Indirect Data Research Articles

Development of a Machine-learning-based Framework to Assess the Performance of Water Distribution Systems

Recent statistics indicate that the national water supply coverage is approximately 99%, reflecting a high level of service. However, the aging infrastructure continues to cause issues such as pipe failures and water quality concerns, creating operational difficulties. To solve these issues, performance assessments are used to quantitatively evaluate the system conditions and ensure effective maintenance. In Korea, these assessments are based on a scoring system that combines direct and indirect assessments. However, direct assessment of all pipes is limited by cost and time constraints. To address this issue, a deep neural network is used to assess the aging of water distribution systems. This study develops a framework to estimate direct results from indirect data by analyzing the correlation between indirect and direct assessments. Additionally, data augmentation is considered to compensate for the lack of training data in direct assessments, improve the reliability of performance assessments, and support better prioritization in system maintenance.

Business Strategy Analysis for Business Development on Boat Rental at PT Prima Sentosa Abadi Services in Samarinda

This research aims to identify and analyze the internal and external factors faced in developing the ship rental business at PT Pelayaran Prima Sentosa Abadi Samarinda, as well as analyze and determine appropriate strategies for developing the ship rental business at PT Pelayaran Prima Sentosa Abadi in Samarinda. This research uses quantitative and qualitative methods with techniques for collecting data from primary and secondary data. Primary data was collected by interviewing informants regarding the answers to questionnaires regarding boat rental at PT Pelayaran Prima Sentosa Abadi in Samarinda, and secondary data was obtained from indirect data from informants. Internal factors in developing the ship rental business at PT Pelayaran Prima Sentosa Abadi Samarinda include strengths and weaknesses. The strength factor has a total value of 2.32, as obtained from the answers to the questionnaire. Meanwhile, the weakness factor was 0.96, which means the total internal factor value was 3.28. External factors faced in developing the ship rental business at PT Pelayaran Prima Sentosa Abadi Samarinda are opportunity and threat factors where the opportunity factor has a total value of 1.57 and the threat factor from the results of the questionnaire answers with a total value of 1.38, which means the total value of external factors is 2.95.

Angiotensin 1-7 – a peptide that increases the resistance of the heart to ischemia and reperfusion: narrative review

Background. The high mortality rate among patients with acute myocardial infarction (AMI) is an important problem of modern cardiology. In recent years, there has not been a significant decrease in mortality in AMI. Drugs used to treat AMI are not effective enough, so there is a need to develop fundamentally new drugs that can significantly increase the heart’s tolerance to ischemia/reperfusion (I/R). Angiotensin 1-7 peptide, which can increase cardiac tolerance to I/R by activating Mas receptor in myocardial tissue, could become a prototype of such drugs. The following enzymes are involved in the formation of the cardioprotective effect of angiotensin 1-7: NO-synthase, soluble guanylyl cyclase, phosphoinositide 3-kinase, extracellular signal-regulated kinases-1/2, Akt kinase and, possibly, protein kinase G. Indirect data indicate that the hypothetical end effector in the cardioprotective impact of angiotensin 1-7 could be mitochondrial or sarcolemmal ATP-sensitive K+ channel.Aim: To review 1-7 role in increasing the heart resistance to ischemia and reperfusion. The literature search was carried out in the PubMed database with queries “angiotensin 1-7 receptors”, “stress”, “angiotensin 1-7”, “mas receptor”, “cardioprotective effects of angiotensin 1-7”.

Smolensk in the Book Tradition of Russia of the XVI Century

The article examines a number of ancient Russian works dating back to the XVI century, in which Smolensk is at the center of the narrative. On the basis of indirect data, the author concludes about the possibility of the appearance of these plots on the Smolensk land, possibly in the form of folk legends, and then the emergence of a literary version based on them, recorded in the sources of the XVI century. The appearance of these plots in the XVI century was not accidental. In 1514, Prince Vasily III of Moscow annexed Smolensk to his possessions. The annexation of an ancient Russian city with a rich history and tradition required legitimization. Literature has become a way of including Smolensk in the ethnocultural space of the Moscow state.

