Exploring the role of iron in Fe_(5)Ni_(4)S_(8)toward oxygen evolution through modulation of electronic orbital occupancy

Ni-Fe-based catalysts are considered to be among the most active catalysts for the oxygen evolution reaction(OER)under alkaline conditions,with Fe playing a crucial role.However,Fe leaching occurs during the reaction due to thermodynamic instability,which has resulted in conflicting reports within the literature regarding its role.To clarify this point,we propose a strategy consisting of modulating the electronic orbital occupancy to suppress the extensive loss of Fe atoms during the OER process.Theoretical calculations,in-situ X-ray photoelectron spectroscopy,molecular dynamics simulations,and a series of characterization showed that the stable presence of Fe not only accelerates the electron transfer process but also optimizes the reaction barriers of the oxygen evolution intermediates,promoting the phase transition of Fe_(5)Ni_(4)S_(8)to highly active catalytic species.The modulated Fe_(5)Ni_(4)S_(8)-based pre-catalysts exhibit improved OER activity and long-term durability.This study provides a novel perspective for understanding the role of Fe in the OER process.

Modulating Pd e_(g) orbital occupancy in Pd-Au metallic aerogels for efficient carbon dioxide reduction

The electronic structure of electrocatalysts plays a critical role in energy conversion,whereas for an efficient catalyst,it is challenging to modulate the orbitals.Herein,we present a new strategy to modulate the e_(g) orbital occupancy of Pd by constructing composition-controllable Pd-Au metallic aerogels(MAs),optimizing the d-band center of Pd to achieve excellent performance for electrochemical carbon dioxide reduction reaction(CO_(2)RR).Specifically,Pd_(1)Au_(2) MAs achieve almost 100% Faraday efficiency(FE) of CO in the range of-0.40 to-0.80 V vs.reversible hydrogen electrode(RHE),as well as the long-term stability,being one of the best Pd-based materials for CO_(2)RR.The X-ray photoelectron spectroscopy(XPS) results and density functional theory(DFT) calculations demonstrate that the introduction of Au modulates the Pd e_(g) orbital occupancy,which significantly weakens *CO adsorption on Pd,reduces the CO_(2)RR energy barrier and consequently improves the electrocatalytic activity and stability for long-term applications.Our work highlights a new strategy for designing efficient electrocatalysts for CO_(2)RR and beyond.

One-dimensional lazy quantum walks and occupancy rate

In this paper, we discuss the properties of lazy quantum walks. Our analysis shows that the lazy quantum walks have O（tn） order of the n-th moment of the corresponding probability distribution, which is the same as that for normal quantum walks. The lazy quantum walk with a discrete Fourier transform （DFT） coin operator has a similar probability distribution concentrated interval to that of the normal Hadamard quantum walk. Most importantly, we introduce the concepts of occupancy number and occupancy rate to measure the extent to which the walk has a （relatively） high probability at every position in its range. We conclude that the lazy quantum walks have a higher occupancy rate than other walks such as normal quantum walks, classical walks, and lazy classical walks.

Experimental characterization of guest molecular occupancy in clathrate hydrate cages: A review

Study on the microscopic structure of clathrate hydrate has made significant progress in the past decades.This review aims to summarize the state of the art of the experimental characterization of guest molecular occupancy in clathrate hydrate cages,which is an important area of the microscopic structures.The characterizing method and features of different guest molecular,such as hydrocarbon,carbon dioxide,hydrogen and inhibitor/promoter,in different hydrate cages have been extensively reviewed.A comprehensive use of advanced technologies such as X-ray diffraction,Raman spectroscopy and nuclear magnetic resonance may provide better understanding on the compositions and microscopic mechanisms of clathrate hydrate.

