Miracle-dz/UniFAR-FTUs huggingface dataset:
Supply Chain Pricing Strategy for Short-Lived Ramp-Type Demand Models

Natural hazards, such as estern Japan earthquake in 2011 and human-induced crises, such as the bankruptcy of Lehman Brothers in 2008, is harmful to global supply chain management. Therefore, a need exists to rethink the methodology for responding to crises. It is well known that the bullwhip effect due to order forecasting and demand fluctuations decrease supply chain efficiency. Compared to the conventional bullwhip effects, short-lived demand changes caused by unexpected natural disasters or a financial crisis can adversely affect supply chain performance. This work discusses the effects of four ramp-type demands using a novel supply chain cost model. Ramp-type demand increases within a short period can lead to profit loss; and consequently, an appropriate pricing strategy should be adopted. Based on price elasticity, demand types and their lifetimes, and supply chain parameters, the price premium can be determined to obtain the highest profit. Simulation results provide guidelines for supply chain managers dealing with demand fluctuations due to natural or human-induced crises.
Prophylaxis of microelementosis in rabbits using a mixture of glauconite, succinic, humic and fulvic acids and minerals

Impaired metabolism of mineral substances in the conditions of industrial rabbit breeding may cause decrease in increment of live mass, reduction of immunity, mass morbidity and death of animals. In our experiment, we studied the efficiency of using a mineral mixture to prevent the disorders in the metabolism of rabbits according to changes in morphologic, biochemical parameters and antioxidant status of blood, chemical composition of blood plasma and increments in body weight compared to the control group of animals. For the studies, we formed four groups of white New Zealand rabbits, each comprising six individuals aged 70 days with mean body weight equaling 1.99 kg. In group I, the rabbits received an aqueous form of a mixture of glauconite, succinic acid, humic and fulvic acids and lactates of zinc, manganese, cuprum, cobalt and iron with water, rabbits of group II were given a dry form of a mixture of glauconite, succinic acid, humic and fulvic acids and lactates of zinc, manganese, cuprum, cobalt and iron with fodder, and the rabbits of group III were intramuscularly injected with butanol fraction of humic acids. The experiment lasted for 21 days. The results of the experiment indicate that the most effective prophylaxis of malfunctions of mineral metabolism in white New Zealand rabbits aged 70–95 was dry mixture of glauconite, succinic acid, humic and fulvic acids and lactates of zinc, manganese, cuprum, cobalt and iron with fodder (group II), which was given once a day for 21-day period. We determined a positive effect of biologically active supplement on the parameters of hematopoiesis(1.25 times significantly higher level of hemoglobin and 1.14 times higher number of erythrocytes), metabolism of proteins (1.54 times significantly higher content of albumins), mineral substances (significantly higher content of inorganic phosphorus – by 1.17 times, calcium by 2.18 times, manganese by 1.39 times, zinc by 1.50 times, iron by 1.39 times and cuprum by 1.49 times), functional condition of the liver (2.04 times lower activity of gamma-glutamyltransferase), the state of the antioxidant system (lowest catalase activity) and energy of rabbits’ growth (1.20-fold increment in body weight). The results of our study indicate that using a dry form of the mixture of glauconite, succinic acid, humic and fulvic acids and lactates of zinc, manganese, cuprum, cobalt and iron with fodder is an efficient method of preventing malfunctioning of mineral metabolism in rabbits.
Suspension of soft magnetic materials using high TC superconductors

This paper describes a novel suspension technique using high Tc superconductors and magnetic materials. It was found for a field-cooled superconductor and an adjacent magnetic material that the usual inverse relationship between the attractive magnetic force and gap distance reverts to a direct relationship for small gap length. Thus, stable, noncontact suspension is possible within a certain gap range. This phenomenon was found for even a soft magnetic material possessing minimal coercive force. Since remarkable reversals were observed for magnetic materials with diameters much smaller than that of the pinned area, it is considered that some of the pinned flux is subject to a gathering effect in the magnetic material. Stable, contactless suspension of a 180 g carbon steel weight under a high Tc superconductor was achieved using this technique.
Epidemiology of EHV-1 and EHV-4 infections: A review