Live Memory Forensic: Capture and Analyzing Volatile Data

As almost 90% of malware is resident in memory, live memory forensics is an essential part of cybersecurity. Live memory forensics refers to the process of analyzing computer RAM or volatile memory (which is lost after rebooting) while the computer is running. This article provides depth on live memory forensics, which is key in the detection and analysis of cyber threats and forensics investigations. Case studies and actual events demonstrate how this method can detect unauthorized access and discover hidden malware, which will help law enforcement investigators. The practical uses of Live Memory Forensics are illustrated using real world examples. Currently, live memory forensics are faced with the temporal nature of volatile data, other technical challenges, the instantiation of indirect data related to data privacy, and evidence handling problems. The paper emphasizes the importance of moral attitude and careful handling of data to keep the forensic process incorrupt. Investigators and cybersecurity professionals should now have a good understanding of live memory forensics and how to utilize live memory forensics to enhance security across borders, not just as a detective technique.

Limitations in creating artificial populations in agent-based epidemic modeling: a systematic review

Introduction. The key step in agent-based modeling of epidemics, which allows researchers to take into account individual characteristics of people, is the creation of an artificial population. The main difficulty of this procedure is finding a balance between the detail of the population description and the computational efficiency of the calculations. The aim and objectives of the review: Critically analyze and summarize the current evidence on how to create artificial populations; evaluate the limitations and advantages of available approaches in solving various problems in epidemiology. Materials and methods. An analysis of literature sources devoted to agent-based modeling has been performed. The analysis is focused on algorithms for creating an artificial population with a given level of detail for modeling human respiratory infections. Results. The approaches to the creation of artificial populations are generalized. The main principles of realization of interaction between agents are revealed: by means of networks of contacts between agents and on the basis of taking into account the movement of agents between locations. The first approach is the most computationally efficient and simple; the second approach allows to better take into account the change in the behavior of agents during the development of the epidemic process. Conclusion. Agent-based modeling is an optimal tool for selecting the best scenario for epidemic control and investigating the role of individual characteristics of people in the development of epidemics. When creating an artificial population, it is important to include in the model factors that can be targeted for control. A significant limitation is the lack of factual data on population structure, but this can be overcome by using indirect data.

Kureika–Tunguska Composite Tectono-Sedimentary Element, northern East Siberia

The Kureika–Tunguska Composite Tectono-Sedimentary Element (KT CTSE) is located in East Siberia. Geologically, it is confined to the homonymic basin in the northwestern part of the Siberian Craton. The basement of the basin is composed of Archean–Early Proterozoic metamorphic rocks. The sedimentary cover is composed of Mesoproterozoic, Neoproterosoic and Early Paleozoic predominantly carbonate rocks capped with a succession of Pennsylvanian–Permian coal-bearing sediments overlain by thick section of Early Triassic tuffs and lavas. The entire sedimentary cover, especially its upper part, is saturated with mafic intrusive bodies. The maximum depth to the top basement can exceed 10 km. The KT CTSE is characterized by a very low degree of exploration. The rather scarce prospecting work carried out on oil and gas in the CTSE has not yet yielded positive results. However, indirect data such as, for example, numerous bitumen fields and evidence of the source rocks are promising for potential discoveries including large hydrocarbon accumulations.

Estimating the Ebro river discharge at 1 km/daily resolution using indirect satellite observations

Estimating river discharge Q at global scale from satellite observations is not yet fully satisfactory in part because of limited space/time resolution. Furthermore, on highly anthropized basins, it is essential to anchor the analysis to reliable Q measurements. Gauge networks are however very sparse and limited in time, and SWOT (Surface Water Ocean Topography) river discharge estimates at global scale are not yet available. The method proposed here is able to obtain continuous daily Q estimates at 1 km/daily resolution, using indirect satellite data and ground-based estimates. We focus here on the Ebro. Over such an anthropized basin (e.g. change of land use, irrigation), the exploitation of 205 available gauges at their nominal resolution (i.e., daily point measurements) is a necessity. The hydrological Continuum model is used to help interpolate spatially and temporally the observations into our optimal interpolation scheme. The proposed Q-mapping is similar to an assimilation scheme were Earth observations (precipitation, evapotranspiration and total water storage change) and model simulations are constrained by in situ gauge measurements. The Q estimates are evaluated using a rigorous leave-one-out experiment, showing a good agreement with the in situ data: a correlation of 0.72 (median), and a 75th percentile of Nash-Sutcliffe Efficiency up to 0.62. Our spatio-temporal continuous Q estimates at high spatial/temporal resolution can describe complex continental water dynamics, including extreme events. SWOT estimates will soon be available, at the global scale but with irregular space/time sampling: our method should help exploit them to obtain a regular space-temporal description of the water cycle at high resolution.

