Usage Control Research Articles

ЗОЛЬСКИЕ СОБЫТИЯ 1913 Г. КАК КРИЗИС ДОВЕРИЯ В ПРАКТИКАХ ОБЩЕСТВЕННО-ГОСУДАРСТВЕННОГО ВЗАИМОДЕЙСТВИЯ В НАЛЬЧИКСКОМ ОКРУГЕ

The subject of trust in public-state interactions and local self-government is examined using the example of agrarian protests on Zolsky pastures grasslands in Nalchik district in June 1913. The new pastureland usage laws, authorized in 1912 and applied in the spring of 1913, sparked mass protests among residents of many Kabardian rural societies. Based on archival sources and mate-rials of periodicals,The major strategies for achieving “trust” in the adoption and approval of pub-lic pastureland use laws are outlined. Ritual and rhetorical forms of official and informal interac-tion between the crown authorities and representatives of the Kabardian society, which allowed to restore trust in the regional authorities, are considered. The grounds for the protracted suspension of the Congress of Entrusted from making decisions on the control of pastureland usage are de-termined, and are related to the fear of repeated expressions of protest feelings. The conclusion is substantiated that the complete overcoming of ideological consequences of the pasture crisis of 1913 became possible only in March 1917, when the congress of entrusted, freed from the super-vision of the crown administration, abolished the rules of 1912, which caused unrest on the Zolsky pastures.

Improving students’ punctuation: classroom experimentation and results in texts by primary and secondary school students in Quebec

The texts of primary and secondary school students show a high proportion of written errors related to punctuation (Boivin and Pinsonneault, 2018, among others). Yet punctuation instruction often offers students only limited opportunities to improve their control of sign usage in a writing context (Riverin and Dufour, 2018). This article presents a quasi-experimental study involving 16 French classes from cycle 3 of primary school and cycle 1 of secondary school in Quebec (age 10 to 13). Students in the experimental groups carried out a sequence of 20 activities implementing three innovative didactic devices, designed during a first phase of the research, in collaboration with the participating teachers. The aim was to improve punctuation and syntax in writing. We will present results drawn from the analysis of short texts written at pre-test and post-test (two texts at each time: one descriptive and one narrative) in the experimental and control groups, in relation to success variables in segmentation into graphic sentences (capital letter & full stop), and in punctuation within graphic sentences and syntactic sentences (clauses, i.e. subject + predicate (+ sentence adverbial(s)), for some comma usage rules.

Differences in Changes in Game Usage Time and Game Use-Related Factors Depending on Parity in a Prospective Study of Pregnant Women in Japan

Game usage has recently been increasing, but the actual situation of game usage and issues among pregnant women are not clarified. The purpose of this prospective longitudinal study was to examine changes in game usage, lifestyle, and thoughts about game usage during pregnancy depending on parity and to clarify the characteristics of pregnant women who continue to use games. We conducted three web surveys in early, mid- and late pregnancy in 238 pregnant women. For primiparous women who continued to use games, there was a significant increase in game usage time from early to late pregnancy (p = 0.022), and 25.0% of those women had anxiety that they might have a game addiction. For primiparous women in mid-pregnancy and multiparous women in early and late pregnancy, the proportions of women who thought that they could not use gaming sufficiently due to pregnancy and child-rearing were significantly higher in women who continued to use games. In both primiparous women and multiparous women, the proportion of partners who used games was significantly higher in women who continued to use games. It is necessary for midwives to discuss with pregnant women and their partners about game usage and to provide advice about control of game usage in daily life.

Integrating Usage Control Into Distributed Ledger Technology for Internet of Things Privacy

The Internet of Things brings new ways to collect privacy-sensitive data from billions of devices. Well-tailored distributed ledger technologies (DLTs) can provide high transaction processing capacities to IoT devices in a decentralized fashion. However, privacy aspects are often neglected or unsatisfying, with a focus mainly on performance and security. In this paper, we introduce decentralized usage control mechanisms to empower IoT devices to control the data they generate. Usage control defines obligations, i.e., actions to be fulfilled to be granted access, and conditions on the system in addition to data dissemination control. The originality of this paper is to consider the usage control system as a component of distributed ledger networks, instead of an external tool. With this integration, both technologies work in synergy, benefiting their privacy, security and performance. We evaluated the performance improvements of integration using the IOTA technology, particularly suitable due to the participation of small devices in the consensus. The results of the tests on a private network show an approximate 90% decrease of the time needed for the UCS to push a transaction and make its access decision in the integrated setting, regardless of the number of nodes in the network.

