Policy Monitoring Research Articles

Qualitative Review of Monitoring and Evaluation Practices in Higher Institutions in Uganda

Purpose: The purpose of the study was to investigate how the practices employed in the Monitoring and Evaluation processes contribute to the overall goal of Higher Education Institutions in Uganda. It was carried out using a qualitative document review method. The study was guided by five objectives: to examine the legal framework of monitoring and evaluation in Uganda’s higher education institutions, to formulate monitoring and evaluation policy in higher education institutions, to assess the establishment of constituent colleges of Makerere university, to examine how monitoring and evaluation policy affects university teaching quality, and to assess how the M & E policies are performed at the university senates and council committees.
 Findings: The findings of the study show that the Uganda Ministry of Education and Sports (MoES) has prioritized the concept of quality assurance in the sector at all education levels. Each college at Makerere University is administered as a semi-autonomous entity within the larger university and the overall supervision of the college is the responsibility of the university council and it is the responsibility of College leadership to conduct regular M&E of services offered in their units to ensure that quality is not compromised. Student evaluation of teaching (SET) is used in Makerere university where questionnaires are given to students to evaluate the quality of instruction by their instructors at the end of every lecture, course or semester. There is also peer observation of teaching where colleagues from the same department, subject or discipline help in giving and receiving feedback from one another on the quality of teaching and effectiveness.
 Recommendations: However, the study recommends that monitoring and evaluation should be implemented even in the secondary and primary education, institutions should have both internal and external evaluations for consistency and transparency, more research should be done on the challenges facing the established policies in higher education institutions of learning in Uganda.

Microplastic removal and management strategies for wastewater treatment plants

Discharging microplastics into the environment with treated wastewater is becoming a major concern around the world. Wastewater treatment plants (WWTPs) release microplastics into terrestrial and aquatic habitats, mostly from textile, laundry, and cosmetic industries. Despite extensive research on microplastics in the environment, their removal, and WWTP management strategies, highlighting their environmental effects, little is known about microplastics' fate and behaviour during various treatment processes. Microplastics interact with treatment technologies differently due to their diverse physical and chemical characteristics, resulting in varying removal efficiency. Microplastics removed from WWTPs may accumulate in soil and harm terrestrial ecosystems. Few studies have examined the cost, energy use, and trade-offs of large-scale implementation of modern treatment methods for the removal of microplastics. To safeguard aquatic and terrestrial habitats from microplastics' contamination, focused and efficient management techniques must bridge these knowledge gaps. This review summarizes microplastic detection, collection, removal and management strategies. A compilation of treatment process studies on microplastics’ removal efficiency and their destiny and transit paths shows recent improvement. Bioremediation, membrane bioreactor (MBR), electrocoagulation, sol-gel technique, flotation, enhanced filtering, and AOPs are evaluated for microplastic removal. The fate and behaviour of microplastics in WWTPs suggest they may be secondary suppliers of microplastics to receiving ecosystems. Innovative microplastic removal strategies and technologies such as nanoparticles, microorganism-based remediation, and tertiary treatment raise issues. These new WWTP technologies are examined for feasibility, limitations, and implementation issues. Pretreatment modifies microplastic size, adsorption potential, and surface morphology to remove microplastics from WWTPs. Membrane bioreactors (MBR) can remove 99.9% of microplastics more efficiently than other approaches. MBR systems require membrane cleaning and fouling control, which raises operational and capital costs. To reduce MPs, plastic alternatives and strict controls, including microplastic waste transformation, should be prioritized. Microplastics must be controlled through monitoring policy execution and awareness.

Monitoring tooth wear

Tooth wear is a multifactorial condition leading to the irreversible loss of dental hard tissues. Although tooth wear is mainly a physiological process, it can become pathological if the wear process is accelerated for various reasons. Since this process is not linear, but can sometimes be inactive and sometimes active, a careful monitoring policy is necessary. The possible monitoring tools are described in this article, and a proposal is made with regard to the frequency of the systematic and periodic collection of information. CPD/Clinical Relevance: The prevalence of tooth wear is increasing and it now carries the third highest risk (after caries and periodontitis) for maintaining the natural dentition.

