identifying current quantitative MPTs for valuing flexibility in DoD context, and delivering an initial capability to value investments that provide the flexibility to handle foreseeable sources of change, using easy-to-understand monetizable terms, such as the effect of the investments on total cost of ownership or return on investment. We conducted a critical evaluation of the theoretical foundations underlying current approaches, the dimensions of flexibility, measures of flexibility, value functions, and methods for incorporating flexibility both at the design phase and the operational phase, to identify strengths and weaknesses of each approach. During this period, we also explored the development of an analytical framework based on sound mathematical constructs. This report also presents our advances in defining and formalizing the value of flexibility and the underlying capability-need-value architecture that can be used by systems acquisition decision-makers.
The adaptive lane-departure warning system

A vision-based lane-departure warning system which adapts the variation of brightness is developed in this paper. By sequentially applying the proposed processing techniques as lane strengthening, dichotomy, and smoothing filtering, an efficient decision rule is then applied to the processed image to realize the lane-departure warning system. Moreover, according to the variation of the brightness by reading the output of a photo-resistance sensor, the adaptive threshold for dichotomy is achieved. The present system effectively achieves real-time lane-departure warning with 10 decisions per second and 97.4% correct detection rate as driving angles varied larger than /spl plusmn/5/spl deg/ in the experiments.
Energy Efficient Wireless Offloading Scheme Based on Lyapunov Optimization with Preservation of Secrecy and Privacy

Multi-access edge computing (MEC) architecture is emerging as a promising paradigm to improve the computing quality for mobile devices. Nevertheless, the offloading process of MEC encounters privacy and security problems. Independent protection for security and privacy will lead to different offloading policies which may contradict with each other. Besides, high unpredictability of channel information and the threaten of vicious edge nodes make it very challenging to offload securely. To address the problem about privacy and security, this paper proposes a Lyapunov-based privacy-aware secure offloading scheme. The scheme minimizes average energy consumption with known and unknown channel information of the eavesdropper. Lyapunov optimization is resorted to design an efficient online task offloading algorithm which can reduce the energy consumption under the strict security and privacy requirements. When compared to other schemes in the simulation, the proposed algorithm achieves fewer energy consumption and guarantees the security and the privacy in MEC offloading process.
Pulse based dead time compensator for PWM voltage inverters

The dead time necessary to prevent the short circuit of the power supply in pulse width modulated (PWM) voltage inverters for AC drives results in output voltage deviations. Although individually small, when accumulated over an operating cycle, the voltage deviations are sufficient to distort the applied PWM signal. This paper presents a new method to correct for the dead time deviations. The pulse based compensator is less hardware and software intensive than other dead time compensation methods providing a low cost solution. The pulse based technique is developed by analyzing the effects of dead time on a pulse by pulse basis and correcting each pulse accordingly. The technique is evaluated through simulation and experimental results. Other compensation methods are evaluated and the results compared with the pulse based technique. This comparison indicates previous methods can produce magnitude and phase errors in the applied terminal voltage, whereas the proposed method compensates for the dead time without significant magnitude and phase errors in the terminal voltage of PWM voltage source inverters.
The Effect of Loading Time on Color Stability of Various Restorative Materials Bonded to Silver Diamine Fluoride-Treated Demineralized Dentin

Aim To investigate the effect of immediate versus one week later loading time on color stability of resin-based composite (RBC), resin-modified glass ionomer cement (RMGIC) and glass ionomer cement (GIC) restorative materials bonded to silver diamine fluoride (SDF)-treated demineralized dentin. Materials and Methods Ninety extracted premolars were randomly assigned to the following groups (n = 30 each): group-I (loaded with RBCs), group-II (loaded with RMGIC), and group-III (loaded with GIC). Each group was divided randomly into the following subgroups (n = 10): subgroup-A (control specimens) consisted of sound dentin and the restorative material was immediately loaded; subgroup-B consisted of demineralized dentin, underwent a SDF treatment and the restorative material was immediately loaded; subgroup-C consisted of demineralized dentin, underwent a SDF treatment and the restorative material was loaded 1 week later. The color difference (ΔE) and visual color changes (L*a*b*) of each specimen were calculated using a spectrophotometer. Data were analyzed using one-way ANOVA and post hoc Tukey’s tests to compare the ΔE values and a paired t test to compare the mean of L* a* b* coordinates. Results The highest color stability was observed for GIC, followed by RMGIC, and the lowest color stability was observed for the RBC group. Significant differences within groups were noted in RBC and RMGIC (p < 0.001). Regarding the loading time of the restorative material, in RBCs, a significantly lower ΔE value was observed in the delayed loading group than in the immediate loading group (p = 0.035). In the RMGIC and GIC groups, there were no significant differences. Conclusion Delaying the loading time of the restorative material for 1 week following the application of SDF resulted in greater color stability than that of immediate loading. The caries arresting potential of SDF was revealed by the dark staining, which could be improved with the subsequent delayed restoration.
Detection of Early Reflections in the Room Impulse Response by Estimating the Excess Coefficient at Short Time Intervals