A multi-criteria decision model to support sustainable building energy management system with intelligent automation

With rising energy consumption in buildings, optimizing energy management is crucial for sustainability. This research pioneers the application of multi-criteria decision making (MCDM) techniques for real-time operational optimization of energy systems in buildings. A multicriteria decision analysis framework is used in this study to provide a model for decision making of generation and load balance. To assess the selection criteria, a thorough investigation is undertaken. The decision-based sustainable framework across conflicting criteria (encapsulating equal and objective weights) and aims towards the suitable trade-off solution. The framework is applied on workshop building across load-generation balance and is benchmarked with hardware. The research endeavor relies heavily on the deployment of sensor systems to prevent power wastage. By incorporating sensor systems, solar power usage control becomes smarter and more adaptable, enabling real-time modifications according to environmental conditions and energy requirements. This maximizes the overall efficiency and effectiveness of solar energy systems. Furthermore, the integration of sensor systems in solar power usage control improves reliability and maintenance through the identification and alerting of potential problems. TOPSIS and MCE are two methodologies that can be used in the field of multi-criteria decision model (MCDM). The originality of this study lies in the development of a MCDM framework to assist consumers in identifying resilient and optimal combinations of energy efficiency, cost-saving, and Indoor Environmental Quality (IEQ) improvement strategies for buildings in Pakistan.

Effectiveness of the Implementation of Semarang Mayor Regulation Number 27 of 2019 on Plastic Usage Control in Semarang City Area

This article is based on the existence of plastic which is one of the wastes from appropriate technology that is often used by humans.Focus in this article about amount to increase plastic waste in Semarang city over 3 years and implementation of regulation for all subyect bussiness targets in Semarang City. Therefore, this regulations are formed to reduce the generation of consume plastics in Semarang City. The purpose of this study is to determine to effectiveness of implementation of the mayor regulation of the city of semarang number 27 of 2019 as an effort to reduce consume plastic for to reduce the amount plastic waste in Semarang City. The legal research method used is empirical with the legal data analysis method that is descriptive qualitative. The results of this research are the conclusion is that the implementation of Semarang Mayor Regulation no. 27 of 2019 because there has been no reduction in the amount of plastic waste generated in Semarang City in 2019 -2020.

Roles of historical land use/cover and nitrogen fertilizer application changes on ammonia emissions in farmland ecosystem from 1990 to 2020 in China

In the past decades, China has witnessed significant changes in its land use/land cover (LULC) pattern. These changes have led to a direct impact on ammonia (NH3) emissions in soil background, and indirectly affected the total nitrogen fertilizer (N-fertilizer) application, crop planting amount and the resulting straw mass through the changes of cropland area. Great changes have also taken place in the amount and structure of fertilizer application in China, which affects the NH3 emissions from farmland ecosystems caused by N-fertilizer application. The aforementioned changes have led to significant alterations in NH3 emissions from China's farmland ecosystems over the past 30 years. The process of these changes remains to be analyzed, and the contributions of LULC changes and N-fertilizer application in this process are yet to be assessed. This study aims to investigate the NH3 emission changes and spatiotemporal variation characteristics from farmland ecosystems during 1990 and 2020 due to the LULC changes. Additionally, the study employs scenario analysis method to discuss the effects of LULC changes and N-fertilizer application changes on NH3 emissions in farmland ecosystems. Results indicate that there is evident spatiotemporal heterogeneity in China's LULC pattern, particularly in eastern China. The southeast region is predominantly characterized by the conversion of cropland into construction land. Moreover, some regions such as Northwest China and Northeast China have experienced the conversion of other land types into cropland, significantly influenced by national development policies. From 1990 to 2020, the national NH3 emissions from farmland ecosystem range from 3294.75 Gg to 4064.20 Gg. NH3 emissions and their interannual variation in farmland ecosystems exhibit significant differences across various regions. The regions with higher contributions to NH3 emissions in farmland ecosystems are East China, Central China, and North China, accounting for 25.32 %–37.26 %, 18.85 %–22.46 % and 11.24 %–18.50 % of the total emissions, respectively. NH3 emissions in each region are influenced by cropland area, N-fertilizer application, and regional development characteristics. Compared to LULC changes, changes in N-fertilizer application have a more pronounced impact on NH3 emission changes in farmland ecosystems. From 1990 to 2020, the contribution (increase or decrease) of N-fertilizer application changes to NH3 emission changes in farmland ecosystems in China ranges from 0.11 % to 16.61 %, while the contribution (increase or decrease) of LULC changes ranges from 0.47 % to 2.38 %. South China demonstrates a unique situation regarding the influence of LULC changes. This region has a relatively small cropland area, and fluctuations in cropland area significantly affect NH3 emissions in farmland ecosystems. The influence of policies is evident. From the changes in cropland area in Northwest China and Northeast China to changes in N-fertilizer application, policy changes have consistently impacted the changes in NH3 emissions in China's farmland ecosystems. From “soft policies” involving encouragement and guidance to “hard policies” encompassing the establishment of necessary targets, the degree of strictness in policy directly affects the timeliness of policies effectiveness. The results of this study indicate that reducing the application of N-fertilizers is the primary approach to reducing NH3 emissions in China's farmland ecosystems. In terms of policy guidance, compared to implementing structural and pathway adjustments, implementing clear total control of fertilizer usage is a timely and effective choice for reducing NH3 emissions.