ProMiSE: A High-Performance Programmable Hardware Monitor for High Security Enforcement of Software Execution

In recent years, to prevent computer systems from software attacks, hardware monitors are proposed as a type of efficient security enforcement scheme, which can detect software attacks at runtime. However, due to the limited flexibility of dedicated hardware monitors, one monitor can be only applied to a few targeted application scenarios, and is hard to defend against unconsidered attacks. This leads to high cost for redesigning monitors for new scenarios. Although recent studies propose flexible hardware monitors, the scope and security of the reconfigurable monitoring policies are still limited. To further improve the flexibility and security, this work proposes a monitor instruction set and multiple security-assisting designs for supporting general operations needed by various attack detection schemes. Based on the above efforts, an efficient programmable hardware monitor named ProMiSE is designed. After implemented on the RocketChip RISC-V processor, ProMiSE can be programmed to realize a wider range of monitoring policies with higher security and similar hardware resource overhead, compared with stateof-the-art flexible hardware monitors. With these advantages, ProMiSE still has the detection latency as low as 18-59 CPU cycles. The performance overhead ranges from 0%-23.4%, which is also reasonable compared with the dedicated hardware monitors of corresponding policies.

Exploring the Effect of Policies on Environmental Pollution Liability Insurance in China’s Highly Polluting Industries: Applying Ajzen’s Theory of Planned Behavior

ABSTRACT This paper investigates the effects of different types of government policies related to environmental pollution liability insurance (EPLI) and how these policies promote the demand for EPLI of polluting enterprises. Based on the theory of planned behavior (TPB), we establish a research framework to analyze the effects and mechanisms of the three different policies (mandatory, incentive, and monitoring policies). Our empirical results suggest that the mandatory and monitoring policies can effectively promote companies to buy insurance, but the incentive policies have no significant impact on the insurance demand overall. Furthermore, companies with more positive environmental attitudes are not sensitive to mandatory policies. Although the overall effect of incentive policies is not significant, they have a significant positive impact on the EPLI demand of non-state-owned companies. The monitoring policies prompt enterprises to purchase insurance by strengthening information disclosure and compliant production.

5.C. Skills building seminar: Leveraging local government policies to improve food systems for public and planetary health

Abstract Changing food systems is one of the most promising and impactful ways to address nutrition and health, climate change and environmental degradation. The International Network for Food and Obesity/NCDs Research Monitoring and Action Support (INFORMAS) developed the Healthy Food Environment Policy Index (Food-EPI) to measure the extent of implementation of healthy food environment policies by governments compared to international best practice. The Food-EPI provides a mechanism to assess government policies and infrastructure support to create healthy food environments. The Food-EPI tool covers seven food policy areas, including composition, labelling, promotion, prices, provision, retail and trade, and six measures of infrastructure, including leadership, governance, funding, monitoring, platforms and health-in-all-policies. The Food-EPI process includes the drafting of a comprehensive evidence document on the implementation of policies, verified by government stakeholders and the assessment of those policies, as well as identification of priority policy actions by an expert panel at the national level. The tool and process were pilot tested and implemented in New Zealand in 2014 and then again in 2017 and 2020. Since 2014, about 50 countries have implemented Food-EPI at the national level, including more than 10 European countries. There is increasing demand for a similar monitoring tool and process which can be used at the municipal/city government level to assess government actions addressing food systems for both public and planetary health. Local governments can often make more rapid progress than national governments, but on the other hand may not have jurisdiction in all critical policy areas. INFORMAS recently developed a new Food Systems Policy Index, based on a compilation of international recommendations for good practice government policies to address food systems and a scoping review on the potential effectiveness of the recommended good practice policies and interventions to improve nutrition and environmental sustainability outcomes. The new index covers policies addressing food supply chains and food environments, and is being implemented in a range of West and East African and European countries and cities. The purpose of the workshop is to discuss the role and potential of local level government (cities and municipalities) policies in addressing food systems to improve both public and planetary. The workshop will have several key presentations, some with a more global perspective and some with a very practical local perspective. Together with the panelists and the audience, the key opportunities and challenges will be discussed for European cities and municipalities to address food systems, as well as the role of monitoring and benchmarking policy implementation to increase local actions on food systems. Key messages • Monitoring and benchmarking the policy implementation to address food systems to improve public and planetary health by governments is key to increase accountability for action. • A better understanding on the role and potential of local government policies in addressing food systems can be beneficial to accelerate and innovate policy implementation.

Eye & Diabetes in Morocco: Where are we from the global screening guidelines?