PET imaging for receptor occupancy: meditations on calculation and simplification

This invited mini-review briefly summarizes procedures and challenges of measuring receptor occupancy with positron emission tomography. Instead of describing the detailed analytic procedures of in vivo ligand-receptor imaging, the authors provide a pragmatic alJproach, along with personal perspectives, for conducting positron emission tomography imaging for receptor occupancy, and systematically elucidate the mathematics of receptor occupancy calculations in practical ways that can be understood with elementary algebra. The authors also share insights regarding positron emission tomography imaging for receptor occupancy to facilitate applications for the development of drugs targeting receptors in the central nervous system.

Evaluating Traffic Congestion Using the Traffic Occupancy and Speed Distribution Relationship: An Application of Bayesian Dirichlet Process Mixtures of Generalized Linear Model

Accurate classification and prediction of future traffic conditions are essential for developing effective strategies for congestion mitigation on the highway systems. Speed distribution is one of the traffic stream parameters, which has been used to quantify the traffic conditions. Previous studies have shown that multi-modal probability distribution of speeds gives excellent results when simultaneously evaluating congested and free-flow traffic conditions. However, most of these previous analytical studies do not incorporate the influencing factors in characterizing these conditions. This study evaluates the impact of traffic occupancy on the multi-state speed distribution using the Bayesian Dirichlet Process Mixtures of Generalized Linear Models (DPM-GLM). Further, the study estimates the speed cut-point values of traffic states, which separate them into homogeneous groups using Bayesian change-point detection (BCD) technique. The study used 2015 archived one-year traffic data collected on Florida’s Interstate 295 freeway corridor. Information criteria results revealed three traffic states, which were identified as free-flow, transitional flow condition (congestion onset/offset), and the congested condition. The findings of the DPM-GLM indicated that in all estimated states, the traffic speed decreases when traffic occupancy increases. Comparison of the influence of traffic occupancy between traffic states showed that traffic occupancy has more impact on the free-flow and the congested state than on the transitional flow condition. With respect to estimating the threshold speed value, the results of the BCD model revealed promising findings in characterizing levels of traffic congestion.

Spectrum Occupancy Measurement and Analysis

This paper analyzes current spectrum utilization from all aspects based on related methods of spectrum measurement. The measurement results show that some spectrum resources are not used effectively due to current fixed spectrum allocation policy, and the spectrum occupancy varies dramatically in terms of time and space. These results provide basis for the development of next generation wireless communication technologies such as Cognitive Radio (CR).

Dopant Occupancy in MgO-Codoped Lithium Niobate Crystals

On the basis of the bond valence model, the preferential occupancy of various dopant such as Mn2+, Eu3+, Er3+, Nd3+, Lu3+, Yb3+, In3+, Cr3+, Fe3+ and Ti4+ in the ideal stoichiometric lithium niobate (SLN) crystallographic frame was investigated in a viewpoint of chemical bonds. Theoretical analysis indicates that the dopant occupancy is significantly influenced by the anti-site Nb4+Li. Our work also shows that Mg-like ions (Mg2+, Zn2+, In3+, Sc3+) have a repulsive effect on Nb4+Li ions. When removing Nb4+Li ion by codoping Mg-like ions, the dopant occupancy in the LN crystallographic frame is determined by the natural characteristics of dopant, which is consistent well with the result in the ideal SLN crystals.

Effects of historic wildfire and prescribed fire on site occupancy of bats in Shenandoah National Park,Virginia,USA

Given the likelihood of regional extirpation of several once-common bat species in eastern North America from white-nose syndrome,it is critical that the impacts of forest management activities,such as prescribed fire,are known in order to minimize potentially additive negative effects on bat populations.Historic wildfires may offer a suitable surrogate to assess long-term burn impacts on bats for planning,implementing and assessing burn programs.To examine the effects of historic fire on bats,we sampled bat activities at 24 transect locations in burned and unburned forest stands in the central Appalachian Mountains of Shenandoah National Park(SNP),Virginia,USA.There was limited evidence of positive fire effects over time on hoary bats(Lasiurus cinereus Beauvois)and big brown bats(Eptesicus fuscus Beauvois)occupancy.Overall,there were few or mostly equivocal relationships of bat occupancy relative to burn conditions or time since fire in SNP across species using a false-positive occupancy approach.Our results suggest that fire does not strongly affect bat site occupancy short-or long-term in the central Appalachians.