A new method of automatic detection of early reflections in room impulse responses is studied. This method consists in estimating the excess coefficient within the impulse response segments into which they are divided, and in comparing these estimates with a certain threshold value. The threshold value choice is based on a predetermined probability of error detection of the burst caused by early reflection and on the length of the segment. The efficiency of this method and the corresponding experimental algorithm is checked with the use of simulated and real room impulse responses. In the case of simulated room impulse responses, the method and algorithm general efficiency have been shown. In the case of real room impulse responses, the first early reflection from the ceiling was correctly detected in 90% of cases, and the error of estimation of time of arrival did not exceed 0.15 ms. These results indicate the effectiveness of the proposed method.
Five-year outcomes of mild paravalvular regurgitation after transcatheter aortic valve implantation.

BACKGROUND Mild paravalvular regurgitation (PVR) remains a frequent and underappreciated adverse event after transcatheter aortic valve implantation (TAVI) despite remarkable progress in device technology and implantation technique. AIMS This study sought to investigate the impact of mild PVR after TAVI on five-year clinical outcomes. METHODS In a prospective TAVI registry, PVR prior to discharge was retrospectively assessed in an echocardiographic core laboratory. Patients with ≥moderate PVR were excluded. Mild PVR was categorised into mild and mild-to-moderate PVR using a recently proposed unifying 5-class grading scheme. RESULTS A total of 1,128 patients undergoing TAVI between 2007 and 2015 were enrolled. Of these, 560 patients had mild PVR, including 433 with mild (5-class) PVR and 127 with mild-to-moderate PVR. Patients with mild PVR were older (83 years vs 82 years, p=0.013) and had a higher surgical risk compared to patients with none/trace PVR (STS-PROM: 6.49±4.68 vs 5.41±3.48, p<0.001). At five years, patients with mild PVR had a higher risk of mortality than those with none/trace PVR (54.6% vs 43.8%; HRadjusted 1.26, 95% CI: 1.06-1.50). When applying the 5-class grading scheme, only mild-to-moderate PVR was associated with an increased risk of mortality at five years (mild PVR: HRadjusted 1.19, 95% CI: 0.99-1.43, mild-to-moderate PVR: HRadjusted 1.56, 95% CI: 1.20-2.02). The effect of mild PVR on five-year mortality was consistent across major subgroups. CONCLUSIONS Mild PVR was associated with an increased risk of mortality at five years after TAVI. The detrimental effect was primarily driven by mild-to-moderate PVR using the 5-class grading scheme. CLINICAL TRIAL REGISTRATION https://www.clinicaltrials. gov. NCT01368250.
Quantification of Arsenic Species in Wheat Flour Samples by Ion Chromatography Coupled to High Resolution Inductively Coupled Plasma-Mass Spectrometry (IC-HR-ICP-MS)

