Occupancy Rate Research Articles

COVID-19 outbreaks in long-term care facilities—a nationwide population-based cohort study in Taiwan, May–July 2021

Long-term care facilities (LTCFs) are high-risk settings for the novel coronavirus disease (COVID-19). The aim of the study was to describe the extent and the impacts of 2021 COVID-19 outbreaks on LTCFs in Taiwan. We retrospectively analyzed the data of each COVID-19 outbreak in LTCFs from May 15 to July 31, 2021 in Taiwan. We characterized the features of LTCFs with outbreaks and compared the characteristics of infected staff members and residents of the affected LTCFs. COVID-19 outbreaks were reported in 16 LTCFs (0.9%). The outbreak was significantly associated with LTCFs with ≥50 beds [adjusted odds ratio (aOR), 6.3; 95%confidence interval [CI], 1.9-21.1] and location of Taipei metropolitan area (aOR, 4.6; 95%CI, 1.7-12.8). Resident cases accounted for 75.4% (203/269) of confirmed cases affected by outbreaks. The 30-day all-cause mortality was 24.2% for residents only and was significantly associated with age ≥65 years [adjusted hazard ratio (aHR, 4.3; 95%CI, 1.7-10.5)], presence of symptoms on diagnosis (aHR, 2.2; 95%CI, 1.3-3.7), and LTCF occupancy rate ≥80% (aHR, 3.0, 95%CI, 1.3-7.4). COVID-19 outbreaks have a critical impact on residents in LTCFs owing to the advanced age and high prevalence of chronic comorbidities in this population. Multi-pronged infection control measures and mass testing are vital for mitigating COVID-19 transmission in LTCFs.

The effect of digitalization of nursing forms in ICUs on time and cost

ObjectiveIntensive Care Units are one of the areas with the lowest digitization rate. This study aims to measure the effect of digitizing medical records kept in paper forms in ICUs on time-saving and paper consumption. In our study, care forms in ICUs were transferred to digital media. In our research, care forms in ICUs were transferred to digital media.MethodsThe time required to fill out the nursing care forms on paper and digital media was measured, the change in paper and printer costs was determined, and the results were compared. Two volunteer nurses working in the ICU of a university hospital in Istanbul measured the time it took to fill out the forms of patients on paper. Then, a future projection was made using digital form data of 5,420 care days of 428 patients hospitalized between October 2017 and September 2018. Only anonymous data of patients hospitalized in the general ICU were used, and other untempered were not included in the study.ResultsWhen the forms were filled in digitally by the nurses, one nurse per patient per day saved 56.82 min (3.95% per day).DiscussionHealth care services are provided in hospitals in Turkey with 28,353 adult intensive care beds and an occupancy rate of 68%. Based on the occupancy rate of 68%, the number of full beds is 19,280. When 56.82 min are saved per bed from the forms filled by the nurses, 760.71 care days are dedicated. Considering the salary of 1,428.67 US dollars per nurse, the savings to be achieved are estimated to be 13,040,804.8 US dollars per year.

Usefulness of Percutaneous Pedicle Screw Fixation for Treatment of Lower Lumbar Burst (A3-A4) Fractures: Comparative Study with Thoracolumbar Junction Fractures.

Percutaneous pedicle screw fixation (PPSF) without fusion has been recently recommended in the treatment of thoracolumbar fracture to reduce the adverse effects associated with the conventional open approaches and to restore range of motion. However, those studies report on the thoracolumbar junction, and there is no report on lower lumbar fracture. To assess effectiveness of PPSF without fusion for treating lower lumbar burst (A3 and A4) fractures. A retrospective analysis was made to evaluate consecutive 50 patients with AO type A3 and A4 thoracolumbar fracture underwent PPSF. Patients were divided into a thoracolumbar junction (TLJ) group (T11-L2) and lower lumbar (LL) group (L3-5). The following items were measured and compared between the two groups. Vertebral height and consolidation, retropulsed fragment, sagittal curve and fixation failure were assessed with certain interval regularly. The average height at pre- and post-reduction were 56.2% (36.2-74.3), 95.3% (84.2-98.3) in TLJ group and 65.7% (45.7-86.2), 91% (73.1-100) in LL group. The average canal area occupancy rate at pre- and post-reduction were 46.1% (37.4%-67.5%), 38.1% (31.3%-40.8%) in TLJ group and 40.4% (15.0-65.7), 19.3% (9.4-26.6) in LL group. Consolidation was completed within 12months after surgery in both groups. There was no significant difference between two groups in clinical and radiographic parameters except cobb angle loss. Patients with lower lumbar fracture can be effectively managed with PPSF without fusion. PPSF following the implant removal can restore the movement of the lower lumbar spine, which is essential for daily life.