This review mainly focuses on the epidemiological characteristics of respiratory diseases, abortions, perinatal mortalities and neurological diseases in horses caused by EHV-1 and EHV-4. There are several sources of EHV-1 and EHV-4 which are transmitted by different routes. The latency and reactivation of EHV-1 and EHV-4 play an important role in the persistence of infection with these viruses in the equine population. These viruses are major agents in respiratory diseases in horses. Mares and their foals play an important role in the circulation of these viruses on farms. Abortion and perinatal mortality can take the sporadic or epizootic form. Neurological disease is caused primarily by neuropathogenic EHV-1. Combined epizootics of neurological diseases and abortions are common.
The Role of Anemia in Term and Preterm Pregnancies: Evidence from the Brazilian Multicenter Study on Preterm Birth (EMIP)

Camilla O. Figueira1, Helena M Gomide1, José P. Guida1, Tabata Z. Dias1, Giuliane J. Lajos1, Ricardo P. Tedesco2, Marcelo L. Nomura1, Patrícia M. Rehder1, José G. Cecatti1,3, Renato Passini Jr1, Fernanda G. Surita1, Maria Laura Costa1,3*, Brazilian Multicenter Study on Preterm Birth study group* 1Department of Obstetrics and Gynecology, University of Campinas, Campinas/SP, Brazil 2Department of Obstetrics and Gynecology, Jundiaí School of Medicine, Jundiaí, Brazil 3Centre for Studies in Reproductive Health of Campinas (CEMICAMP)
Classifying subclinical depression using EEG spectral and connectivity measures

Detecting depression on its early stages helps preventing the onset of severe depressive episodes. In this study, we propose an automatic classification pipeline to detect subclinical depression (i.e., dysphoria) through the electroencephalography (EEG) signal. To this aim, we recorded the EEG signals in resting condition from 26 female participants with dysphoria and 38 female controls. The EEG signals were processed to extract several spectral and functional connectivity features to feed a nonlinear Support Vector Machine (SVM) classifier embedded with a Recursive Feature Elimination (RFE) algorithm. Our recognition pipeline obtained a maximum classification accuracy of 83.91% in recognizing dysphoria patients with a combination of connectivity and spectral measures. Moreover, an accuracy of 76.11% was achieved with only the 4 most informative functional connections, suggesting a central role of cortical connectivity in the theta band for early depression recognition. The present study can facilitate the diagnosis of subclinical conditions of depression and may provide reliable indicators of depression for the clinical community.
Semi-parametric Identification of SVAR Models with Zero Lower Bound

The US federal funds rate was frequently constrained at zero after the Great Recession, and Federal Reserve has turned to unconventional monetary policy tools. This paper uses a model of structural vector autoregression with Zero Lower Bound (SVAR-ZLB) to characterize the censored nominal interest rate and the effect of unconventional monetary policy. The existing literature relies on the assumption of zero short-run effect of unconventional monetary policy to identify this model, but this paper examines point identification of this model without the assumption on unconventional monetary policy. First, in the case of classic Gaussian shocks, I explain the known result of no point identification from the new perspective of likelihood. However, in the case of empirically relevant non-Gaussian shocks, this paper proposes a generic semiparametric identification scheme to prove point identification, without relying on the parametric form of the shock distribution. An efficient Bayesian inference routine is designed to facilitate the model estimation in practice.
Bipolar Degradation of High Voltage 4H-SiC p-i-n Diodes in Pulse Regime

We report on specific features of forward voltage degradation of 4H-SiC p-i-n diodes in the pulse mode. It is shown that pulse stresses with a pulse duration shorter than several milliseconds cause substantially smaller forward voltage drift in comparison with a dc stress with the same charge passed through the diodes and the same distribution of injected carriers. A self-recovery of the forward voltage is observed at room temperature.
Profile inference revisited