Abstract In Morocco, the prevalence of diabetes in the adult population is 12.4% (WHO). Diabetic Retinopathy (DR) is the 2nd cause of blindness. Nearly 1 million people worldwide are blind due to diabetes. The aim of our work is to study the epidemiological profile of patients with diabetes in ophthalmology and to determine the observance of the follow-up guidelines. This is a descriptive study carried out at the Vision Clinic of Tetouan-Morocco, including all diabetic patients who presented to the ophthalmology consultation of the same doctor, between June 2022 and December 2022. The study involved 500 patients, including 217 men and 283 women, with an average age of 62 years. The average duration of diabetes was 11.5 years. 1 out of 3 diabetic patients was unaware that diabetes was a blinding disease and 3 out of 4 patients did not follow a specific diet. 1 out of 8 patients has an annual ophthalmological check-up. 55% of the patients have a screening every 2-5 years, when 7% haven't had their eyes checked in the last 10 years. Visual complaints accounted for 58% of the motivations for all consultations, while diabetes only accounted for 30%. Depending on the duration of the condition, diabetes represents 60% of the reasons for consultation among new diabetics (1 year) whereas it represents only 20% among diabetics over 10 years old. Eye examinations revealed a proliferative DR in 24% of the cases and a non proliferative DR in 22%. In 31%, there was no sign of DR and in 23%, the fundus was inaccessible due to cataract. The prevalence of proliferative DR increases with years of diabetes, reaching 40% in diabetics over 20 years old. The results of this work prove that diabetes is still underestimated by the Moroccan population. This is probably related to a lack of information of the target population. Thus, health professionals should strengthen their education in order to establish a better monitoring and screening policy aimed to reduce the occurrence of an avoidable blindness. Key messages • Less than one Diabetic out of 3 consults an ophthalmologist for their diabetes & Only one diabetic out of 8 consults annually in ophthalmology. • The older the diabetes, the less regular is the consultation in ophthalmology & One out of 4 diabetics will already have proliferative diabetic retinopathy at their ophthalmological consultation.

The relationship between dynamic monitoring network plans and eco-efficiency – New evidence from atmospheric quality monitoring policy in China

China’s rapid economic development in recent decades has come at a considerable environmental cost. This paper explores whether atmospheric quality monitoring policy (AQMP) improves eco-efficiency by using AQMP as a natural experimental group. We assessed the eco-efficiency of 285 cities in China from 2009 to 2019 using the super-efficient SBM model and estimated the impact of AQMP using the propensity score method Difference-in-Difference (PSM-DID) model. The key findings of this paper are as follows: First, AQMP can enhance eco-efficiency, promoting sustainable urban development. Second, governmental and non-governmental organizations play contrasting roles in either fostering or reversing the positive effects of AQMP. Factors like innovation, clean energy adoption, and industrial structure have a positive mediating influence. Finally, the impact of AQMP on eco-efficiency varies across cities, displaying heterogeneity. Specifically, AQMP has a positive effect on eco-efficiency in resource-rich cities, small and medium-sized urban centers, smart cities, and coastal areas. These findings carry significant implications for the establishment of dynamic monitoring networks and the advancement of eco-efficiency in emerging countries, including China.

Socio-Economic Value and Availability of Plant-Based Non-Timber Forest Products (NTFPs) within the Charcoal Production Basin of the City of Lubumbashi (DR Congo)

The overexploitation of forest resources in the charcoal production basin of the city of Lubumbashi (DR Congo) is reducing the resilience of miombo woodlands and threatening the survival of the riparian as well as urban human populations that depend on it. We assessed the socio-economic value and availability of plant-based non-timber forest products NTFPs in the rural area of Lubumbashi through ethnobotanical (100 respondents) and socio-economic (90 respondents) interviews, supplemented with floristic inventories, in two village areas selected on the basis of the level of forest degradation. The results show that 60 woody species, including 46 in the degraded forest (Maksem) and 53 in the intact forest (Mwawa), belonging to 22 families are used as sources of NTFPs in both villages. Among these species, 25 are considered priority species. NTFPs are collected for various purposes, including handcrafting, hut building, and traditional medicine. Moreover, the ethnobotanical lists reveal a similarity of almost 75%, indicating that both local communities surveyed use the same species for collecting plant-based NTFPs despite differences in the level of degradation of the miombo woodlands in the two corresponding study areas. However, the plant-based NTFPs that are collected from miombo woodlands and traded in the urban markets have significant economic value, which ranges from USD 0.5 to USD 14.58 per kg depending on the species and uses. NTFPs used for handicraft purposes have a higher economic value than those used for other purposes. However, the sustainability of this activity is threatened due to unsustainable harvesting practices that include stem slashing, root digging, and bark peeling of woody species. Consequently, there is a low availability of plant-based NTFPs, particularly in the village area, where forest degradation is more advanced. It is imperative that policies for monitoring and regulating harvesting and promoting the sustainable management of communities’ plant-based NTFPs as a priority, be undertaken to maintain their resilience.