Empirical studies on the impact of booking status on customers’ choice behavior in online appointment systems

We consider customers' choice behavior in online appointment systems. In three online experiments, we investigate whether and to what extent customers are impacted by the number of available slots by asking subjects to choose between two providers of several service areas with different occupancy rates. In line with previous literature, we find some evidence that customers infer quality from a utilized system compared to an empty schedule; that is, any demand (very few booked appointments) is preferred to no demand (empty booking schedule). A too-small offer set, in contrast, shows congestion and leads to an opposed scarcity effect because customers expect the provider to be in a rush, the waiting room to be crowded, and further value flexibility in the choice of the appointment time. We contribute to the literature by analyzing the interaction of the two nonlinear effects and further find that the presence of the quality-inference effect depends on the type of service. For a standardized service, we find no evidence of the quality-inference effect. For nonstandardized services, however, we find an inverse U-shaped preference in the number of offered slots, showing that customers prefer a medium utilization of the service provider. We find that this is a robust representation of customers' preferences, even if other quality signals, such as star ratings and prices, are available.

Estimation of multicomponent stress–strength reliability based on unit Burr XII distribution: an application to dam occupancy rate of Istanbul, Turkey

ABSTRACT In this paper, we consider the estimation of a multicomponent stress–strength reliability when stress and strength variables follow unit Bur XII distribution. In estimation procedure, the maximum likelihood and Bayesian methods are used. The maximum likelihood estimator is obtained via iterative methods. The asymptotic confidence interval is constructed using asymptotic properties of the corresponding estimator. In addition, two bootstrap confidence intervals are constructed. Bayesian estimator is obtained using three different approximation methods: Lindley’s approximation, Tierney–Kadane approximation and Markov Chain Monte Carlo method. The interval estimation based on Bayesian method is studied. The simulation study is conducted to investigate and compare the performance of the considered methods. Finally, an original data set, general dam occupancy rate of Istanbul, Turkey obtained from Istanbul Statistic Office, is analysed in the concept of multicomponent stress–strength reliability.

Checking in at bee hotels: trap-nesting occupancy and fitness of cavity-nesting bees in an urbanised biodiversity hotspot

With urbanisation leading to loss of nesting resources, and increasing public interest in helping bees, bee hotels (trap-nests) are becoming popularised. However, their success is relatively understudied. The influence of habitat type in determining occupancy and emergence is also poorly known. Over two years across 7 bushland remnant and 7 residential garden sites, trap-nests were installed and completed nests collected monthly over spring-summer. Bees appeared to take a month to find the trap-nests, irrespective of month they were installed. A small percentage (13% and 6% in the two years) of tubes were occupied, but this was within the range of other trap-nesting studies. Smaller 4 and 7 mm diameter nests had a higher occupancy rate than 10 mm diameter tubes. An impressive number − 24 bee species – occupied the trap-nests. Representation however was dominated by five species. The species composition (species and their relative abundances) of cavity-nesting bees differed greatly between those using the trap-nests compared with those observed in the field. Bushland remnants tended to have more bee hotels occupied, and male body size of emerged bees was larger in this habitat. Unexpectedly native and total flower diversity reduced bee hotel occupancy, whereas native flower parameters tended to positively influence bee fitness. Overall installing bee hotels can provide additional nesting resources for native bees in urbanised areas, and providing high proportions of native flora in the vicinity should enhance fitness of the bees using them.

