Enhanced Resource Allocation Research Articles

Safe radiological spinal intervention: A multicenter snapshot survey of musculoskeletal radiologists in the UK and India

Objectives: Research, knowledge, and technological advances have promoted minimally invasive image-guided diagnostic and therapeutic intervention. Such interventions are increasingly performed for musculoskeletal diseases by radiologists within outpatient settings. The objective of this study was to ascertain levels of safe practice among musculoskeletal radiologists in the United Kingdom and the Indian public health-care system, as defined by access to spinal surgeons and anesthetists during radiological spinal procedures. Material and Methods: An online cross-sectional survey of eight questions (multiple choice and free text) was circulated among musculoskeletal radiologists in the UK and India, to evaluate: (i) Image-guided practice among musculoskeletal radiologists. (ii) Types of interventions undertaken. (iii) Practice setting. (iv) Availability of supportive, backup access to spinal surgery services. Results: A total of 53 replies were received of which 43 (81.1%) were from musculoskeletal radiologists who perform spinal interventional procedures. Spinal biopsies and injections were the most common procedures performed by the 43 eligible radiologists (79.1% and 74.4%, respectively), with vertebroplasty and sacroplasty performed by only 16.3% and 11.6%, respectively. Less than half (46.5%) of musculoskeletal radiologists performing interventional procedures did so within a hospital setting with both a spinal surgeon and an anesthetist on site, 20.9% had an anesthetist on site but no spinal surgeon and 16.3% had neither on-site. Conclusion: Minimally invasive image-guided diagnostic and therapeutic intervention is a niche sub-specialty practiced by a few musculoskeletal radiologists. Enhanced resource allocation, skills training, and multidisciplinary service provision will ultimately minimize existing deficiencies, improving patient-related clinical outcomes, and quality of care.

Enhanced Resource Allocation in D2D Communications With NOMA and Unlicensed Spectrum

Device-to-device (D2D) communications with non- orthogonal multiple access (NOMA) have been proved in enhancing the network capacity and reducing the burden of the traditional cellular network. Due to reusing the same resources, the underlying D2D communication may cause high interference to cellular users, and thus reducing the network throughput. To alleviate this issue, we consider moving D2D users to the unlicensed band. In this case, D2D users can reuse the resources in cellular networks or share the unlicensed band with WiFi users. However, a critical question is how to effectively perform NOMA user clustering and determine D2D pairs that should use unlicensed band and how to guarantee the quality service of users at both networks. Our objective is to maximize the network throughput by investigating a joint resource allocation problem of user clustering, power control, and D2D mode selection. Since the formulated problem is a mixed-integer nonlinear programming problem, finding an optimal solution is a great challenge. To solve this problem, we propose to use a swarm intelligence approach, namely whale optimization algorithm in solving our optimization problem with an efficient solution. Through simulation results, we show that our proposed scheme attains a better performance than other alternative schemes.

Resource Allocation in 4G and 5G Networks: A Review

The advent of 4G and 5G broadband wireless networks brings several challenges with respect to resource allocation in the networks. In an interconnected network of wireless devices, users, and devices, all compete for scarce resources which further emphasizes the fair and efficient allocation of those resources for the proper functioning of the networks. The purpose of this study is to discover the different factors that are involved in resource allocation in 4G and 5G networks. The methodology used was an empirical study using qualitative techniques by performing literature reviews on the state of art in 4G and 5G networks, analyze their respective architectures and resource allocation mechanisms, discover parameters, criteria and provide recommendations. It was observed that resource allocation is primarily done with radio resource in 4G and 5G networks, owing to their wireless nature, and resource allocation is measured in terms of delay, fairness, packet loss ratio, spectral efficiency, and throughput. Minimal consideration is given to other resources along the end-to-end 4G and 5G network architectures. This paper defines more types of resources, such as electrical energy, processor cycles and memory space, along end-to-end architectures, whose allocation processes need to be emphasized owing to the inclusion of software defined networking and network function virtualization in 5G network architectures. Thus, more criteria, such as electrical energy usage, processor cycle, and memory to evaluate resource allocation have been proposed. Finally, ten recommendations have been made to enhance resource allocation along the whole 5G network architecture.