Internet of Things Assisted Solid Biofuel Classification Using Sailfish Optimizer Hybrid Deep Learning Model for Smart Cities

Solid biofuels and Internet of Things (IoT) technologies play a vital role in the development of smart cities. Solid biofuels are a renewable and sustainable source of energy obtained from organic materials, such as wood, agricultural residues, and waste. The integration of IoT technology with solid biofuel classification can improve the performance, quality control, and overall management of biofuel production and usage. Recently, machine learning (ML) and deep learning (DL) models can be applied for the solid biofuel classification process. Therefore, this article develops a novel solid biofuel classification using sailfish optimizer hybrid deep learning (SBFC-SFOHDL) model in the IoT platform. The proposed SBFC-SFOHDL methodology focuses on the identification and classification of solid biofuels from agricultural residues in the IoT platform. To achieve this, the SBFC-SFOHDL method performs IoT-based data collection and data preprocessing to transom the input data into a compatible format. Moreover, the SBFC-SFOHDL technique employs the multihead self attention-based convolutional bidirectional long short-term memory model (MSA-CBLSTM) for solid biofuel classification. For improving the classification performance of the MSA-CBLSTM model, the SFO algorithm is utilized as a hyperparameter optimizer. The simulation results of the SBFC-SFOHDL technique are tested and the results are examined under different measures. An extensive comparison study reported the betterment of the SBFC-SFOHDL technique compared to recent DL models.

Unconventional secretion of Magnaporthe oryzae effectors in rice cells is regulated by tRNA modification and codon usage control.

Microbial pathogens deploy effector proteins to manipulate host cell innate immunity, often using poorly understood unconventional secretion routes. Transfer RNA (tRNA) anticodon modifications are universal, but few biological functions are known. Here, in the rice blast fungus Magnaporthe oryzae, we show how unconventional effector secretion depends on tRNA modification and codon usage. We characterized the M. oryzae Uba4-Urm1 sulfur relay system mediating tRNA anticodon wobble uridine 2-thiolation (s2U34), a conserved modification required for efficient decoding of AA-ending cognate codons. Loss of s2U34 abolished the translation of AA-ending codon-rich messenger RNAs encoding unconventionally secreted cytoplasmic effectors, but mRNAs encoding endoplasmic reticulum-Golgi-secreted apoplastic effectors were unaffected. Increasing near-cognate tRNA acceptance, or synonymous AA- to AG-ending codon changes in PWL2, remediated cytoplasmic effector production in Δuba4. In UBA4+, expressing recoded PWL2 caused Pwl2 super-secretion that destabilized the host-fungus interface. Thus, U34 thiolation and codon usage tune pathogen unconventional effector secretion in host rice cells.