Aluminum Ion Occupancy in the Structure of Synthetic Saponites

Saponite has been widely used in a number of industrial fields because of the higher surface acidity and thermal stability when compared with other clay minerals (Alexander and Dubois, 2000; Casagrande et al., 2005). Due to its limited natural resource, synthesis of saponite has attracted much attention during the last two decades (Vogels et al., 2005; Bisio et al., 2008). The main aim of this study is to investigate occupancy of Al ions and its effect on the structure of synthetic saponites.

Handover Traffic Model and Channel Occupancy Time in LEO Satellite Networks

This paper presents a method of determining handover traffic and mean channel occu-pancy time of a traffic model for the LEO(Low Earth Orbit)satellite networks.The mainideas are that the handover traffic is mainly due to the movement of the satellite and that thevelocity of the mobile terminals and earth rotation are ignored.The performance level can becalculated according to different handover queuing models.

Utilizing Occupancy Models and Platforms-of-Opportunity to Assess Area Use of Mother-Calf Humpback Whales

The Hawaiian Islands, and particularly the Maui 4-island region, are a critical breeding and calving habitat for humpback whales (Megaptera novaeangliae) belonging to the Hawaii distinct population segment. Our aims were to test the use of platforms-of-opportunity to determine trends in mother-calf pod use of the region and to present opportunistic platforms as an alternative method of long-term, cross-seasonal monitoring. Data were collected from whale watching vessels over a 4-year period and analyzed using occupancy models to determine the probability of habitat use of pods with calves and pods without calves within the study area. Detection probability was influenced by survey effort and month for all pod types with detection of adult only pods further influenced by year. Pods with a calf showed a preference for shallow (<100 meters) low latitude waters (<20.7°N), while pods without a calf preferred deeper waters (>75 meters). Results presented here align with previous work, both in Hawaii and in other breeding grounds, which show a distinct segregation of mothers with a calf from other age-classes of humpback whales. The need for long-term continuous monitoring of cetacean populations is crucial to ensure species conservation. Data collected aboard platforms-of-opportunity, as presented here, provide important insight on humpback whale spatial and temporal distribution, which are essential for species protection and management.

Buffer Occupancy of Double-Buffer Traffic Shaper in Real-Time Multimedia Applications across Slow-Speed Links

In this paper, a double-buffer traffic shaper was investigated to adjust video frame rate inflow into the TCP sender-buffer of a multimedia application source across a slow-speed link. In order to guarantee QoS across a slow-speed link (i.e. 1 MBPS), the double-buffer traffic shaper was developed. In this paper, the buffer size dynamics of double-buffer was investigated. The arrival and departure of frames were modeled as a stochastic process. The transition matrix for the process was generated and the stationary probability computed. A simulation program was written in Matlab 7.0 to monitor the buffer fullness of the second buffer when a 3600 seconds H.263 encoder trace data was used as test data. In the second buffer, it was discovered that over 90% of the play-time, the buffer occupancy was upper bounded at 300 frames per second and utilization maintained below 30%.

Occupancy Factor Model for Exposure to Natural Radionuclides along the Coastline of Erongo Region, Namibia