The contributions of citizen science to SDG monitoring and reporting on marine plastics

The accumulation of plastic litter in marine environments is a major environmental challenge along with the difficulties in their measurement because of the massive size of the oceans and vast circulation of plastic litter, which is being addressed as part of the United Nations (UN) Sustainable Development Goals (SDGs). Citizen science, public participation in scientific research and knowledge production, represents a potential source of data for SDG monitoring and reporting of marine plastic litter, yet there has been no evidence of its use to date. Here, we show how Ghana has become the first country to integrate existing citizen science data on marine plastic litter in their official monitoring and reporting of SDG indicator 14.1.1b for the years 2016–2020, which has also helped to bridge local data collection efforts with global monitoring processes and policy agendas by leveraging the SDG framework. The results have been used in Ghana’s 2022 Voluntary National Review of the SDGs, and reported on the UN SDG Global Database, as well as helping to inform relevant policies in Ghana. In addition, here, we present a pathway that can be adopted by the relevant government authorities in other countries that have an interest in following a similar citizen science data validation and reporting process for this indicator and potentially others.

Fiscal monitoring and corporate investment

AbstractDoes state fiscal monitoring of local governments impact firms? Exploiting the staggered adoption of state fiscal monitoring policies, our results show that state fiscal monitoring of local governments increases corporate investment. Affected firms increase their investment by increasing capital expenditures as well as research and development expenditures. Additional analyses reveal that firms fund this increase in investment by decreasing share repurchases and issuing debt. We also provide evidence that the increase in corporate investment is driven by a reduction in local corruption.

The need for specificity in uncertainty communication is further supported: Preliminary evidence from eye tracking

Automation transparency is understudied in environments with varied automation reliability. We previously found uncertainty communication, a form of automation transparency, led to nuanced and unintentional performance outcomes in this type of environment. To better understand these outcomes, participants’ monitoring policies of automation were studied via a preliminary eye tracking analysis. In a simulated multi-UAV mission, 272 Naval Aviation trainees monitored three automated systems that were identical in function, but differed in reliability. Halfway through the experiment, uncertainty communication about the least reliable system was delivered as a chat message. Performance improvements coincided with a monitoring policy that had larger dwell times overall and one where the proportion of visual attention towards the automated system mentioned in the uncertainty communication increased upon its delivery. Overall, examining participant monitoring policies helped explain other performance outcomes and bolstered our previous conclusion: effective uncertainty communication requires maximum specificity.

Optimal monitoring and attack detection of networks modeled by Bayesian attack graphs

Early attack detection is essential to ensure the security of complex networks, especially those in critical infrastructures. This is particularly crucial in networks with multi-stage attacks, where multiple nodes are connected to external sources, through which attacks could enter and quickly spread to other network elements. Bayesian attack graphs (BAGs) are powerful models for security risk assessment and mitigation in complex networks, which provide the probabilistic model of attackers’ behavior and attack progression in the network. Most attack detection techniques developed for BAGs rely on the assumption that network compromises will be detected through routine monitoring, which is unrealistic given the ever-growing complexity of threats. This paper derives the optimal minimum mean square error (MMSE) attack detection and monitoring policy for the most general form of BAGs. By exploiting the structure of BAGs and their partial and imperfect monitoring capacity, the proposed detection policy achieves the MMSE optimality possible only for linear-Gaussian state space models using Kalman filtering. An adaptive resource monitoring policy is also introduced for monitoring nodes if the expected predictive error exceeds a user-defined value. Exact and efficient matrix-form computations of the proposed policies are provided, and their high performance is demonstrated in terms of the accuracy of attack detection and the most efficient use of available resources using synthetic Bayesian attack graphs with different topologies.