원주이씨 해남문중의 『용하도록』과 지역사 정보

In this article, we analyzed the 『Yonghadorok(用下都錄)』 owned by WonjuLee clan(原州李氏) and examined the area of Durak(斗落) in the Haenam region , the problem of place names, the opening of Mokpo Port and the rice crop house, and the drought in the Haenam region during the Japanese colonial period. The average area of 1 durak in 『Yonghadorok』 is 214 pyeong(坪), which is larger than the average of 200 pyeong in Haenam Country. And out of the 12 places analyzed, there are as many as 4 places that deviate from 200 pyeong to 10% error of 180~220 pyeong, and among them, 2 places are close to 300 pyeong. Thus, it can be seen that even within the same municipality there was a great deviation in the area of 1 durak. 『Yonghadorok』 conveys micro-place names that have not been recorded in the existing research. Accordingly, the analysis of Yonghagi(用下記) can be said to be local history information that can supplement the study of place names at dong(洞) levels. On the other hand, if you look at the 『Yonghadorok』, the same place name is written in different Chinese characters depending on the writer, which shows that even the local literate class was not well versed in the origin of the place names in their own region. The Haenam(海南) area belongs to the Mokpo cultural area, where Mokpo Port can be easily accessed by ship. With the opening of the port of Mokpo Port, the price of rice skyrocketed. Specifically, the price of rice in Haenam and Yeongam(靈巖) region soared 2 times and 2.42 times, respectively. The crop status of Yonghagi is an indirect data that can grasp the drought at the city and county level as a time series. As a result of the analysis, through in 1901, 1912, 1938, and 1942~1943, when droughts occurred in Jeolla Province(全羅道), in Haenam region the average or abundant crops were harvested. As a result, it was possible to specifically observe that the weather-related information at the Province(道) level cannot be applied to the city and county level as it is.

THE EFFECT OF PRICE AND ADVERTISING PROMOTION ON THE INTEREST OF ONLINE TRANSPORTATION SERVICE USERS

This research aims to analyze the influence of price and advertising promotion on people's interest in using Grab online transportation services. The approach used is a nonprobability sampling technique, namely purposive sampling. The data were statistically analyzed using validity test, reliability test, classical assumption test, multiple linear regression, and determination test (R2). The data source used in this study is primary data using the help of SPSS 25.0 software data analysis tools. The subjects of this study are 78 respondents who use Grab online transportation services with a data collection method using questionnaire distribution. In addition, secondary data is obtained from indirect data sources such as articles and journals. The results of the analysis show that price variables have a positive and significant effect on people's interest in using Grab online transportation services. Meanwhile, the variable of advertising promotion has no effect on people's interest in using Grab online transportation services. The test simultaneously produced prices and advertising promotions that had a positive and significant effect on people's interest in using Grab online transportation services.

Observational evidence for groundwater influence on crop yields in the United States

As climate change shifts crop exposure to dry and wet extremes, a better understanding of factors governing crop response is needed. Recent studies identified shallow groundwater-groundwater within or near the crop rooting zone-as influential, yet existing evidence is largely based on theoretical crop model simulations, indirect or static groundwater data, or small-scale field studies. Here, we use observational satellite yield data and dynamic water table simulations from 1999 to 2018 to provide field-scale evidence for shallow groundwater effects on maize yields across the United States Corn Belt. We identify three lines of evidence supporting groundwater influence: 1) crop model simulations better match observed yields after improvements in groundwater representation; 2) machine learning analysis of observed yields and modeled groundwater levels reveals a subsidy zone between 1.1 and 2.5 m depths, with yield penalties at shallower depths and no effect at deeper depths; and 3) locations with groundwater typically in the subsidy zone display higher yield stability across time. We estimate an average 3.4% yield increase when groundwater levels are at optimum depth, and this effect roughly doubles in dry conditions. Groundwater yield subsidies occur ~35% of years on average across locations, with 75% of the region benefitting in at least 10% of years. Overall, we estimate that groundwater-yield interactions had a net monetary contribution of approximately $10 billion from 1999 to 2018. This study provides empirical evidence for region-wide groundwater yield impacts and further underlines the need for better quantification of groundwater levels and their dynamic responses to short- and long-term weather conditions.