Green Credit Policy and Corporate Productivity: Evidence from a Quasi-natural Experiment in China

• We examine the impact of green credit policy on corporate total factor productivity. • Green credit policy improves total factor productivity of heavily polluting firms. • Technology innovation and resource allocation efficiency are the channels. • Firm characteristics, external monitoring, and regional differences shape the link. Taking the implementation of the “Green Credit Guidelines” in China in 2012 as an exogenous shock, we adopt the difference-in-differences (DIDs) method to explore the influence of the green credit policy on total factor productivity (TFP). We show evidence of a significant and positive correlation between green credit and corporate total factor productivity, and this result is robust to a series of robustness tests. In addition, the improvement is particularly evident for non-SOEs, small-scale firms, firms with weak external supervision, and firms in developed areas of eastern China. Moreover, the green credit policy mainly affects corporate total factor productivity through promoting technological innovation and enhancing resource allocation efficiency. Overall, green credit promotes the win-win development of the environment and the economy.

Optimal Resource Allocation in Economic Systems: A Numerical Approach

Optimal resource allocation is a critical challenge faced by modern manufacturing companies seeking to maximize profitability while adhering to resource limitations and market demands. This study investigates the application of numerical optimization techniques in addressing resource allocation complexities. Using a hypothetical case study of a manufacturing company producing electronic gadgets, we analyze the effectiveness of numerical methods in comparison to traditional analytical approaches. Through a detailed exploration of gradient-based optimization and derivative-free methods, we demonstrate the advantages of numerical optimization in achieving optimal resource allocations. Our findings underscore the significance of considering both demand forecasts and production capacities, leading to insightful policy recommendations for manufacturing companies and economic decision-makers. This research contributes to the field of economic optimization by highlighting the potential benefits of numerical approaches in enhancing resource allocation decision-making processes.

Does digital investment affect carbon efficiency? Spatial effect and mechanism discussion

Digitalization supported by ICT capital is a core weapon for decoupling economic growth from carbon emissions. This research innovatively calculates ICT capital in China from 2001 to 2018 and explores how ICT capital affects carbon emission efficiency and its spatial spillover effects from a digital investment perspective. The empirical results prove that ICT capital contributes to improvement of carbon emission efficiency, pure technical efficiency, scale efficiency and technological progress. Furthermore, interestingly, ICT communication capital was found to have the strongest effect on improving carbon emission efficiency, while ICT hardware capital and software capital have a weaker effect. The spatial effect demonstrates that ICT capital not only helps improve the local carbon emission efficiency but also has spatial spillovers to the surrounding areas and has the most prominent effect on the carbon emission efficiency of the central region. The mediation tests illustrate that ICT capital improves carbon emission efficiency by promoting technological innovation, alleviating industrial structure distortions, enhancing resource allocation efficiency and accelerating human capital accumulation. These findings have important policy guiding significance for the region to stimulate the potential of ICT capital and facilitate the low-carbon transformation of the economy.

Symptoms of anxiety and depression associated with concerns about infection and gender-based violence during the COVID-19 pandemic

