Miracle-dz/UniFAR-FTUs huggingface dataset:
Green Behavior: Factors Influencing Behavioral Intention and Actual Environmental Behavior of Employees in the Financial Service Sector

The financial sector is a key industry to invest in sustainable products and services, and to help other companies to make sustainable investments. So far, research sheds little light on environmental attitudes and the behavioral patterns of employees in this sector. We investigated what motivation and motivators promote or inhibit “green” behavior among professionals in the financial service industry. A smartphone friendly online survey concerning the intention to improve and show ‘green behavior’ was sent to 1200 professionals working in 17 locations in 13 European countries, 470 of which responded to the survey (39%). From these participants, 20% are convinced of the need to act in a “green” manner, and only 5% are hardly accessible. Monetary benefits combined with social motives contribute to sustainable living, whereas financial benefits alone actually hinder it. The result of this study points to an intention-behavior gap; intention is built from various influences including moderating factors like sex, age and family status influencing individual decisions. It is recommended that we should evaluate the green attitude and behavioral patterns of employees based on a practical typology of “green behavior”, which is suggested in this study, helping companies to know what actions can be taken to close the intention-behavior gap.
Error statistics for concatenated systems on non-renewal time-varying channels

— The statistics of the error process generated by a discrete super channel formed by the concatenation of a constrained encoder, a non-renewal ﬁnite state channel (FSC), and a constrained decoder is studied in this paper. First, recursions are developed for the error weight distribution. This statistics is relevant to the design of coding schemes and interleaving in concatenated systems. We also study the renewal nature of the residual error process as modiﬁed by the constrained decoder. Ferreira et al. conjectured that if the channel model is a renewal FSC, the super channel can be modeled as a similar renewal model. We use a statistics called the multigap distribution to analytically disprove this hypothesis. Furthermore, the eﬀect of interleaving is investigated from a new perspective using the variance of the multigap distribution.
Variable Selection and Function Estimation in Additive Nonparametric Regression Using a Data-Based Prior

Abstract A hierarchical Bayesian approach is proposed for variable selection and function estimation in additive nonparametric Gaussian regression models and additive nonparametric binary regression models. The prior for each component function is an integrated Wiener process resulting in a posterior mean estimate that is a cubic smoothing spline. Each of the explanatory variables is allowed to be in or out of the model, and the regression functions are estimated by model averaging. To allow variable selection and model averaging, data-based priors are used for the smoothing parameter and the slope at 0 of each component function. A two-step Markov chain Monte Carlo method is used to efficiently obtain the data-based prior and to carry out variable selection and function estimation. It is shown by simulation that significant improvements in the function estimators can be obtained over an approach that estimates all the unknown functions simultaneously. The methodology is illustrated for a binary regressio.
HIGH RESOLUTION SEARCH FOR DARK MATTER AXIONS IN MILKY WAY HALO SUBSTRUCTURE

The axion is one of the leading particle candidates for the universe’s dark matter component. Despite possessing very small couplings, the axion’s interaction with photons can be utilized to search for it using a microwave cavity detector. The Axion Dark Matter eXperiment (ADMX) uses such a detector to search for axions in our galactic halo. ADMX has recently added a new, high resolution channel to search for axions in discrete flows. ADMX’s medium resolution channel searches for axions in the thermalized component of the halo. We review the motivation for the axion and its properties which make it a good dark matter candidate. We also review the arguments for the existence of discrete flows in galactic halos. A flow of discrete axions with small velocity dispersion will appear as a very narrow peak in the output of a microwave cavity detector. A high resolution search can detect such a peak with large signal to noise. We have performed such a search. The details of the high resolution axion search and analysis procedure are presented. In this search, no axion signal was found in the mass range 1.98–2.17 μ eV. We place upper limits on the density of axions in local discrete flows based on this result.
The Big Sort: Why the Clustering of Like-Minded America Is Tearing Us Apart

Have free times? Read the big sort why the clustering of like minded american is tearing us apart writer by Why? A best seller publication worldwide with excellent value and content is combined with fascinating words. Where? Just here, in this site you can check out online. Want download? Naturally offered, download them also right here. Readily available files are as word, ppt, txt, kindle, pdf, rar, and also zip.
The challenge of participatory restoration in rural areas

Restoration is a prominent field of research and of restoration projects that seek to recover degraded and dysfunctional ecosystems and the services they provide. Humanity’s environmental crisis has increased awareness of the urgent need to conserve ecosystems and their biodiversity. Many countries and international organizations have set ambitious plans and restoration targets. This paper emphasizes on current themes such as landscape restoration, invasive species, novel ecosystems, and the necessary involvement of local communities in ecological restoration. It is focused mainly on tropical forest ecosystems. Another aim of this paper is a review of the results obtained in diverse restoration practices that concentrate on inducing secondary succession processes in tropical forests. It draws heavily on case studies from Mexico. Members of society should play an active role in restoration planning and implementation. Social participation is central to the success and sustainability of restoration projects. Traditional ecological knowledge is essential in many projects, and there should be careful consideration of the ethics involved. In the coming years, we will probably see a surge in the unassisted revegetation and reforestation of many abandoned rural areas making the understanding and managing of these restoration processes necessary and crucial. Finally, a set of guidelines that view restoration as a long-term social and ecological process is given.
The magnetocaloric effect at a first order phase transition