BENEFICIAL IMPACTS OF EMERGING SMART SOLUTIONS FOR ENERGY EFFICIENCY IN THE BUILT ENVIRONMENT

It is common knowledge that the activities, processes, materials, and technologies employed in the built environment (BE) are excessively energy-intensive. It is also known that the BE is one of the critical sectors of the economy that requires holistic intervention and attention if the global sustainability agenda will be achieved. However, factors such as energy efficiency, water efficiency, waste management, and resource/materials efficiency among others are identified to be key to realizing a sustainable BE. The objective of this study is to identify the benefits of adopting and incorporating Emerging Smart Solutions (ESS) for achieving energy efficiency in the South African BE. The quantitative research method was adopted in this research study. A structured questionnaire was distributed to active construction professionals in the SACI for data collection. Descriptive and exploratory factor analysis was employed to analyze the retrieved data. Findings from the study revealed nineteen benefits of ESS for energy efficiency in their order of importance. The findings further identified reduction in air pollution, carbon footprint reduction, efficient control of energy usage, increased energy security, and market creation for energy-efficient products as the top benefits of adopting ESS. The study conclusively opined that the adoption of ESS will significantly reduce the atmospheric carbon footprint, pollution, and energy cost among others. A robust multi-disciplinary collaboration among stakeholders and political will is recommended to increase the capability of ESS to fulfill its sustainable potential in the BE.

IoT Based Implementation of Power Saving and Gas Leakage Detector

The implementation of IoT based power saving and gas leakage detector is an innovative approach to reduce energy consumption and enhance safety in households and commercial buildings. This system utilizes smart sensors to detect gas leaks and turn off power in rooms where there is no human presence. The sensor data is transmitted to a central server or cloud-based platform, which triggers alarms and alerts to notify residents and building managers of any potential safety hazards. The implementation of this IoT based solution can significantly reduce energy costs and improve safety by providing real-time monitoring and control of energy usage and gas leaks in buildings.

Isolation and Identification of Acinetobacter Spp. from Various Clinical Specimen and their Antibiotic Susceptibility Pattern in PDU Medical College, Rajkot, Gujarat, Western India

Introduction: Up to 25% of healthy adults exhibit cutaneous colonization by Acinetobacter and are the most common Gram-negative bacteria carried on the skin of hospital personnel. They are opportunistic pathogens causes a number of outbreaks of infections but their predominant role is in intensive care units. Such infections are often difficult to treat because of widespread resistance to the major groups of antibiotics. Materials and Methods: Various samples were collected aseptically and transported immediately to the bacteriology laboratory. The pathogens were identified by standard laboratory procedures including Gram’s staining, motility, culture, colony characters and biochemical reactions. Antimicrobial susceptibility testing was performed by modified Kirby Bauer method as per the CLSI guidelines. Result: 128 (3.11%) Acinetobacter spp. were isolated from 4112 specimens. Out of these, 72 from general wards and 46 from ICU and 10 from opd. Males (59.37%) are predominant than females (40.62%). The isolates sensitivite to Meropenem (83.59%) followed by Pipracillin-tazobactum (66.41%), Tetracycline (58.59%). Maximum resistance was observed to Cefotaxime (93.75%) followed by Ceftazidime (92.19%) & Cefepime (89.06%). Conclusions: Acinetobacter are the “superbugs” of the modern hospital environment causing significant infections in specific patient populations, especially in patients of ICU which are prone to cause infections due to over use of broad spectrum antibiotics. Awareness to maintain good housekeeping, equipment decontamination, strict attention to hand washing, isolation procedures and control of antibiotic usage, especially in high-risk areas, appear most likely measures to control the spread of Acinetobacter spp. in hospitals.

Using AI to Control the Cost of a Buffet Restaurant

This paper focuses on the application of AI technology to control costs in the buffet industry, using the example of the restaurant KAMII as a case study. Our analysis of KAMII and the buffet industry overall has revealed that a significant proportion of operational issues are related to cost control. Moreover, there is also room to reduce restaurant costs. To address these challenges, we have drawn inspiration from Haidilao’s “Smart Cloud Migration” technology and propose to leverage AI for dish prediction and ingredient usage control. By doing so, we aim to achieve cost control not only for KAMII, but also for the broader buffet industry, as well as the catering industry. Ultimately, the project aims to generate practical solutions for real-world problems.

Risk and UCON-based access control model for healthcare big data

The rapid development of healthcare big data has brought certain convenience to medical research and health management, but privacy protection of healthcare big data is an issue that must be considered in the process of data application. Access control is one of the methods for privacy protection, but traditional access control models cannot adapt to the dynamic, continuous, and real-time characteristics of healthcare big data scenarios. In this paper, we propose an access control model based on risk quantification and usage control (RQ-UCON). The model adds a risk quantification module to the traditional UCON model to achieve privacy protection of medical data. This module classifies risks into direct and indirect risks and quantifies them based on the physician's visit history. The model stores the quantified risk values as subject attributes. The RQ-UCON model uses an improved Exponentially Weighted Moving Average (EWMA) and penalty factors to predict risk value and to update the risk values of the subject attributes in real-time. The RQ-UCON model uses agglomerative hierarchical clustering to cluster the risk values of physicians within the department, resulting in risk intervals for each physician's operational behavior. Each risk interval is stored as a condition in the RQ-UCON model. Finally, according to the model whether the subject attributes meet the model conditions to determine whether the subject has the corresponding access rights, and according to the risk interval to grant the subject the corresponding access rights. Through the final experiment, it can be seen that the access control model proposed in this paper has a certain control on the excessive access behavior of doctors and has a certain limitation on the privacy leakage of healthcare big data.