BackgroundIt is known that the COVID-19 pandemic and social isolation has increased anxiety, depression, and gender-based violence. However, to the best of our knowledge no studies have evaluated differences in the association between anxiety and depression symptomatology with concern about becoming infected with COVID-19, and the differential risk of suffering from gender-based violence among women with a previous mental disorder, and black women.
 MethodsWe conducted a cross-sectional study among adults living in Brazil during the COVID-19 lockdown (20th June-30th August 2020). We administered an online questionnaire containing questions on socioeconomic characteristics, risk perception, confinement, health conditions, and gender-based violence. We ran two ordinal logistic regression models. In the first, we considered having a previous mental disorder and sex as the predictors, and concern about becoming infected with COVID-19 as the outcome. In the second model, we considered previous mental disorders and race as the predictors, and gender-based violence as the outcome. Depressive symptomatology and anxiety symptomatology was assessed through PHQ-9 and GAD-7, respectively.
 FindingsPeople who declared that they suffered from depression had a 2% less chance of concern about becoming infected with COVID-19, while those with anxiety had an 11% higher chance. Women had 19% more chance of being very concerned about becoming infected with COVID-19, compared to men. Women with previous mental health disorders had a 34% higher chance of suffering from gender-based violence, compared to women who did not declare having a previous mental health disorder. Black women had a 54% higher chance of suffering from gender-based violence during the COVID-19 pandemic, compared to white women.
 ConclusionsThis is the first study to demonstrate that black women and those with mental health problems are more likely to suffer from gender- based violence during the pandemic. These findings could be used in the preparation of protection policies focused on women in situations of major vulnerabilities, optimising interventions and enhancing resource allocation for those most in need, especially during pandemics.

Predicting the future: introducing business analytics to endoscopy units.

currently, most endoscopy software only provides limited statistics of past procedures, while none allows patterns to be extrapolated. To overcome this need, the authors applied business analytic models to predict future demand and the need for endoscopists in a tertiary hospital Endoscopy Unit. a query to the endoscopy database was performed to retrieve demand from 2015 to 2021. The graphical inspection allowed inferring of trends and seasonality, perceiving the impact of the COVID-19 pandemic, and selecting the best forecasting models. Considering COVID-19's impact in the second quarter of 2020, data for esophagogastroduodenoscopy (EGD) and colonoscopy was estimated using linear regression of historical data. The actual demand in the first two quarters of 2022 was used to validate the models. during the study period, 53,886 procedures were requested. The best forecasting models were: a) simple seasonal exponential smoothing for EGD, colonoscopy and percutaneous endoscopic gastrostomy (PEG); b) double exponential smoothing for capsule endoscopy and deep enteroscopy; and c) simple exponential smoothing for endoscopic retrograde cholangiopancreatography (ERCP) and endoscopic ultrasound (EUS). The mean average percentage error ranged from 6.1 % (EGD) to 33.5 % (deep enteroscopy). Overall, 8,788 procedures were predicted for 2022. The actual demand in the first two quarters of 2022 was within the predicted range. Considering the usual time allocation for each technique, 3.2 full-time equivalent endoscopists (40 hours-dedication to endoscopy) will be required to perform all procedures in 2022. the incorporation of business analytics into the endoscopy software and clinical practice may enhance resource allocation, improving patient-focused decision-making and healthcare quality.

Resource Allocation in 4G and 5G Networks: A Review

The advent of 4G and 5G broadband wireless networks brings several challenges with respect to resource allocation in the networks. In an interconnected network of wireless devices, users, and devices, all compete for scarce resources which further emphasizes the fair and efficient allocation of those resources for the proper functioning of the networks. The purpose of this study is to discover the different factors that are involved in resource allocation in 4G and 5G networks. The methodology used was an empirical study using qualitative techniques by performing literature reviews on the state of art in 4G and 5G networks, analyze their respective architectures and resource allocation mechanisms, discover parameters, criteria and provide recommendations. It was observed that resource allocation is primarily done with radio resource in 4G and 5G networks, owing to their wireless nature, and resource allocation is measured in terms of delay, fairness, packet loss ratio, spectral efficiency, and throughput. Minimal consideration is given to other resources along the end-to-end 4G and 5G network architectures. This paper defines more types of resources, such as electrical energy, processor cycles and memory space, along end-to-end architectures, whose allocation processes need to be emphasized owing to the inclusion of software defined networking and network function virtualization in 5G network architectures. Thus, more criteria, such as electrical energy usage, processor cycle, and memory to evaluate resource allocation have been proposed. Finally, ten recommendations have been made to enhance resource allocation along the whole 5G network architecture.