Design and application of an intelligent communication platform for aesthetics education for internationalization

Abstract With the rapid development of information technology, aesthetics education is changing, and the use of computer technology for teaching has become the new norm in the teaching field. In recent years, many intelligent platforms for aesthetics education have emerged at home and abroad, but most of them are only simple video courses, which can hardly meet the needs of aesthetics education. In order to design an international-oriented intelligent communication platform for aesthetics education, this paper builds an intelligent platform serving aesthetics education based on the relevant technologies of intelligent learning communication and completes performance tests after implementation. On the user side, the average memory consumption of the intelligent platform is 15.6 MB, the average memory occupation rate is only 15.34%, and the average network traffic consumed per operation step is only 7.56 MB. The CPU consumption of the platform is also relatively low. The highest occupation rate is 3.76%, the lowest is 0.81%, and the average is only 2.58%. For the server-side Web test, the average system response time of the intelligent platform is 0.72 seconds, which is a very fast response time. In the concurrency test, the platform still runs smoothly under the full concurrency of 100 concurrency numbers and can respond to most users’ requests within 1 second. The intelligent platform is fully capable of meeting the needs of teachers and students in aesthetics education. The international-oriented intelligent communication platform for aesthetics education designed in this paper can help cultivate students’ aesthetic perception and thinking ability, thus improving their aesthetic literacy in an all-around way.

Challenging transitions? Assessing the occupational mobility patterns of US immigrants by gender

AbstractThis article uses the New Immigrant Survey to assess the occupational mobility of US immigrants. Estimates from OLS and Heckman selection models show the occupational mobility of immigrants follows a U‐shaped pattern: immigrants arriving in the United States see their occupational status decline before it gradually improves. However, even 9 years after coming to the United States, the occupational status of immigrants remains lower than prior to their arrival in the country. Our findings also suggest that immigrant women with higher occupational status tend to move more often to the United States than immigrant men. Conversely, immigrant women are more likely than men to experience career interruptions after migration. Finally, occupational employment growth rates (defined as the growth rate in the number of jobs for an occupation) have a positive impact on both men and women immigrants' ability to recover their occupational status, though the impact appears to be greater for immigrant women.

Stability and bifurcation analysis of an infectious disease model with different optimal control strategies

This paper deals with the non-linear Susceptible–Infected–Hospitalized–Recovered model with Holling type II incidence rate, treatment with saturated type functional response for the prevention and control of disease with limited healthcare facilities. The well-posedness of the model is ensured with the help of the non-negativity and boundedness of the solution of the system. The feasibility of the model with DFE (Disease-free equilibrium) and EE (endemic equilibrium) is analysed. The local and global stability are discussed with the help of the computed basic reproduction number R0. At R0=1, we use the Centre manifold theory to analyse the transcritical bifurcation exhibited by the system. It is found that the disease is not eradicated even if R0<1 due to the occurrence of backward bifurcation. The occurrence condition of Hopf bifurcation is obtained. The optimal control theory is used to analyse the effects of the minimum possible medical facilities, hospital beds, and awareness creation on the population dynamics. The Hamiltonian function is constructed with the extended optimal control model and solved by Pontryagin’s maximum principle to get the minimum possible expenditure. Different types of control strategies are shown by numerical simulation. The sensitivity analysis is discussed with the help of a crucial parameter that depends on the reproduction number. Further, the model is simulated numerically to support the theoretical studies. This paper emphasizes the significance of treatment intensity, the total number of hospital bed available and their occupancy rate as vital parameters for prevention of disease prevalence.