In this study, an occupancy factor model was developed and used to calculate the average time spent for outdoor and indoor activities along the coastline of the Erongo region of Namibia. A closed ended questionnaire was developed and administered to 800 respondents who visited the coastline for leisure, occupational and other activities. The mean time allocated for leisure activities ranges from 13.00 to 1.00 h, occupational mean time between 10.18 to 9.06 h and the values of other activities range from 16.66 to 11.00 h. The average computed time spent outdoor was found to be 11.46 h and indoor calculated to be 12.54 h. This shows an outdoor factor of 0.48 and indoor factor of 0.52 respectively. From the results obtained, the value of the absorbed dose rate ranged from 93.27 to 105.95 nGy·hǃ and the annual effective dose rate ranged from 121.01 to 176.61 μSv·yǃ (UNSCEAR factor) and 292.60 to 413.63 μSv·yǃ (present factor). The values obtained for annual effective dose are higher than the acceptable limit. However, from this study, we can conclude that the use of the UNSCEAR outdoor factor in the coastline will lead to underestimation of effective dose by 24% based on the present factor.

Efficient ammonia production over e_(g)-occupancy-optimized perovskite electrocatalysts

Renewable-energy-driven nitrate(NO_(3)^(−))electroreduction to ammonia(NH_(3))(NERA)has been an attractive technology for decarbonizing NH_(3)production and wastewater treatment.Improving NERA efficiency requires electrocatalysts that are earth-abundant and show fantastic performance.Here we report a semiempirical activity descriptor of eg occupancy(of surface B-site cations)for identifying inexpensive perovskite oxides with extremely high efficacy toward NERA.We establish the descriptor by systematic investigations of more than 10 perovskite oxides.These investigations demonstrate that their intrinsic NERA activities display a volcano-shaped dependence on eg occupancy and the optimized intrinsic activities are accessible at near-1 eg occupancies.This could plausibly be attributed to the favorable overlaps between surface adsorbates and vertically-oriented eg orbitals.More importantly,utilizing this descriptor,we predict a highly active,selective,and durable NERA electrocatalyst with a composition of Ba_(0.5)Sr_(0.5)Co_(0.8)Fe_(0.2)O_(3−δ)(BSCF).Because of its close-to-1 e_(g)occupancy(i.e.~1.2),the BSCF features a superior NH_(3)production rate of 0.12 g·h^(−1)·mg_(cat.)^(−1)(Faradaic efficiency of 97.8%)that is at top of the volcano plot,and substantially outperforms most NERA electrocatalysts reported in literature.

Short-term prediction of on-street parking occupancy using multivariate variable based on deep learning

Short-term prediction of on-street parking occupancy is essential to the ITS system,which can guide drivers in finding vacant parking spaces.And the spatial dependencies and exogenous dependencies need to be considered simultaneously,which makes short-term prediction of on-street parking occupancy challenging.Therefore,this paper proposes a deep learning model for predicting block-level parking occupancy.First,the importance of multiple points of interest(POI)in different buffers is sorted by Boruta,used for feature selection.The results show that different types of POI data should consider different buffer radii.Then based on the real on-street parking data,long short-term memory(LSTM)that can address the time dependencies is applied to predict the parking occupancy.The results demonstrate that LSTM considering POI data after Boruta selection(LSTM(+BORUTA))outperforms other baseline methods,including LSTM,with an average testing MAPE of 11.78%.The selection process of POI data helps LSTM reduce training time and slightly improve the prediction performance,which indicates that complex correlations among the same type of POI data in different buffer zones will also affect the prediction accuracy of LSTM.When there are more restaurants on both sides of the street,the prediction performance of LSTM(+BORUTA)is significantly better than that of LSTM.

Occupancy-aided ventilation for airborne infection risk control:Continuously or intermittently reduced occupancies?