Effect of Strategy Implementation on Performance of Chemelil Sugar Company in Kisumu County, Kenya

The performance at Chemelil Sugar Company in Kisumu County has been unsatisfactory and thus, the study sought to examine whether strategy implementation can affect the performance. The study was underpinned on resource-based view theory. The descriptive research design was deemed relevant to the study. The target population was 60 and the key respondents incorporated the heads of departments. The sample size was 60. The study adopted the purposive sampling technique and questionnaires were used to collected the data. The analysis of the data was done using descriptive and inferential statistics. The results of the study showed that strategy implementation affect performance positively. The strategy implementation can be determined by resource allocation, stakeholders, communication and structure. The correlation analysis showed there was a strong positive relationship between performance and strategy implementation. The coefficient of determination (r2=.424) indicated that 42.4% of the variation in organizational performance can be explained by strategy implementation. The regression results established that strategy implementation is positively and significantly related to performance (?= .883, t = 2.847, p = .016). Hence, unit increase in strategy implementation while holding all other factors constant, increases performance by 0.883 units. The study recommended the improvement of strategy implementation through enhanced resource allocation, stakeholders, communication and structure could improve the performance of the organization. The allocation of the resources need to be adequate to foster the strategy implementation. It is suggested that stakeholders' skills to be matched with their responsibilities. The managers to create maximum awareness to employees when implementing new policies and effective structure be developed to encourage information sharing between departments. Keywords: Strategy implementation, performance, Chemelil Sugar Company, Kisumu County, Kenya

Computing Resource Allocation Scheme for DAG-Based IOTA Nodes.

IOTA is a distributed ledger technology (DLT) platform proposed for the internet of things (IoT) systems in order to tackle the limitations of Blockchain in terms of latency, scalability, and transaction cost. The main concepts used in IOTA to reach this objective are a directed acyclic graph (DAG) based ledger, called Tangle, used instead of the chain of blocks, and a new validation mechanism that, instead of relying on the miners as it is the case in Blockchain, relies on participating nodes that cooperate to validate the new transactions. Due to the different IoT capabilities, IOTA classifies these devices into full and light nodes. The light nodes are nodes with low computing resources which seek full nodes’ help to validate and attach its transaction to the Tangle. The light nodes are manually connected to the full nodes by using the full node IP address or the IOTA client load balancer. This task distribution method overcharges the active full nodes and, thus, reduces the platform’s performance. In this paper, we introduce an efficient mechanism to distribute the tasks fairly among full nodes and hence achieve load balancing. To do so, we consider the task allocation between the nodes by introducing an enhanced resource allocation scheme based on the weight least connection algorithm (WLC). To assess its performance, we investigate and test different implementation scenarios. The results show an improved balancing of data traffic among full nodes based on their weights and number of active connections.

Software-defined networks for resource allocation in cloud computing: A survey

Cloud computing has a shared set of resources, including physical servers, networks, storage, and user applications. Resource allocation is a critical issue for cloud computing, especially in Infrastructure-as-a-Service (IaaS). The decision-making process in the cloud computing network is non-trivial as it is handled by switches and routers. Moreover, the network concept drifts resulting from changing user demands are among the problems affecting cloud computing. The cloud data center needs agile and elastic network control functions with control of computing resources to ensure proper virtual machine (VM) operations, traffic performance, and energy conservation. Software-Defined Network (SDN) proffers new opportunities to blueprint resource management to handle cloud services allocation while dynamically updating traffic requirements of running VMs. The inclusion of an SDN for managing the infrastructure in a cloud data center better empowers cloud computing, making it easier to allocate resources. In this survey, we discuss and survey resource allocation in cloud computing based on SDN. It is noted that various related studies did not contain all the required requirements. This study is intended to enhance resource allocation mechanisms that involve both cloud computing and SDN domains. Consequently, we analyze resource allocation mechanisms utilized by various researchers; we categorize and evaluate them based on the measured parameters and the problems presented. This survey also contributes to a better understanding of the core of current research that will allow researchers to obtain further information about the possible cloud computing strategies relevant to IaaS resource allocation.