The magnetocaloric effect (MCE) can be defined as the isothermal entropy change (or adiabatic temperature change) of a material upon application/removal of an external magnetic field and is the key physics for a magnetic cooling device. A discontinuity of entropy at a first order phase transition (FOPT) allows for a large entropy change to be induced by a relatively small field. However, a hysteresis is necessarily associated with a FOPT. The effects of hysteresis, as measured in a sensitive microcalorimeter, are the focus of the thesis. The calorimetric setup used is unique in allowing a separate measurement of heat capacity and latent heat and thereby the possibility to clearly distinguish the first and higher order contributions to MCE. Due to the high measurement fidelity required, the experimental chapter is a core component of the thesis and includes a thorough analysis of the measurement errors associated with the microcalorimeter. Several improvements are proposed to improve precision and accuracy of the measurement in future studies. The first of the hysteresis effects is a spurious ‘colossal’ MCE. Its indirect observation was claimed in 2004 from magnetisation measurements analysed using a Maxwell relation and was widely disputed thereafter. It was shown that a different measurement protocol leads to non ‘colossal’ MCE. This thesis investigates whether the ‘colossal’ MCE can be achieved by a particular magnetisation history by reproducing the original measurement protocol in a more direct calorimetric measurement. It is shown that the ‘colossal’ MCE is just an artefact of the use of Maxwell relation in a non-equilibrium process. The final chapter discusses a second effect of hysteresis: a subtle difference between the indirect and calorimetric measurements of MCE that can be clearly observed when comparing measurements on field application and removal. Maxwell relation leads to an artefact related to temperature dependence of the hysteresis. In the calorimetric measurement the dissipation of magnetic work in a hysteretic magnetisation cycle is observed. DECLARATION OF ORIGINALITY I hereby declare that the work presented here is entirely my own. Where I have incorporated the work of others it has been acknowledged and referenced appropriately. Milan Bratko September 2013 COPYRIGHT DECLARATION The copyright of this thesis rests with the author and is made available under a Creative Commons Attribution Non-Commercial No Derivatives licence. Researchers are free to copy, distribute or transmit the thesis on the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any reuse or redistribution, researchers must make clear to others the licence terms of this work.
Indirect $\boldsymbol{CP}$ Violation in $\boldsymbol{D^0 \rightarrow h^+ h^-}$ Decays at LHCb

Indirect CP violation in the $D^0$ system can be probed by measuring the parameter $A_{\Gamma}$, defined as the CP asymmetry of the effective lifetime of the $D^0$ meson decaying to a CP eigenstate. This can be significantly enhanced beyond Standard Model predictions by new physics. Measurements of $A_{\Gamma}$ using $D^0 \rightarrow K^+K^-$ and $D^0\rightarrow \pi^+\pi^-$ decays reconstructed from pp collisions collected by the LHCb experiment, corresponding to an integrated luminosity of 1.0 fb$^{-1}$, are presented. The results are \begin{align*} A_{\Gamma} (\pi\pi) = (+0.33 \pm 1.06 \pm 0.14) \times 10^{-3},\quad A_{\Gamma} (KK) = (-0.35 \pm 0.62 \pm 0.12) \times 10^{-3}, \end{align*} where the uncertainties are statistical and systematic, respectively. These are the most precise measurements of their kind to date, and show no evidence of CP violation.
The construction of meanings in and for : a stochastic domain of abstraction.

This study takes as its focus young children's intuitive knowledge of randomness. Previous work in this field has studied the misconceptions that people, especially adults, hold in making judgements of chance (see, for example, the work of Kahneman & Tversky and Konold). In contrast, I study how primitive meaningsf or randomnessfo rm a basis for new meanings,a processw hich the misconceptionsa pproachf ails to illuminate. The guiding principle for this study is that the observation of students' evolving thought in a carefully designedc omputer-basedd omain will provide a betteru nderstanding of how the specific features of the domain shape and are shaped by activities within it. There are, then, two deeply connected strands to this thesis: the study of children's evolving meanings for randomness as expressed in a computer-based microworld, and the articulation of design principles which encapsulate pedagogic meaningsfor that microworld. More specifically, the thesis aims to shed light upon the answers to four crucial questions: Meanings for the domain: What do formalisms of stochastic behaviour look like in a domain of abstraction? What structures in the domain for stochastic abstraction optimise the articulation of intuitions and the construction of new meanings? Meanings in the domain: What articulations of informal intuitions of stochastic behaviour do we observe? How do the structures of the domain support the forging of situated meanings? The study uses an iterative design methodology, which cycles between the design of computer-based tools and the observ4tion of children, between the ages of 9 and II years, as they use these tools. The thesis identifies initial meanings for the behaviour of various stochastic phenomena and traces how new pieces of knowledge, especially relating to long term random behaviour, emerge through the forging of connections between the internal and external resources.
The effect of nursing care satisfaction on pain and anxiety levels of patients undergoing orthopedic surgery in the early postoperative period