Operational performance and budget constraints: case study in a Public Hospital specialized in Hematology

The objective of this paper is to analyze the impact of budget constraints of the Brazilian public sector on operational performance indicators in a hematology specialized Hospital. In order to carry out this research a case study approach was designed considering average length of stay, occupancy rate, hospital mortality rate. Data regarding results of these indicators were obtained considering two periods of time. The first period was from January 2013 to December 2014 and the second period was from January 2015 to September 2016. Expected performance reference values from these indicators were also obtained. Data were obtained from official performance reports. The starting point for budget constraints considered was January 2015. Descriptive statistics was used to present the operational performance obtained. Mann-Whitney U test was used to analyze the presence of significant differences (p=0.05) in operational performance for the performance indicators considered. The results point out that, despite budget constraints, the operational performance regarding occupancy rates and hospital mortality rate did not presented statistically significant differences. Average length of stay was higher in the second period.

Royal Victoria Hotel Industrial Strategies and Efforts Towards the Impact of The Covid-19 Pandemic

The spread of the COVID-19 Virus occurred very quickly, the lack of responsive public awareness caused the virus to spread and eventually claimed lives and caused unrest. The COVID-19 pandemic has also affected economic activity. The impact of COVID-19 on the hospitality industry in Indonesia has also been badly affected. Various strategies were carried out by the hotel industry and the government in reducing the impact of increasingly large losses. The research aims to analyze the strategies and efforts of the Hotel Victoria industry towards the impact of the COVID-19 pandemic. A qualitative descriptive approach is the foundation of research by collecting data through observation, interviews and document studies. The conclusions from this research are; The occupancy rate of the Hotel Royal Victoria has fallen sharply. In 2019 the occupancy rate of Hotel Royal Victoria was 37%. The impact of the COVID-19 Pandemic includes decreasing hotel occupancy rates, increasing operational costs, and termination of employment. The strategies implemented by Hotel Royal Victoria in dealing with the COVID-19 pandemic include: having a CHSE certificate, issuing frugal Meals Box and Rice Bowl packages, promoting on social media, offering room rates with a 50% discount on travel platforms, and conducting employee reviews. whose contract has expired. These strategies were recognized as very effective and helped Hotel Royal Victoria survive during the COVID-19 pandemic.

Reuse of mixed masonry wastes in plastering mortars

According to Eurostat statistics, the volume of waste collected is constantly increasing, the amount of waste produced in Europe in 2020 reaching 2151 million tons. In the European Union, the most waste-producing activity is construction and demolition, accounting for 37.1% of the total waste produced in 2020. This type of waste has a high occupancy rate. This article proposes the reuse of mixed masonry waste in the production of plaster mortars. The maximum amount of mixed masonry waste used in the experiment was 35%, partially replacing the aggregate component. The physical and mechanical characteristics that have been measured in the experimental program may be divided into two categories: characteristics of mortars in fresh state (apparent density, consistency) and in hardened state (bending strength, compressive strength and adhesion to the support layer). In order to highlight the influence of the addition of waste on the composition and on the evolution of the mechanical properties of the studied mortars, the experimental program was distributed over 3, 7 and 28 days. The results showed an increase in the mechanical strength of mortars containing mixed masonry waste compared to standard mortar. Mixed masonry waste can be a substitute for raw materials in the production of new types of plaster mortars and contributes to the reduction of the resulting waste by recycling and reuse. The experimental program will be continued with microscopic investigations using modern investigation methods, to highlight the behaviour of mortars with masonry waste, and to identify the correct proportion of waste that can be used in mortar networks so as not to affect the characteristics required by the acting norms.

Fire risk assessment of Malaysia public hospital buildings

Fire risk assessment of Malaysia public hospital buildings

Collaborative Planning of Community Charging Facilities and Distribution Networks

The construction of community charging facilities and supporting distribution networks based on the predicted results of electric vehicle (EV) charging power in saturation year has resulted in a large initial idleness of the distribution network and a serious waste of assets. To solve this problem, this paper proposes a collaborative planning method for urban community charging facilities and distribution networks. First, based on the load density method and occupancy rate to predict the base electricity load in the community, the Bass model and charging probability are used to predict the community’s electric vehicle charging load. Taking the minimum annual construction and operation costs of the community distribution network as the objective function, the power supply topology of the distribution network for a new community is optimized by using Prim and single-parent genetic algorithms. Finally, the proposed scheme is verified by using the actual community data of a certain city in China as an analysis example, and the scheme of one-time planning of the distribution network and yearly construction of charging facilities is given.