Classification and Review of Variable Displacement Fluid Power Pumps and Motors

Displacement control of positive displacement machines has been a part of fluid power since the early days. Some of the early hydraulic presses already used two different displacement settings, though this was realised by using two different pumps rather than changing the displacement. Later, radial motors with variable stroke length appeared, followed by other designs of variable machines, such as swashplate machines, bent-axis machines, and variable vane machines. All these solutions control the displacement by varying the volume difference of the displacement element – but there are other ways of achieving this. Most have not passed the research state, but some are commercially available. In this paper, different ways of varying the displacement are presented and classified. The classification divides concepts into either control of displaced fluid or control of usage of displaced fluid. In turn, these concepts can be either on system level or displacement element level. This results in four main classes, which to some extent can describe the characteristics of the control.

DATAVAULTS APP: PERSONAL DATA PLATFORM IN THE SMART CITIES DOMAIN AND ITS POTENTIAL INTEGRATION INTO IDS ARCHITECTURES (INTERNATIONAL DATA SPACE)

Current data sharing architectures, like International Data Space – IDS, still lack maturity and certain requirements or functionalities that prevent them from being complete solutions when it comes to implementing intelligent, exploitable, secure, and reliable data spaces on which to develop a healthy data economy. One of these main shortcomings is the treatment of personal data and it is that these reference models are highly oriented to guarantee the sovereignty of the data for industrial data, and therefore the access control and exploitation of personal data is out of their scope, forgetting the exceptional privacy and usage conditions that must be considered in this type of data. In this paper we present the DataVaults project, and the platform implemented to allow the discovery of this kind of data and at the same time, control that only those who have been specified by the owner user have access and under the terms that he has previously established. Our approach allows the exchange of information not to be limited to industrial or business domains, where sharing is focused only on impersonal industrial data. The validation will be carried out in cases of use started in Smart Cities for the treatment of data and decision-making of citizens. Key Words: Data sharing, International Data Spaces, personal data privacy, access and usage control.

Accurate and Rapid Measurement of Soil Dry Depth Using Ultrasonic Reflection Waves

Soil dry depth is a key parameter that determines soil fertility and nutrient availability, ultimately affecting crop yield and quality. However, accurately measuring the dry depth of soil has been a challenge. In this work, we propose using reflective ultrasonic waves to measure dry depth in soil. Four soil types, including clay, sandy loam, silty loam, and sandy were prepared and the feasibility of the method was demonstrated through theoretical analysis. An experimental measurement system was established to verify the consistency between ultrasonic measurements and manually measured values. Two statistics were used in Ordinary Least Squares (OLS) regression to evaluate the model fit: R-square (R2) and Root mean square error (RMSE). The results indicate that the proposed method provides a higher accuracy in estimating the dry depth of sandy loam and silty loam (R2 values of 0.9899 and 0.992 for sandy loam, RMSE values of 1.57% and 1.5% for silty loam) than those of the clay and sandy samples (R2 values of 0.9896 and 0.9874 for clay, RMSE values of 1.66% and 1.77% for sandy). The maximum measurement errors for all the soil type predictions are below 6%; the overall accuracy was acceptable. Our findings suggest that ultrasonic measurement is an efficient and cost-effective approach for measuring soil dry depth, which could enable the precise control of irrigation water usage and the conservation of valuable water resources.

Trace Y for as-cast Ti6Al4V to simultaneous enhance strength-ductility

The introduction of rare earth element yttrium helps Ti6Al4V overcome the strength-ductility trade-off through matrix deoxidation and grain refinement. However, strict usage control is necessary in this process. In this work, the effect of yttrium content on the mechanical properties of Ti6Al4V-xY (x = 0, 0.1, 0.3, 0.5, 0.7) was studied. The results show that the alloy containing 0.1% Y has the highest elongation, while the alloy containing 0.3% Y has the highest tensile strength and the elongation is not significantly reduced. This is because the trace Y contributes to the deoxidation of the matrix, and the product Y2O3 can refine the grains through the Zener effect. On the contrary, excessive oxide particles will lead to stress concentration at the tip, thus increasing the probability of fracture. This work provides rich data and unique insights for Y enhancing mechanical properties of Ti6Al4V.