In our study, we aimed to examine the effect of nursing care satisfaction on the pain and anxiety levels of patients who underwent orthopedic surgery. This descriptive study was conducted with the participation of patients who underwent surgery in the orthopedic clinic of a training and research hospital, and they were in the early postoperative period. Patient information form, Newcastle Satisfaction with Nursing Scale and State-Trait Anxiety Inventory were used in data collection. In this study, we found that 41.2% of the orthopedic patients were between the ages of 36 and 50, and 60.4% of them were women. Both nursing care satisfaction and anxiety levels were found to be higher in women than men (p<0.05). The highest satisfaction rate was found among patients aged 18-35 years old, and the highest anxiety level was found in patients over the age of 66. In our study, we found that higher anxiety levels increased pain intensity, and a high level of nursing care satisfaction could be seen in various pain and anxiety levels. Our study showed that nursing care satisfaction was affected by pain and anxiety in patients who underwent orthopedic surgery. In addition, it showed that pain and anxiety trigger each other. Clinicians should be aware of the negative effects of pain and anxiety on postoperative recovery. Strategies to increase nursing care satisfaction should be developed.
Antimicrobial Step-Down Therapy versus Conventional Antimicrobial Therapy in the Treatment of Patients with Sepsis

Objective This study was to evaluate the efficacy of antimicrobial step-down therapy versus conventional antimicrobial therapy in the treatment of patients with sepsis. Methods Between September 2020 and September 2021, 65 patients with sepsis treated in the intensive care unit (ICU) of our hospital were recruited and assigned at a ratio of 1 : 1 to receive either conventional antimicrobial therapy (sulbactam plus cefoperazone) (control group) or antimicrobial step-down therapy (imipenem/cilastatin) (observation group). The results of drug sensitivity tests and clinical effects were evaluated comprehensively after 3-5 d of treatment, downgraded, and upgraded, or maintenance treatment was administered for 10 d. Outcome measures included clinical and laboratory indices and treatment efficacy. Results Antimicrobial step-down therapy resulted in a significantly higher efficacy and lower levels of white blood cell (WBC) count and C-reactive protein (CRP) versus conventional antimicrobial therapy (P < 0.05). The patients given antimicrobial step-down therapy showed a significantly shorter duration of antimicrobial drug administration, temperature recovery, time of respiratory support, and ICU stays versus conventional antimicrobial therapy (P < 0.05). Conclusion Antimicrobial step-down therapy contributes to the mitigation of inflammatory responses in patients with sepsis and shortens the duration of antimicrobial drug use and ICU stay versus conventional antimicrobial therapy. The reliability of the conclusions can be further increased if multicenter and large sample clinical observations can be conducted, which is the direction of endeavor for future clinical studies.
Robust Coordinated Optimization With Adaptive Uncertainty Set for a Multi-Energy Microgrid

With the increasing integration of the multi-energy microgrid (MEM) with the distribution network (DN), the distributed coordination between MEM and DN becomes critical. This paper proposes a distributed scheduling method for the coupled MEM-DN under operational uncertainties. First, a worst-expectation min-max-max-min robust optimization model is formulated for MEM considering the uncertainties of renewable distributed generation (wind and photovoltaic) as well as its class probability. Second, the column and constraint generation algorithm with an alternating iteration strategy (C&CG-AIS) is proposed to accelerate the solution by decoupling the subproblems. Third, the multi-interval convex hull uncertainty set (MCHUS) is proposed to reduce the conservatism of robust optimization by decreasing the low-probability scenarios. Furthermore, the Bregman alternating direction method with multipliers (BADMM) is combined with the alternating optimization procedure (AOP) to overcome the convergence difficulty in the nonconvex distributed MEM-DN model. Finally, the effectiveness of the proposed model and method is verified by simulation tests based on IEEE-33 node DN and a park-level MEM.
Characterizing HfO2-Based Ferroelectric Tunnel Junction in Cryogenic Temperature