NCG-TSM: A Noncooperative Game for the Taxi Sharing Model in Urban Road Networks

Taxi sharing is a promising method to save resource consumption and alleviate traffic congestion while satisfying people’s commuting needs. Existing research methods include taxi dispatching methods based on intelligent algorithms, single vehicle route recommendation algorithms, and route recommendation algorithms based on vehicle traffic history. However, these studies either focus on how to efficiently dispatch satisfactory vehicles for passengers, ignoring the effect of efficient routes on vehicle travel efficiency, or let vehicles follow the shortest detour distance recommended by the system, ignoring the traffic congestion caused by the influx of vehicles into the same road. To address the abovementioned problems, a noncooperative game for a taxi sharing model (NCG-TSM) in urban road networks is proposed in this paper combined with the traffic conditions of the optional routes, and a distribution estimation algorithm for the shared taxi game is designed to make multivehicle route selections reach Nash equilibrium. The effectiveness of NCG-TSM is verified through simulation experiments. When the number of vehicles reaches the congestion capacity of the road segment, compared to the three common frameworks, the travel time cost and fuel consumption cost can be reduced by 5.8% to 9.1% and 3.5% to 8.9%, respectively. Besides, the occupancy rate has been improved, especially compared to the BMP framework, by 5.5% to 40%.

Passive acoustic monitoring indicates Barred Owls are established in northern coastal California and management intervention is warranted

Abstract Barred Owls (Strix varia) have recently expanded westward from eastern North America, contributing to substantial declines in Northern Spotted Owls (Strix occidentalis caurina). Passive acoustic monitoring (PAM) represents a potentially powerful approach for tracking range expansions like the Barred Owl’s, but further methods development is needed to ensure that PAM-informed occupancy models meaningfully reflect population processes. Focusing on the leading edge of the Barred Owl range expansion in coastal California, we used a combination of PAM data, GPS-tagging, and active surveys to (1) estimate breeding home range size, (2) identify patterns of vocal activity that reflect resident occupancy, and (3) estimate resident occupancy rates. Mean breeding season home range size (452 ha) was reasonably consistent with the size of cells (400 ha) sampled with autonomous recording units (ARUs). Nevertheless, false-positive acoustic detections of Barred Owls frequently occurred within cells not containing an activity center such that site occupancy estimates derived using all detected vocalizations (0.61) were unlikely to be representative of resident occupancy. However, the proportion of survey nights with confirmed vocalizations (VN) and the number of ARUs within a sampling cell with confirmed vocalizations (VU) were indicative of Barred Owl residency. Moreover, the false positive error rate could be reduced for occupancy analyses by establishing thresholds of VN and VU to define detections, although doing so increased false negative error rates in some cases. Using different thresholds of VN and VU, we estimated resident occupancy to be 0.29–0.44, which indicates that Barred Owls have become established in the region but also that timely lethal removals could still help prevent the extirpation of Northern Spotted Owls. Our findings provide a scalable framework for monitoring Barred Owl populations throughout their expanded range and, more broadly, a basis for converting site occupancy to resident occupancy in PAM programs.

Bayesian-Based Hyperparameter Optimization of 1D-CNN for Structural Anomaly Detection.