Occurrence, distribution, and ecological risks of antibiotics in Honghu Lake and surrounding aquaculture ponds, China.

Antibiotics are largely applied in aquaculture to increase production and control diseases, while how the antibiotics used in pond farming influence the distribution of antibiotics in receiving water seasonally is still not well understood. In this study, the variations of 15 frequently used antibiotics in Honghu Lake and surrounding ponds were investigated seasonally to figure out the impact of pond farming on antibiotics distributions in Honghu Lake. Results showed that the antibiotic concentrations in fish ponds ranged from 11.76 to 389.8ng/L, while in crab and crayfish ponds were lower than 30.49ng/L. The predominant antibiotic in fish ponds was florfenicol, followed by sulfonamides and quinolones, with generally low concentrations. Sulfonamides and florfenicol were the main antibiotics in Honghu Lake, affected by the surrounding aquaculture water partially. The antibiotics residue in aquaculture ponds showed obvious seasonal characteristics, with the lowest in spring. From summer, the concentrations of antibiotics in aquaculture ponds gradually increased and reached a peak in autumn, and the seasonal variation of antibiotics in the receiving lake was also related to the antibiotics in the aquaculture ponds. Risk assessment analysis showed that antibiotics such as enrofloxacin and florfenicol in fish ponds posed a medium and low risk to algae, and Honghu Lake acted as a natural reservoir of antibiotics and poses increased risks to algae. In general, our study demonstrated that aquaculture represented by pond farming brought significant risks of antibiotic pollution to natural water bodies. Therefore, reasonable control of the fish antibiotics usage in autumn and winter, as well as the rational use of antibiotics in aquaculture and the use of antibiotics before pond cleaning, is required to reduce the migration of antibiotics from aquaculture surface water to the receiving lake.

SG-APSIC1074: Trend of ‘ESKAPE’ and their susceptibility changes for meropenem and levofloxacin during the pandemic at Sardjito Hospital Yogyakarta Indonesia

Objectives: The bacteria in the ‘ESKAPE’ group are monitored due to their ability to resist antibiotic action. During the COVID-19 pandemic at our hospital, the usage of meropenem and levofloxacin as the empirical treatment for bacterial pneumonia increased and might have contributed to the antimicrobial resistance problem. In this study, we evaluated the ESKAPE group infection rates and their susceptibility to antibiotics in Dr. Sardjito Hospital, a referral and academic hospital in Yogyakarta, Indonesia. Methods: Data for ESKAPE pathogens in 2019–2021 were taken from the microbiology laboratory of Dr. Sardjito Hospital and were evaluated. Results: The proportion of ESKAPE isolates among positive cultures during 2019–2021 slightly increased from 49.4% to 48.4% to 50.7% each year (P > .05). The dominant ESKAPE infections were pneumonia, bloodstream infection, and urinary tract infection by K. pneumoniae, and wound infection by P. aeruginosa. The susceptibility pattern of ESKAPE to meropenem decreased from 72% in 2019 to 68% in 2020 but increased to 84% in 2021. To levofloxacin, the susceptibility pattern was decreased in a fluctuating trend from 68% in 2019 to 33% in 2020 and to 39% in 2021. During the COVID-19 pandemic (2020–2021), the pattern of ESKAPE infections was similar to that of 2019. In descending order, the frequency rank was K. pneumoniae, P. aeruginosa, A. baumannii, Enterobacter spp, and S. aureus. The proportions of MDR isolates increased from the prepandemic period to the COVID-19 pandemic era for E. faecium (from 5% to 24.4%), for A. baumannii (from 9.6% to 38.5%), and for P. aeruginosa (from 7.4% to 13.5%) (P < .05). These patterns did not differ between non–COVID-19 patients and COVID-19 patients. These results highlight the general impact of overused antibiotics beyond COVID-19 patients. Usage of watched and restricted antibiotics must be more controlled because bacterial coinfection and superinfection in COVID-19 patients was relatively low. Conclusions: During the COVID-19 pandemic, ESKAPE infections increased and their susceptibility to meropenem and levofloxacin decreased. Tight control of antibiotic usage is needed.