Since the discovery of ferroelectric properties in doped HfO2, various types of memory devices have emerged based on this novel material. Especially, the ferroelectric tunnel junction (FTJ) has gained considerable attention for selector-less crossbar array. Although various studies have been carried out for the HfO2-based FTJs, there are no investigations of them at a cryogenic temperature. While cryogenic memories are getting increasing attentions for diverse applications from high-performance computing to aerospace electronics, exploring the FTJ at cryogenic temperature is particularly interesting because it has been known for relatively poor retention characteristics and endurance at room temperature (RT). For the first time, we characterize the HfO2-based FTJ at cryogenic temperature down to 77 K. It was found that both the retention and endurance characteristics become greatly improved at 77 K. Furthermore, the read voltage was found to be critical for optimized performance in terms of ON-current, OFF-current, and their ratio at 77 K.
An Application of IoT in a Drone Inspection Service for Environmental Control

This paper presents an exploratory activity with a drone inspection service for environmental control. The aim of the service is to provide technical support to decision-makers in environmental risk management. The proposed service uses IoT for the interaction between a mobile application, a Smart City platform, and an Unmanned Aircraft System (UAS). The mobile application allows the users to report risky situations, such as fire ignition, spills of pollutants in water, or illegal dumping; the user has only to specify the class of the event, while the geographical coordinates are automatically taken from device-integrated GPS. The message sent from the mobile application arrives to a Smart City platform, which shows all the received alerts on a 3D satellite map, to support decision-makers in choosing where a drone inspection is required. From the Smart City platform, the message is sent to the drone service operator; a CSV file defining the itinerary of the drone is automatically built and shown through the platform; the drone starts the mission providing a video, which is used by the decision-makers to understand whether the situation calls for immediate action. An experimental activity in an open field was carried out to validate the whole chain, from the alert to the drone mission, enriched by a Smart City platform to enable a decision-maker to better manage the situation.
Shifts of Antibiotic Resistomes in Soil Following Amendments of Antibiotics-Contained Dairy Manure

Dairy manure is a nutrition source for cropland soils and also simultaneously serves as a contamination source of antibiotic resistance genes (ARGs). In this study, five classes of antibiotics including aminoglycosides, beta-lactams, macrolides, sulfonamides, and tetracyclines, were spiked in dairy manure and incubated with soil for 60 days. The high throughput qPCR and 16S rRNA amplicon sequencing were used to detect temporal shifts of the soil antibiotic resistomes and bacterial community. Results indicated dairy manure application increased the ARG abundance by 0.5–3.7 times and subtype numbers by 2.7–3.7 times and changed the microbial community structure in soils. These effects were limited to the early incubation stage. Selection pressure was observed after the addition of sulfonamides. Bacterial communities played an important role in the shifts of ARG profiles and accounted for 44.9% of the resistome variation. The incubation period, but not the different antibiotic treatments, has a strong impact on the bacteria community. Firmicutes and Bacteroidetes were the dominant bacterial hosts for individual ARGs. This study advanced our understanding of the effect of dairy manure and antibiotics on the antibiotic resistome in soils and provided a reference for controlling ARG dissemination from dairy farms to the environment.
SubTTD: DOA Estimation via Sub-Nyquist Tensor Train Decomposition

Conventional tensor direction-of-arrival (DOA) estimation methods for sparse arrays apply canonical polyadic decomposition (CPD) to the high-order coarray covariance tensor for retrieving angle information. However, due to the low convergence rate of CPD-based algorithms for high-order tensors, these methods suffer from a high computation cost. To address this issue, a sub-Nyquist tensor train decomposition (SubTTD)-based DOA estimation method is proposed for a three-dimensional (3-D) sparse array, where an augmented virtual array is derived from the sub-Nyquist tensor statistics. To reduce computational complexity of processing the 6-D coarray covariance tensor, the proposed SubTTD model efficiently decomposes it into a train of head matrix, 3-D core tensors, and tail matrix. Based on that, a core tensor decomposition and a change-of-basis transformation for the head matrix are designed to retrieve canonical polyadic factors of the coarray covariance tensor for DOA estimation. The computational efficiency of the proposed method is theoretically analyzed, and its effectiveness is verified via simulations.
In-Flight Energy-Driven Composition of Drone Swarm Services

We propose a novel framework for swarm-based drone delivery services with in-flight energy recharging. The framework aims to enhance the delivery time of multiple packages by reducing the number of stops and recharging times at intermediate stations. The proposed framework considers various intrinsic and extrinsic delivery constraints. We propose to use support drones whose sole purpose is to recharge other drones in the swarm during their flight. In this respect, we compute the optimal set of optimal support drones to minimize the probability of delivery services and recharging time at the next stations. We also use two settings to position the support drones in a flight formation for comparative purposes. Two novel energy sharing methods are proposed, namely, Priority-based and Fairness-based methods. A re-ordering method of the delivery drones is presented to facilitate the in-flight energy composition process. An enhanced A* algorithm is implemented to compose the optimal services in terms of delivery time. Experimental results prove the efficiency of our proposed approach.