Abstract A method was developed for arsenic speciation of South African wheat flour by microwave-assisted extraction with ion chromatography (IC) separation and detection with high resolution inductively coupled plasma–mass spectrometry (IC-HR-ICP-MS). Method optimization included development of the extraction and elution methods for baseline separation of the As-species in the samples. The As-species were successfully extracted using deionized water and baseline separation was attained using a gradient elution method with 0.5 mM HNO3 (pH 3.4) and 50 mM HNO3 (pH 1.4). Method validation parameters, including trueness (bias), precision, linearity, limit of detection (LOD), limit of quantification (LOQ) and selectivity were evaluated to assess the quality of the results. Three certified reference materials (CRMs), NIST SRM 1568b (rice flour), NMIJ CRM 7533-a (brown rice flour), and ERM BC211 (brown rice flour) were used to evaluate the trueness of the developed method. Low limits of detection and quantification were achieved (0.3 to 2.6 pg g−1 and 1.1 to 8.6 pg g−1, respectively) for the As-species. The dominant peaks in the wheat flour were arsenite (As(III)), dimethyl arsenic acid (DMA), and arsenate (As(V)). The concentrations of the inorganic (iAs), i.e., As(III) and As(V) in the wheat flour were very low from 6.8 to 17.8 ng g−1, with a relative expanded uncertainty ( ) of <6.9% ( =2), which is below the permissible level of iAs in food and food products proposed by the World Health Organization (WHO).
Runtime Trojan Detection using Step-Based Reverse Function Redundancy Algorithm

Lightweight ciphers are built to encrypt data in particular for resource-constrained devices (RCDs). Hardware Trojans (HTs) are integrated in lightweight chippers building designs to leak sensitive data. Runtime monitoring techniques effectively detects HTs, however, require significant resources (area, power and energy). Recently, runtime monitoring algorithm based on reverse-function redundancy (RFR) was proposed. RFR minimizes energy and power but requires significant area resources to implement critical nodes' monitors. The objective of this research is to develop a simplified runtime monitoring algorithm with minimal area resources, power and energy. The algorithm uses step-based reverse function redundancy (SRFR), facilitates design-for-trust and is targeted for lightweight ciphers in RCDs. Initially, several optimization techniques were examined and then incorporated in the proposed algorithm. Implementation results show that area resources were significantly reduced by 60%. Compared with RFR, SRFR algorithm decreases the power by 5 % and the energy by % 8.
Grief, Continuing Bonds, and Unreciprocated Love
 1

a Bstract : The widely accepted “continuing bonds” model of grief tells us that rather than bereavement necessitating the cessation of one’s relationship with the deceased, very often the relationship continues instead in an adapted form. However, this frame- work appears to conflict with philosophical approaches that treat reciprocity or mutuality of some form as central to loving relationships. Seemingly the dead cannot be active participants, rendering it puzzling how we should understand claims about continued relationships with them. In this article, we resolve this tension by highlighting two fundamental aspects of paradigmatic loving relationships that can, and often do, continue in an adapted form following bereavement: love and mutual shaping of interests, choices, and self- concepts. Attention to these continuing features of relationships helps to capture and clarify the phenomenological and behavioral features of continuing bonds. However, love and mutual shaping must also change in important ways following bereavement. Love becomes unreciprocated, and although the dead continue to shape our interests, choices, and self- concepts, we predominantly shape their legacies mind science an emphasis on perception, emotion, and interpersonal and memories in return. These changes place important constraints upon the nature of our interpersonal connections with the dead.
SEMI-AUTOMATED TEST MODEL GENERATION

Appropriate test models that can satisfy complex constraints are required for testing model management programs in order to build confidence in their correctness. Models have inherently complex structures and are often required to satisfy non-trivial constraints which makes them time consuming, labour intensive and error prone to construct manually. Automated capabilities are therefore required, however, existing fully-automated model generation tools cannot generate models that satisfy arbitrarily complex constraints. This thesis addresses this problem by proposing a semi-automated approach towards the generation of such models. A new framework named Epsilon Model Generator (EMG) that implements this approach is presented. The framework supports the development of model generators that can produce random and reproducible test models that satisfy complex constraints.
Heavy Metal Contamination of Animal Feed in Texas