With the rapid development of sensor technology, structural health monitoring data have tended to become more massive. Deep learning has advantages when handling big data, and has therefore been widely researched for diagnosing structural anomalies. However, for the diagnosis of different structural abnormalities, the model hyperparameters need to be adjusted according to different application scenarios, which is a complicated process. In this paper, a new strategy for building and optimizing 1D-CNN models is proposed that is suitable for diagnosing damage to different types of structure. This strategy involves optimizing hyperparameters with the Bayesian algorithm and improving model recognition accuracy using data fusion technology. Under the condition of sparse sensor measurement points, the entire structure is monitored, and the high-precision diagnosis of structural damage is performed. This method improves the applicability of the model to different structure detection scenarios, and avoids the shortcomings of traditional hyperparameter adjustment methods based on experience and subjectivity. In preliminary research on the simply supported beam test case, the efficient and accurate identification of parameter changes in small local elements was achieved. Furthermore, publicly available structural datasets were utilized to verify the robustness of the method, and a high identification accuracy rate of 99.85% was achieved. Compared with other methods described in the literature, this strategy shows significant advantages in terms of sensor occupancy rate, computational cost, and identification accuracy.

Logistics dynamic information retrieval based on blockchain data security model

This study presents blockchain technology to integrate the time attribute of Internet of Things data and the time stamp of blockchain, and proposes a data retrieval solution based on dynamic information retrieval. Analyze and reorganize the blockchain data at the bottom of the logistics information platform to synchronize the logistics information to the third-party relational database. The experimental results show that the proposed method can improve the data entry time of the system by 5.2%, and the system occupancy rate is less than 4.1%. It is proved that the proposed model can simplify the data attributes of the Internet of Things, improve the universality of data, effectively integrate the structural characteristics of the Internet of Things and blockchain, and realize safe and efficient data management and application.

Adaptation Strategies for the post recovery of Medium-Sized Hotel Businesses from the COVID-19 Pandemic in Koh Samui Island, Thailand

This study aims to investigate the adaptation strategies and factors related to business recovery among medium-sized hotel entrepreneurs in Koh Samui District, Surat Thani Province during the COVID-19 pandemic. The research surveyed 150 participants, and data analysis was performed using statistical techniques such as frequency, percentage, mean, standard deviation, t-test, F-test, One-Way ANOVA, and Chi-Square test. The study found that the majority of hotel entrepreneurs operate independently, with a primary customer base of foreign tourists, and promote their businesses through online advertising. The impact of the pandemic on revenue, occupancy rate, and employment was severe, with a decrease of 81-100%. During the recovery period, hotel business owners recognized the need for adjustment, with operations being the highest priority, followed by marketing, finance, human resources, and customer aspects. Furthermore, hotel type, star rating, and marketing strategies had varying impacts on the adjustments made during the recovery period. The study concludes that the severity of the pandemic's impact is related to the adaptation strategies of medium-sized hotel business owners during the recovery period. Therefore, the findings of this study can provide a guideline for hotel entrepreneurs to manage their businesses effectively during future pandemics.

Application of image recognition based on neural network algorithm in multimedia dance teaching

Neural network recognition algorithm is a deep learning-based convolutional neural network, which has been applied to target detection, image recognition, sound recognition and other fields. Although the recognition technology of convolutional neural network has been gradually stabilized, it is mainly implemented in single-machine serial mode. Therefore, there will be problems such as too long training time and insufficient memory capacity. According to the previous work, this paper has carried out related research and obtained some useful results. This paper focuses on the introduction of image recognition technology based on neural network algorithm. At the same time, this paper proposes a fast real-time image recognition algorithm, which has high recognition accuracy. In this paper, the existing algorithms mentioned in the paper are analyzed, the characteristics and shortcomings of all algorithms are summarized, and the appropriate combination of algorithms is selected for specific problems. On this basis, the acceleration method of artificial neural network is used to improve the algorithm of convolutional neural network image recognition technology. With the continuous development of education and the increase of the number of students year by year, the effect of classroom teaching becomes particularly important. Therefore, modern information technology is used to transfer the classroom teaching mode to the network and realize a new method of online remote online dance teaching. According to the actual situation of dance teaching, the advantages of multimedia dance teaching are analyzed. The software of multimedia dance teaching system is tested comprehensively, from the aspects of computer system memory occupancy rate and temperature, to test whether the activities of B/S mode multimedia dance teaching system meet the expected goals and requirements of each core module of multimedia dance teaching system.