Profile-guided optimization (PGO) is an important component in modern compilers. By allowing the compiler to leverage the program’s dynamic behavior, it can often generate substantially faster binaries. Sampling-based profiling is the state-of-the-art technique for collecting execution profiles in data-center environments. However, the lowered profile accuracy caused by sampling fully optimized binary often hurts the benefits of PGO; thus, an important problem is to overcome the inaccuracy in a profile after it is collected. In this paper we tackle the problem, which is also known as profile inference and profile rectification. We investigate the classical approach for profile inference, based on computing minimum-cost maximum flows in a control-flow graph, and develop an extended model capturing the desired properties of real-world profiles. Next we provide a solid theoretical foundation of the corresponding optimization problem by studying its algorithmic aspects. We then describe a new efficient algorithm for the problem along with its implementation in an open-source compiler. An extensive evaluation of the algorithm and existing profile inference techniques on a variety of applications, including Facebook production workloads and SPEC CPU benchmarks, indicates that the new method outperforms its competitors by significantly improving the accuracy of profile data and the performance of generated binaries.
BULLY-VICTIMIZATION, DEPRESSION, AND SCHOOL CONNECTEDNESS IN EARLY ADOLESCENT STUDENTS

ii Acknowledgements . iii List of Tables . viii List of Figures . ix List of Appendices . x Chapter One: Introduction . 1 Chapter Two: Literature Review . 6 Early Adolescence . 6 Biological Changes. 6 Cognitive Changes. 7 Social Changes. 7 Bullying . 8 Bully. 8 Victimization. 9 Bully-Victim. 10 Gender differences. 11 Depression . 12 Gender differences. 12 Bullying and depression. 13 School Connectedness . 16 vi School connectedness and depression. 18 School connectedness and bullying. 19 Summary . 22 Chapter Three: Statement of the Problem . 24 Hypothesis and Research Question . 28 Hypothesis. 28 Research Question. 29 Chapter Four: Methods . 30 Participants . 30 Instrumentation . 30 Bullying. 30 Depression. 34 School Connectedness. 35 Procedure . 36 Data Analyses . 37 Benefits and Potential Risks . 38 Chapter Five: Results . 40 Preliminary Analyses . 40 Primary Analyses . 40 Hypothesis. 40 Research Question. 45 Supplementary Analyses . 48 vii Exploratory mediation analysis by gender. 48 Exploratory mediation analysis by ethnicity. 49 Chapter Six: Discussion . 51 Primary Study Results . 51 Hypothesis. 51 Research Question. 53 Supplementary Analyses . 55 Exploratory mediation analysis by gender. 55 Exploratory mediation analysis by ethnicity. 55 Limitations . 56 Future Directions . 58 Conclusions . 62 References . 65
The Size of the Friction Coefficient Depending on the Size and Course of Normal Load

The coefficient of friction for the bronze material (CuZn25Al6) with inset graphite beds is investigated in the present paper. Friction coefficient was investigated experimentally by the testing machine Tribotestor`89 which uses the principle of the ring on ring method. Tribotestor`89 machine may be classed to the rotary tribometers. The tested sliding pairs were of the same material. The internal bushing performed a rotational movement with constant sliding speed (v = 0.8 m s-1). The external fixed bushing was exposed to the normal load, which was of different sizes and different variations. Process of load was increased from level 50 N to 200 N (400 N, 600 N) during run up 600 s, after the run up the appropriate level of load was held.The forth test had a rectangular shape of loading with direct current component 400 N and the amplitude 200 N period 600 s, the whole test took 1800 s. The obtained results reveal that friction coefficient decreases with the increase of normal load. Further, that the coefficient of friction was found smaller at constant load, as compared to rectangular shape of loading.
Attentional bias towards high and low caloric food on repeated visual food stimuli: An ERP study