The management of animal feed safety risks using a risk management framework begins with identifying and quantifying the presence of hazards. For animal feed, a paucity of information exists about the presence of heavy metal in feed ingredients, premixes, and finished feed. This study examines 564 feed samples over a period of five years (2010-2015) collected by Texas Feed and Fertilizer Control Service (FFCS) investigators using ocial sampling and chain-of-custody techniques. Samples were prepared and analyzed in the Oce of the Texas State Chemists laboratory (Agricultural Analytical Service) on the campus of Texas A&M University in College Station, TX. The heavy metals of concern included arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), lead (Pb), mercury (Hg), molybdenum (Mo), nickel (Ni), selenium (Se), and thallium (Tl). Data were analyzed using descriptive statistic techniques and summarized by element, feed type, and year. During 2010, 28% of the samples contained detectable levels of heavy metals, a few of which contained higher than maximum tolerable levels of the elements [1]. The percentage of detectable heavy metals increased in subsequent years as the analytical technique used became more sensitive and an increased number of heavy metal contaminants were analyzed. A positive skewness was observed for most heavy metals in most ingredients resulting for the detection of high levels of contamination among a few samples. This study provides a comprehensive analysis of heavy metals during the prescribed time period and ingredient/finished feed type and will facilitate risk assessment and implementation of risk management techniques prescribed by the Food Safety Modernization Act requirements that impacts the United States and global feed industry.https://doi.org/10.21423/jrs-v04n01p021 (DOI assigned 7/23/2019)
Integration of Single-Port Memory (ISPM) for Multiprecision Computation in Systolic-Array-Based Accelerators

On-chip memory is one of the core components of deep learning accelerators. In general, the area used by the on-chip memory accounts for around 30% of the total chip area. With the increasing complexity of deep learning algorithms, it will become a challenge for the accelerators to integrate much larger on-chip memory responding to algorithm needs, whereas the on-chip memory for multiprecision computation is required by the different precision (such as FP32, FP16) computations in training and inference. To solve it, this paper explores the use of single-port memory (SPM) in systolic-array-based deep learning accelerators. We propose transformation methods for multiple precision computation scenarios, respectively, to avoid the conflict of simultaneous read and write requests on the SPM. Then, we prove that the two methods are feasible and can be implemented on hardware without affecting the computation efficiency of the accelerator. Experimental results show that both methods have about 30% and 25% improvement in terms of area cost when accelerator integrates SPM without affecting the throughput of the accelerator, while the hardware cost is almost negligible.
Nasal Septum Anatomy and Deviations: beyond straight and flat

Poster: "ECR 2015 / C-1810 / Nasal Septum Anatomy and Deviations: beyond straight and flat" by: "V. Familiar Carrasco1, S. Mancheva Maneva1, A. Cabeza Carreto1, B. Sobrino Guijarro1, C. Ordonez-Gonzalez2, J. Del Valle1, J. Montoya1; 1Madrid/ES, 2Murcia/ES"
Balancing Latency and Energy Efficiency in mmWave 5G NR Systems With Multiconnectivity

Multiconnectivity is a vital option in 5G New Radio (NR) systems allowing user equipment (UE) to maintain multiple links to nearby base stations (BS) improving service reliability. However, this functionality is very power-hungry prohibiting its application in practice. To alleviate this shortcoming discontinuous reception (DRX) mechanism can be utilized. The latter requires careful parameterization as it may drastically increase latency at the air interface. In this letter, we develop a mathematical model to characterize the trade-off between energy efficiency and latency in millimeter wave (mmWave) 5G NR systems under micromobility and blockage impairments. We then utilize it to determine the optimal type of DRX timers scaling. We show that micromobility has a positive impact on energy efficiency. For low micromobility speeds (<0.2°/s) proportional DRX scaling scheme with the scaling coefficient <inline-formula> <tex-math notation="LaTeX">$k < 1.0$ </tex-math></inline-formula>, provides the best performance in terms of considered metrics while for higher speeds it leads to a compromise between them. The optimal value of <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> depends on design preferences.
Stepwise inertial control of a wind turbine generator to minimize a second frequency dip

AbstractWind turbine generators (WTGs) in power systems with high wind penetration levels are encouraged or forced to participate in frequency control. A stepwise inertial control (SIC) scheme instantly increases WTG output to arrest the frequency drop for a preset period upon detecting a disturbance. After arresting the frequency drop, the output is rapidly reduced to recover the rotor speed. The reduction could cause a power deficit to the power system, which in turn results in a second frequency dip (SFD). This paper proposes an SIC scheme that can improve the frequency nadir (FN) and maximum rate of change of frequency (ROCOF) while minimizing an SFD. To achieve this, a reference function is separately defined prior to and after the FN. To improve the FN and maximum ROCOF, the output is instantly increased by adding a constant, which is proportional to the rotor speed, and maintaining it until the FN is reached. To minimize an SFD, the output is slowly reduced with the rotor speed. This reduction ensu.