Development and validation of a risk prediction model for high-risk adenomas at the time of first screening colonoscopy among screening aged Canadians

The aim of this study was to develop a risk prediction model for high risk adenomas (HRAs) detected at screening colonoscopy based on readily available participant information. The cohort consisted of 3035 participants aged 50 to 74 years with no history of cancer who underwent a primary screening colonoscopy at a centralized colon cancer screening centre between 2008 and 2016. A multivariable logistic regression model was created using CRC risk factors identified from prior research. Model covariates were collected from a baseline questionnaire and included participant demographics (age and sex), lifestyle parameters (body mass index, alcohol, smoking, and vitamin D supplement use) and medical history (family history of CRC and diabetes). Mean participant age was 58.8 years, and 54.7% were male. 249 participants with HRAs were identified (8.2%). An adjusted c-statistic of 0.67 was calculated, and a specificity and negative predictive value of 97.2% (95% CI: 96.5–97.8) and 92.5% (95% CI: 92.2–92.8) for the detection of HRAs, respectively, were achieved using 20% predicted probability as a high-risk threshold. However, only a sensitivity of 12.1% (95% CI: 8.3–16.8) was achieved. Our model has moderate predictive ability, with strengths in being able to rule out those with an absence of HRAs on screening colonoscopy. Maximizing screening efficiency through improved risk prediction can enhance resource allocation. Ultimately, this model has the potential to improve patient care by reducing unnecessary colonoscopies, limiting this invasive procedure to those most likely to have significant findings.

An arabinose-induced enhancement of asexual reproduction and concomitant changes in metabolic state in the filamentous fungus Bipolaris maydis.

l-Arabinose, a major constituent pentose of plant cell-wall polysaccharides, has been suggested to be a less preferred carbon source for fungi but to be a potential signalling molecule that can cause distinct genome-wide transcriptional changes in fungal cells. Here, we explore the possibility that this unique pentose influences the morphological characteristics of the phytopathogenic fungus Bipolaris maydis strain HITO7711. When grown on plate media under different sugar conditions, the mycelial dry weight of cultures on l-arabinose was as low as that with no sugar, suggesting that l-arabinose does not substantially contribute to vegetative growth. However, the intensity of conidiation on l-arabinose was comparable to or even higher than that on d-glucose and on d-xylose, in contrast to the poor conidiation under the no-sugar condition. To explore the physiological basis of the passive growth and active conidiation on l-arabinose, we next investigated cellular responses of the fungus to these sugar conditions. Transcriptional analysis of genes related to carbohydrate metabolism showed that l-arabinose stimulates carbohydrate utilization through the hexose monophosphate shunt (HMP shunt), a catabolic pathway parallel to glycolysis and which participates in the generation of the reducing agent NADPH (the reduced form of nicotinamide adenine dinucleotide phosphate). Then, the HMP shunt was impaired by disrupting the related gene BmZwf1, which encodes glucose-6-phosphate dehydrogenase in this fungus. The resulting mutants on l-arabinose showed remarkably decreased conidiation, but a conversely increased mycelial dry weight compared with the wild-type. Our study demonstrates that l-arabinose acts to enhance resource allocation to asexual reproduction in B. maydis HITO7711 at the cost of vegetative growth, and suggests that this is mediated by the concomitant stimulation of the HMP shunt.