Phyformer: A degradation physics-informed self-data driven approach to machinery prognostics

Machinery degradation prognostics methods have been suffering the “dilemma” that both physics and data-driven methods have their own limitations. On one hand, constructing accurate close-form mathematical physics models are prohibitively difficult for a complex system. On the other hand, for pure data driven models such as deep learning models, due to the lack of physics guidance, their extrapolation capability decays over time and even yield unexplainable predictions that violate common cognition. Therefore, relaxing the pursuit for the perfect and accurate degradation model, and instead coupling general degradation model with deep learning model, fully leveraging the advantages from both physics-based prognostics and data-driven prognostics, is a promising way to solve the “dilemma”. Driven by this motivation, this paper proposes Phyformer, a general degradation physics-informed self-data-driven method for machinery prognostics. A backbone deep learning model based on auto-correlation and Transformer architecture is developed for time series data prediction. Multiple local physical models that are constructed with data in sliding time windows are embedded into the backbone model in the form of loss function. Only the historical data of the machine itself are used to extrapolate the future, which is significant especially for high-end equipment since their run-to-fail data are scarce. Then the predicted data are mapped to degradation stage by an unsupervised clustering model Gath-Geva adaptively without the requirement of knowing the number of degradation stages in advance. Due to the above nature, Phyformer is high flexibility, easy to be deployed in different applications, working condition-independent and simple. Two typical prognostics tasks are studied, which use direct and indirect condition monitoring data as input, respectively. Comparisons with other state-of-the-art machinery prognostics models show the advances of Phyformer.

The Specificity of Epizootic and Epidemiological Processes in Natural Foci of Hemorrhagic Fever with Renal Syndrome and Tick-Borne Encephalitis in Russia, as the Basis for the Prospects of Creating a Combined Vaccine for the Prevention of These Infections.

Hemorrhagic fever with renal syndrome (HFRS) and tick-borne encephalitis (TBE) are the most common viral diseases in Russia. HFRS is caused by six different types of hantaviruses: Hantaan, Amur, Seoul, Puumala, Kurkino, and Sochi, which are transmitted to humans through small mammals of the Muridae and Cricetidae families. TBE is caused by viruses belonging to five different phylogenetic subtypes. The similarities in the ecology of HFRS and TBE pathogens is presented here. Hantavirus-infected small mammals can transmit the virus to uninfected animals, and ticks can also transmit hantavirus to other ticks and mammals. Hantavirus transmission from ticks to humans is possible only hypothetically based on indirect data. Over the past 23 years, 164,582 cases of HFRS (4.9 per 105 people) and 71,579 cases of TBE (2.5 per 105 people) were registered in Russia. The mortality rate was 0.4% (668 cases) in HFRS and 1.6% deaths (1136 cases) in TBE. There were 4030 HFRS (2.5%) and 9414 TBE (13%) cases in children under 14 years old. HFRS and TBE cases were registered in 42 out of 85 Russian regions; in 18-only HFRS, in 13-only TBE, and 12 had no reported cases. The prospects of applying a combined vaccine for HFRS and TBE prevention are shown in this paper.

Which Is The Role of Social Media in Web-Based Adolescent NonSuicidal Self-Injury (NSSI)?

In recent years, there has been a significant surge in non-suicidal self-injury (NSSI)-related content on the Internet. In fact, the technology landscape rapidly evolved, with social media now playing a pivotal role in the lifestyle of the general population, particularly among youths and adolescents. The current review aims at overviewing all studies so far published investigating the relationship between social media and NSSI among adolescents, focusing on the motivations behind posting NSSI-related contents and the role that social media may play in the promotion and/or maintenance of NSSI behaviors. A comprehensive systematic literature review was carried out by using MEDLINE/PubMed. Following screening through established inclusion criteria, eleven studies were finally selected and here retrieved. Due to the high methodological heterogeneity, all studies were assessed and categorized, based on the type of data collection, in three groups: a) studies using direct data (e.g., interviews/surveys); b) indirect data (e.g., content analysis on social media); and, c) mixed data. Major findings reported that social media may significantly influence the development and maintenance of NSSI behaviors. Those victims of cyberbullying often seek out pro-self-harm contents, to both normalize the behavior and/or seek peer-to-peer emotional support. Social media platforms facilitate the dissemination of self-harm techniques and encourage competition among users, exacerbating the severity of self-injury. Interviews highlighted motivations such as attention-seeking, expressing emotions, and feeling part of a group. Other studies showed that social media contents often contain both supportive and harmful advice regarding self-harm. Social media could cover a dual role in both providing support and triggering self-harm through exposure to harmful content(s). Furthermore, social media could also offer opportunities for positive interventions (i.e., awareness campaigns, mental health resources, etc.). Mental health professionals should be aware about the impact of social media on youngsters, as well as providing a routine assessment on social media use in their clinical practice. Future research should explore the (bi)directional causal role of social media on NSSI and viceversa, as well as developing preventive and treatment strategies to support young people to disincentive NSSI behaviors via social media.