Food variety influences appetitive behaviour, motivation to eat and energy intake. Research found that repeated exposure to varied food images increases the motivation towards food in adults and children. This study investigates the effects of repetition on the modulation of early and late components of event-related potentials (ERPs) when participants passively viewed the same food and non-food images repeatedly. The motivational attention to food and non-food images were assessed in frontal, centroparietal, parietooccipital and occipitotemporal areas of the brain. Participants showed increased late positive potential (late ERP component) to high caloric image in the occipitotemporal region compared to low caloric and non-food images. Similar effects could be seen in the early ERP component in the frontal region, but with reversed polarity. Data suggest that both the early and late ERP components show greater ERP amplitude when viewing high caloric images than low caloric and non-food images. Despite repeated exposure to same image, high caloric food continued to show sustained attention compared to low caloric and non-food image.
Assessing Transfer Entropy in cardiovascular and respiratory time series under long-range correlations

Heart Period (H) results from the activity of several coexisting control mechanisms, involving Systolic Arterial Pressure (S) and Respiration (R), which operate across multiple time scales encompassing not only short-term dynamics but also long-range correlations. In this work, multiscale representation of Transfer Entropy (TE) and of its decomposition in the network of these three interacting processes is obtained by extending the multivariate approach based on linear parametric VAR models to the Vector AutoRegressive Fractionally Integrated (VARFI) framework for Gaussian processes. This approach allows to dissect the different contributions to cardiac dynamics accounting for the simultaneous presence of short and long term dynamics. The proposed method is first tested on simulations of a benchmark VARFI model and then applied to experimental data consisting of H, S and R time series measured in healthy subjects monitored at rest and during mental and postural stress. The results reveal that the proposed method can highlight the dependence of the information transfer on the balance between short-term and long-range correlations in coupled dynamical systems.
Application of Revenue Management Practices in Star-Rated Hotels In Kenya

The study aimed to find the extent of applying revenue management (RM) practices in star-rated hotels in Kenya. Specifically, the study sought to determine RM policies and implementation, application of RM techniques, and the use of RM systems. The study used a quantitative approach and adopted a cross-sectional survey research design. The study targeted 225 revenue managers from all-star-rated hotels in Kenya. The findings revealed that RM is a practice in star-rated hotels, even though not in all hotels. Hotels reported having RM policy and implementation taking place. There was an adoption of RM techniques. A dynamic RM team and the presence of social media integration with RM were identified. The findings revealed that by large, starrated hotels interact with RM systems and sub-systems on the use of RM systems. Some hotels use either one or a combination of two systems. Furthermost, hotels were found to have automated their revenue collection. It was also revealed that they have adopted integrated RM soft-wares. The hotels were found to have meaningful RM data and information, RM pricing devices, and non-pricing devices. In comparison, information reveals a slightly above average presence of RM application in hotels in Kenya. The empirical evidence presented in this paper reveals that some hotels have not entrenched RM applications in terms of policies and implementation, RM tools and techniques, and their RM systems are lacking. The paper proposes that for full realization and maximization benefits associated with RM practices like predicting the growth of hotels, reducing operational costs, improving yields, and generating revenue, the industry should fully embrace RM applications.
Measurement of triglycerides concentration in human serum using near-infrared transmission spectroscopy and interval PLS

In order to measurement of Triglycerides in human serum with reagent-less using near-infrared (NIR) spectroscopy. Interval partial least square (iPLS) was proposed as an effective variable selection approach for multivariate calibration. For this purpose, an independent sample set was employed to evaluate the prediction ability of the resulting model. The spectrum was split into different interval. Then, the informative region of Triglycerides (1654-1746nm), in which the PLS model has a low RMSEP with 0.157mmol/L and a high R with 0.967, is selected with 18 intervals. The results show that the informative region of Triglycerides can be obtained by iPLS and applied to design the simpler reagent-less NIR instruments for inexpensive Triglycerides measurement in future.
Self-adaptive transmission scheme of integrated services over an IEEE 802.11 WLAN