Enhanced Resource Allocation Algorithm for Heterogeneous Wireless Networks

In heterogeneous wireless networks, service providers typically employ multiple radio access technologies to satisfy the requirements of quality of service (QoS) and improve the system performance. However, many challenges remain when using modern cellular mobile communications radio access technologies (e.g., wireless local area network, long-term evolution, and fifth generation), such as inefficient allocation and management of wireless network resources in heterogeneous wireless networks (HWNs). This problem is caused by the sharing of available resources by several users, random distribution of wireless channels, scarcity of wireless spectral resources, and dynamic behavior of generated traffic. Previously, resource allocation schemes have been proposed for HWNs. However, these schemes focus on resource allocation and management, whereas traffic class is not considered. Hence, these existing schemes significantly increase the end-to-end delay and packet loss, resulting in poor user QoS and network throughput in HWNs. Therefore, this study attempts to solve the identified problem by designing an enhanced resource allocation (ERA) algorithm to address the inefficient allocation of available resources vs. QoS challenges. Computer simulation was performed to evaluate the performance of the proposed ERA algorithm by comparing it with a joint power bandwidth allocation algorithm and a dynamic bandwidth allocation algorithm. On average, the proposed ERA algorithm demonstrates a 98.2% bandwidth allocation, 0.75 s end-to-end delay, 1.1% packet loss, and 98.9% improved throughput performance at a time interval of 100 s.

Effect of Integrated Strategic Planning on Performance of Machakos County Government, Kenya

Resource allocation, environmental scanning and stakeholders’ play an important role in the performance of a county government. Lack of good integrated strategic planning leaders to lack of vision, slow budget approvals, lack of clear individual role, lack of alignment with the organization strategic plan, lack of employee involvement, poor staffing level, and ineffective communication during strategy implementation and lack of coordination of activities during strategy implementation in Machakos County. The specific objectives were to establish resource allocation, environmental scanning and stakeholders’ participation affect performance of Machakos county governments. This study used descriptive survey design with questionnaire as the instrument for data collection. The target population was 130 staffs from Machakos County Government which consisted of 13 county executive committee members, 13 chief officers, 26 directors, 13 accountants, 13 finance officers, 13 economists, 13 Supply chain officer and 26 office administrators. The findings revealed a positive and significant effect of each of the variables with performance of Machakos county governments. The study recommends that in order to performance among county governments, there is a need for the county government to enhance resource allocation through allocating adequate financial resources, utilizing resources as per set goals, proper utilization of physical resources that are accessible, carrying out audits of all the resources allocated and employing and deploying well-trained human resources, do adequate environmental scanning and advocate for stakeholders’ fully participation. Data was collected using structured questionnaire administered through drop and pick. Data collected were sorted, coded, and analyzed. Data were analyzed using both descriptive and inferential statistics with the aid of Statistical Package for Social Sciences. The findings revealed a positive and significant effect of each of the variables with performance of Machakos county governments. The study recommends that in order to performance among county governments, there is a need for the county government to enhance resource allocation through allocating adequate financial resources, utilizing resources as per set goals, proper utilization of physical resources that are accessible, carrying out audits of all the resources allocated and employing and deploying well-trained human resources, do adequate environmental scanning and advocate for stakeholders’ fully participation.

Geospatial Mapping of International Neurosurgical Partnerships and Evaluation of Extent of Training and Engagement