Low-, moderate-, and high-risk obesity in association with cost drivers, costs over the lifecycle, and life expectancy

BackgroundThe prevalence of low-, moderate-, and high-risk obesity has been increasing globally. Our aim was to estimate the societal burden of these three obesity classes in the Austrian population by taking a societal–annual perspective and an individual–life-cycle perspective. Secondly, we sought to identify the respective cost drivers and the effects on life expectancy.MethodsWe used population-weighted survey data on the distribution of body mass index (BMI) and data on relative risks regarding 83 diseases. Using fractional polynomial regressions, we estimated relative risks per BMI unit for about 30 cost-intensive diseases up to BMI values of 50. The approach for the cost analysis was based on the use of population-attributable fractions applied to direct medical and indirect cost data. Macro-disease-specific data regarding cost factors came from cost-of-illness statistics and administrative sources.ResultsAbout 8.2% of deaths and 4.6% of health expenditure are attributable to obesity in Austria in 2019, causing 0.61% of GDP loss. A third of annual direct and indirect costs came from class 2 and class 3 obesity. From an individual perspective, life-cycle costs of class 2 and class 3 obesity were 1.9 and 3.6 times the costs of class 1 obesity, respectively. At the age of 45, people with high-risk obesity are about to lose approximately 4.9 life years and 9.7 quality-adjusted life years.ConclusionsWe have extended the method of population-attributable fractions, allowing us to estimate differences in the life-cycle direct medical and indirect costs between low-, moderate-, and high-risk obesity. We found that the lifetime costs of obesity are strikingly different between obesity classes, which has been veiled in the societal—annual perspective. Our findings provide a foundation for evaluating public health interventions aimed at combating obesity in order to mitigate the escalating individual and societal burden resulting from obesity prevalence and complications in the future.

Community Empowerment in the Development of Bayan Tourism Villages in North Lombok District

Community empowerment is an important aspect in developing tourist villages. This is because the development of tourist villages uses a lot of resources owned by the community. The community has an important role in supporting the success of tourism village development so that powerless communities need to be empowered to create independence and economic prosperity for the community. This type of research is qualitative research using data collection techniques, namely interviews, documentation, observation, focus group discussions and literature studies. Interviews are a data collection method with both direct and indirect data sources. This study examines tourism potential, the role of the community and how to empower the community. Data sources were obtained from the head of Bayan Village, the head of the tourism awareness group, traditional leaders of Bayan Village and the community in Bayan Village to serve as sources. The village can be used as a tourist attraction so that it can invite tourists to come to the Bayan Tourism Village. The existence of this tourist village can increase income opportunities for the community and reduce unemployment. Empowerment is carried out by providing training to the Bayan village community about tourism so that they can take advantage of the opportunities that exist in the Bayan tourist village and can create their own employment opportunities. Having a tourist village can empower the community in Bayan Village, North Lombok Regency.

An evolutionary game model for indirect data sharing in manufacturing big data consortium

In the context of the explosive growth of manufacturing data, a manufacturing big data consortium is a collaborative organization aimed at promoting efficient decision-making and technological innovation. It is of vital significance to study how to effectively promote the data sharing among the members of manufacturing big data consortium. In this paper, we propose an evolutionary game model to investigate how to facilitate data sharing in the manufacturing big data consortium. Then, we analyze the synergistic revenue allocation method based on the indirect data sharing mode, and calculate the probability of the ideal event. We explore the influencing factors of data sharing in the manufacturing big data consortium by simulating Evolutionary Stable Strategies. Our findings reveal that the initial willingness of participants has a profound impact on their sharing behavior. Furthermore, the optimal interval revenue allocation coefficient can improve the probability of the manufacturing big data consortium to share data. Factors such as incentive revenue and social penalties positively influence the evolution towards active sharing strategies. In contrast, factors such as speculative revenue and data sharing costs inhibit the evolution towards active sharing strategies.