A novel self-adaptive transmission scheme to support integrated data and voice transmission over an IEEE 802.11 WLAN is proposed. The simulation results show that the scheme can improve the data traffic performance and decrease efficiently the voice traffic delay jitter, and then increase the WLAN capacity. It is easy to realise as no change in the MAC protocol is required.
Lean implementation in Indian process industries – some empirical evidence

Purpose – In the present era of intense competition, industries are adopting lean manufacturing for successful survival. The concept of lean manufacturing is new for Indian process industries. The purpose of this paper is to investigate the status of lean manufacturing in Indian process industries in terms of lean practices, reasons and challenges of implementing lean manufacturing. Design/methodology/approach – A survey was carried out to assess the level of lean implementation in Indian process industries. Statistical tests were conducted to assess the significant lean practices, reasons and challenges of implementing lean in Indian process industries. Findings – It is observed that the level of implementation of lean manufacturing in Indian process industries is still low. Results indicate that Indian process industries those who have implemented lean found lean to be very useful to reduce wastes and to increase quality. Major lean practices being implemented by Indian process industries are primarily .
Early Detection of Parkinson’s Disease Using Center of Pressure Data and Machine Learning

Parkinson’s disease (PD) is a progressive neurodegenerative disorder resulting in abnormal body movements. Postural instability is one of the primary motor symptoms of PD and contributes to falls. Measurement of postural sway through center of pressure (COP) data might be an objective indicator of Parkinson’s disease. The goal of this work is to use machine learning to evaluate if different features of postural sway can differentiate PD patients from healthy controls. Time domain, frequency domain, time-frequency, and structural features were extracted from COP data collected from 19 PD patients and 13 healthy controls (HC). The calculated parameters were input to various machine-learning models to classify PD and HC. Random Forest outperformed the rest of the classifiers in terms of accuracy, false negative rate, F1-score, and precision. Time domain features had the best performance in differentiating PD from HC compared to other feature groups.
A framework for speech source localization using sensor arrays

Electronically steerable arrays of microphones have a variety of uses in speech data acquisition systems. Applications include teleconferencing, speech recognition and speaker identification, sound capture in adverse environments, and biomedical devices for the hearing impaired. An array of microphones has a number of advantages over a single-microphone system. It may be electronically aimed to provide a high-quality signal from a desired source location while simultaneously attenuating interfering talkers and ambient noise, does not necessitate local placement of transducers or encumber the talker with a hand-held or head-mounted microphone, and does not require physical movement to alter its direction of reception. Additionally, it has capabilities that a single microphone does not; namely automatic detection, localization, and tracking of active talkers in its receptive area. A fundamental requirement of sensor array systems is the ability to locate and track a speech source. An accurate fix on the primary talker, as well as knowledge of any interfering talkers or coherent noise sources, is necessary to effectively steer the array. Source location data may also be used for purposes other than beamforming; e.g. aiming a camera in a video-conferencing system. In addition to high accuracy, the location estimator must be capable of a high update rate as well as being computationally non-demanding in order to be useful for real-time tracking and beamforming applications. This thesis addresses the specific application of source localization algorithms for estimating the position of speech sources in a real room environment given limited computational resources. The theoretical foundations of a speech source localization system are presented. This includes the development of a source-sensor geometry for talkers and sensors in the near-field environment, the evaluation of several error criteria available to the problem, and the detailing of source detection and estimate-error prediction methods. Several practical algorithms necessary for real-time implementation are then developed, specifically the derivation and evaluation of an appropriate time-delay estimator and a novel closed-form locator. Finally, results obtained from several real systems are presented to illustrate the effectiveness of the proposed source localization techniques as well as to confirm the practicality of the theoretical models.