To evaluate the presence, extent, and temporality of transnational neurosurgical partnerships, to understand and inform measures to address neurosurgical deficiencies in low- and middle-income countries (LMICs). A Web search was conducted to identify actors from high-income countries (HICs) participating in neurosurgical delivery and/or capacity-building with LMICs from 2010 to 2018. Descriptive data on current neurosurgical partnerships were collected from published case reports, literature reviews, reports from academic institutions, and information on stakeholder Web pages. The level of training and engagement of each partnership was separately graded based on prespecified criteria, in which grade 3 represented partnerships that have most extensive training and engagement, and grade 1, the least extent. Data were analyzed using descriptive statistics and geospatially depicted on ArcMap GIS software. A total of 123 unique HIC-LMIC partnerships were described. Of these partnerships, 85 (69%) are derived from HICs in North America, followed by Europe, with 23 (19%). The most common LMIC partners were from Africa (n= 56, 45%) and Latin America (n= 32, 26%). In addition, most partnerships provided services in pediatric neurosurgery (88%). The most frequent engagement classifications were grade 2 (35%) or 1 (36%). Similarly, for training, the most common classifications were grade 1 (40%) or 2 (30%). A robust network of HIC-LMIC partnerships exists with varying degrees of engagement and training activities. Several regions are particularly suitable for growth and development. Systematic consolidation and indexing of transnational neurosurgical partnerships aim to enhance resource allocation and present opportunities for future partnership.

Is the number of daily walking steps in sedentary workers affected by age, gender, body mass index, education, and overall energy expenditure?

Healthy adults should take 10,000 steps per day to gain the resulting health benefits. Knowledge regarding the individual characteristics associated with daily walking steps would enhance resource allocation to those most likely to benefit from the 10,000-steps-per-day campaign. To determine the extent to which age, gender, body mass index (BMI), education, and energy expenditure influence daily walking steps in white-collar workers and to assess the correlation of daily walking steps among pedometer, wristband activity tracker, and smartphone application. A cross-sectional study was conducted on 49 sedentary workers. Daily walking steps were simultaneously assessed by three activity trackers in free-living conditions for 7 consecutive days. Associations between daily walking steps and individual factors were examined using linear regression. Correlation tests were conducted to assess the association among the three devices. Multiple regression analyses showed that BMI was associated with daily walking steps. A moderate to good correlation in daily walking steps was found between the wristband activity tracker and pedometer, as well as between the smartphone application and pedometer. BMI influenced daily walking steps in white-collar workers. Daily walking steps assessed by the wristband activity tracker and smartphone application differed from those assessed by the pedometer.

Intercultural Communication Competency Practices in the Hotel Industry

ABSTRACT The purpose of this study is to develop an in-depth understanding of cultural diversity in China’s hotels by examining hotel employees’ Intercultural Communication Competency (ICC) practices. Following qualitative data collection and content analysis of 403 valid questionnaires collected from 16 multinational hotel companies in China, the study uses Exploratory Factor Analysis and Confirmatory Factor Analysis for scale development. Furthermore, Importance-Performance Analysis is conducted to identify employees’ perceptions and performance with regard to ICC practices. The proposed measurement scale for ICC is shown to be both reliable and valid for hotel employees, and the results suggest that the identification of competency gaps can help hotels to improve service quality through enhanced resource allocation. Overall, the findings may help increase the competitiveness of China’s hotel industry by informing the development of effective training programmes.

Ultramassive MIMO Systems at Terahertz Bands: Prospects and Challenges

Terahertz (THz)-band communications are currently being celebrated as a key technology that could fulfill the increasing demands for wireless data traffic in 6G wireless communications. Many challenges, such as high propagation losses and power limitations, which result in short communication distances, have yet to be addressed for this technology to be realized. Ultramassive multiple-input, multiple-output (UMMIMO) antenna systems have emerged as practical means for combatting this distance problem, thereby increasing system capacity. Toward that end, graphene-based nanoantennas have recently been proposed, as they can be individually tuned and collectively controlled in compact UM-MIMO array-of-subarrays (AoSA) architectures. In this article, we present a holistic overview of THz UM-MIMO systems. We assess recent advancements in transceiver design and channel modeling and discuss the major challenges and shortcomings of such designs by deriving the relationships among communication range, array dimensions, and system performance. We further highlight several research advances that could enhance resource allocation at the THz band, including waveform designs, multicarrier configurations, and spatial modulations (SMs). Based on this discussion, we highlight prospective use cases that can bring THz UM-MIMO into reality in the context of sensing, data centers, cell-free systems, and mid-range wireless communications.