A comprehensive approach for assessing social flood vulnerability and social flood risk: The case of Denmark

Flood risk assessment approaches have traditionally been dominated by measures of economic damage. However, the importance of understanding the social impacts of flooding are increasingly being acknowledged. Social vulnerability indices have been constructed in diverse geographical contexts to understand relative susceptibility of different social groups to flood hazards. However, integrated assessments of social vulnerability, exposure, and hazard information are lacking. Here, we construct a national social vulnerability index (SVI) for Denmark and combine this with direct and indirect social exposure data and coastal flood hazard data to construct a national social flood risk index (SFRI). Results show the spatial distribution of social flood vulnerability and social flood risk in Denmark. Our findings illustrate that including social data in flood risk assessment could significantly change our understanding of flood risk on a national scale. Methodologically, our work introduces a comprehensive flood risk modelling approach that explicitly considers the social impacts of flooding in all model components. The application of this model in Denmark reveals that the social impacts of flooding extend far beyond flooded areas, thus highlighting the importance of explicitly considering direct and indirect social exposure in addition to social vulnerability in flood risk assessment. By introducing a comprehensive, socially specific approach to flood risk assessment that is usable within existing risk management frameworks such as the EU Floods Directive, our work aims to mainstream social wellbeing, resilience, and justice as central considerations in decision making on flood risk management.

Social Media As Source Study Generation Millennials

One of the lifestyles of the younger generation, better known as the Millennial Generation, in using smartphones, is searching for information and buying and selling on the Internet. This of course includes accessing social media and using it as a source of learning material, which currently supports a lot of educational content. Social media can be integrated into Millennial Generation learning where the use of social media and learning must be planned as one. This research uses a quantitative descriptive approach, using indirect data collection techniques in the form of questionnaires that describe the variables studied and examine the relationships between variables. Based on the results of this research, at the effectiveness stage, social media is used by students more to dig up information on social media accounts such as YouTube and Tiktok . YouTube can be used as a learning tool to have a positive impact on students by increasing learning motivation, creativity and friendship between friends, so that social media can be used effectively as a learning tool. These two accounts are the accounts most followed by students. Based on the explanation of the findings above, it can be concluded that the first and second hypotheses are accepted, namely that there is a positive relationship between the Role of Social Media (X) and Effective Learning Resources (Y) in the millennial generation, namely students and high school students in Sukabumi.

Effect of carnitine supplementation on energy utilization in patients with type 2 diabetes and long-term tube feeding: A CARE-compliant case report

Introduction: Carnitine is essential for the energy utilization of long-chain fatty acids. However, the effects of carnitine supplementation on patients undergoing tube feeding remain unclear, and some enteral formula products do not contain carnitine. In order to gain insights into the role of carnitine supplementation on energy utilization in patients with long-term tube feeding, we observed the changes in respiratory quotient (RQ) of patients before and after the addition of carnitine due to the renewal of an enteral formula product. Case presentation: We observed 6 patients who continued tube feeding with the same enteral formula product scheduled for renewal. All 6 participants had diabetes, and indirect calorimetry data were available for 4 patients. Participants were observed for 3 months after switching to the new formulation. After the switching, a carnitine supplementation of 120 to 180 mg/day was provided, depending on the intake amount. One month after switching, blood free carnitine and total carnitine levels in all 6 patients increased from below the lower limit to within the range of the Japanese reference standard. In 3 of the 4 patients for whom indirect calorimetry was possible, the fasting RQ at baseline was >0.90, suggesting impaired lipid utilization. The mean fasting RQ significantly decreased 2 months after the switch. The 1- and 2-hour postprandial RQ also showed a significant decrease after switching. Conclusion: Carnitine supplementation of enteral formulas may be important for normal energy utilization of lipids in patients receiving long-term tube feeding. An evaluation using randomized controlled trials with a larger number of patients is required.