Ventilation is an important engineering measure to control the airborne infection risk of acute respiratory diseases,e.g.,Corona Virus Disease 2019(COVID-19).Occupancy-aided ventilation methods can effectively improve the airborne infection risk control performance with a sacrifice of decreasing working productivity because of the reduced occupancy.This study evaluates the effectiveness of two occupancy-aided ventilation methods,i.e.,the continuously reduced occupancy method and the intermittently reduced occupancy method.The continuously reduced occupancy method is determined by the steady equation of the mass conservation law of the indoor contaminant,and the intermittently reduced occupancy method is determined by a genetic algorithm-based optimization.A two-scenarios-based evaluation framework is developed,i.e.,one with targeted airborne infection risk control performance(indicated by the mean rebreathed fraction)and the other with targeted working productivity(indicated by the accumulated occupancy).The results show that the improvement in the airborne infection risk control performance linearly and quadratically increases with the reduction in the working productivity for the continuously reduced occupancy method and the intermittently reduced occupancy method respectively.At a given targeted airborne infection risk control performance,the intermittently reduced occupancy method outperforms the continuously reduced occupancy method by improving the working productivity by up to 92%.At a given targeted working productivity,the intermittently reduced occupancy method outperforms the continuously reduced occupancy method by improving the airborne infection risk control performance by up to 38%.

Modelling method of inter-building movement for campus-scale occupancy simulation:A case study

As an important factor in the investigation of building energy consumption,occupant behavior(OB)has been widely studied on the building level.However so far,studies of OB modelling on the district scale remain limited.Indeed,district-scale OB modelling has been facing the challenges from the scarcity of district-scale data,modelling methods,as well as simulation application.This study initiates the extrapolation of occupancy modelling methodology from building level to district scale through proposing modelling methods of inter-building movements.The proposed modelling methods utilize multiple distribution fittings and Bayesian network to upscale the event description methods from inter-zone movement events at the building level to inter-building movement events at the district level.This study provides a framework on the application of the proposed modelling methods for a university campus in the suburbs of Shanghai,taking advantages of data sensing,monitoring and survey techniques.With the collected campus-scale occupancy data,this paper defines five patterns of inter-building movement.One pattern represents the dominated inter-building movement events for one kind of students in their daily campus life.Based on the quantitative descriptions for various inter-building movement events,this study performs the stochastic simulation for the campus district,using Markov chain models.The simulation results are then validated with the campus-scale occupancy measurement data.Furthermore,the impact of inter-building movement modelling methods on building energy demand is evaluated for the library building,taking the deterministic occupancy schedules suggested by current building design standard as a baseline.

Occupancy of rooms in urban residential buildings by users in cold areas of China

Occupancy is used to represent the movements and locations of users among various zones of buildings,and it is the basis of all other daily energy consumption behaviors.This study investigated eight families in cold areas of China based on occupancy measurements obtained in four main rooms,i.e.,living room,bedroom,kitchen,and bathroom.In particular,we analyzed the duration of user occupancy and hourly mean occupancy,and characterized their regular and random features.According to the results,we developed an event-based occupancy model using an inhomogeneous Markov chain,where the rooms were modeled and daily events were divided into three categories according to their randomness.We established a new method for conversion between event characteristic parameters and a transition probability matrix,as well as an overlap avoidance method for active events.The model was then validated using real data.The results showed that the model performed well in terms of two evaluation criteria.The model should improve the accuracy of simulations of occupancy.

Review on occupancy detection and prediction in building simulation

Energy simulation results for buildings have significantly deviated from actual consumption because of the uncertainty and randomness of occupant behavior.Such differences are mainly caused by the inaccurate estimation of occupancy in buildings.Therefore,the error between reality and prediction could be largely reduced by improving the accuracy level of occupancy prediction.Although various studies on occupancy have been conducted,there are still many differences in the approaches to detection,prediction,and validation.Reports published within this domain are reviewed in this article to discover the advantages and limitations of previous studies,and gaps in the research are identified for future investigation.Six methods of monitoring and their combinations are analyzed to provide effective guidance in choosing and applying a method.The advantages of deterministic schedules,stochastic schedules,and machine-learning methods for occupancy prediction are summarized and discussed to improve prediction accuracy in future work.Moreover,three applications of occupancy models—improving building simulation software,facilitating building operation control,and managing building energy use—are examined.This review provides theoretical guidance for building design and makes contributions to building energy conservation and thermal comfort through the implementation of intelligent control strategies based on occupancy monitoring and prediction.