The development and application of a novel helicopter-based airborne platform for near-surface monitoring and sampling of atmospheric pollutants

This study presents a novel approach utilising helicopters as platforms for real-time monitoring of air pollutants and routine canister sampling to enhance our understanding of air pollution in the Greater Bay Area (GBA). By employing this method, local spatial and vertical distribution of various air pollutants (including CO, NO, NO2, O3, PM2.5 and VOCs) in Hong Kong could be obtained within hours for fast snapshots of air pollution.The investigation involved hovering ascent and descent operations above Tap Mun Island, revealing no indication of self-contamination from engine exhaust during the hovering process. The analysis of air pollutant spatial distribution in and around Hong Kong through multiple trips showed higher concentrations of O3 and PM2.5 in the northern region on days with episodic pollution, while urban areas exhibited elevated levels of NO2 and CO concentration. In contrast, Tap Mun Island as the background area demonstrated relatively low pollutant concentrations. The vertical distribution of concentrations of VOC species with high ozone formation potential revealed minor variations at sampling altitudes of 500 ft and 1000 ft over the waters around Hong Kong. The novel monitoring protocol using helicopters as platforms proves to be an effective approach for pollution episode investigations, offering valuable insights in the formation mechanisms and transport pathways of O3. The findings of the heterogenous spatial distribution of O3 and its precursors underscore the significance of ongoing monitoring efforts and policy development to combat air pollution in the dynamic GBA and similar regions worldwide.

Metabolic monitoring of pediatric patients prescribed second-generation antipsychotic medication.

The prevalence of psychotropic medication prescription use in youth has increased over the past several years. Despite recommendations and practice parameters established by the American Diabetes Association-American Psychiatric Association (ADA-APA) outlining metabolic monitoring of patients prescribed second-generation antipsychotic (SGA) medication, monitoring adherence for the pediatric patient population remains inadequate. This project aimed to improve metabolic monitoring of pediatric patients prescribed SGAs and discharge recommendations for follow-up monitoring within a small, child, and adolescent psychiatric hospital. This project compared metabolic monitoring adherence rates pre and postimplementation of a metabolic monitoring organizational policy developed to provide procedural guidance, using ADA-APA guidelines. Participants included prescribing clinicians (physicians and psychiatric nurse practitioners). Phase 1 chart reviews found no records of fasting blood glucose, fasting lipid profile or waist circumference. Following project implementation, chart review found that fasting blood glucose and fasting lipid profile was recorded in 21 (72.4%) of the charts, and waist circumference was recorded in 18 (62.1%) of the charts for patients prescribed SGA medication. For patients discharged on an SGA, written recommendations for follow-up metabolic monitoring improved from 13% to 70% (<0.001). Implementing an organizational metabolic monitoring policy and protocol can improve clinician adherence to ADA-APA guidelines for recording in-patient monitoring of metabolic parameters and discharge recommendations for pediatric patients prescribed SGA medication.

A novel hybrid machine learning model for prediction of CO2 using socio-economic and energy attributes for climate change monitoring and mitigation policies

Industrial development has contributed to carbon emissions majorly, resulting in high concentrations of greenhouse gases (GHGs) in the environment leading to climate change phenomenon. Climate change threatens people in multiple ways: threatening food security, water scarcity, frequent and extreme weather events, the spread of diseases, economic losses and migration etc. The World Health Organization (WHO) declared that climate change is the greatest threat to global health in the 21st century. Since 1970, CO2 emission has increased by about 90 per cent, making it 78 per cent of the total greenhouse gas emission. Climate change impact, carbon emission factors and social-economic attributes make the prediction of GHG emission a very complex research problem having dynamic scenarios due to a large number of factors and impacting variables. Accurate prediction of carbon emission in such a scenario makes it one of the most important and challenging research works. Artificial intelligence and machine learning approaches are increasingly being used to study complex, dynamic environmental phenomenons with high variability of time, space and other factors. The research paper proposes hybrid machine learning models for the prediction of CO2 emissions using energy and social-economic variables. The work uses energy and socioeconomic variables from 1960 to 2018 to collate them to provide a new perspective on the application of machine learning approaches in the modelling and prediction of GHG emissions. The proposed hybrid model of principal component analysis (PCA) and machine learning approaches is compared on accuracy and efficiency and performs better than other machine learning and deep learning approaches such as Linear regression variants, random forest regression (RFR), support vector regression (SVR), recurrent neural network (RNN), long short term Memory (LSTM) and Tabnet etc. The proposed hybrid model reports MAE equal to 0.0307, RMSE equal to 0.0346, MAPE equals to 5.1447 and SMAPE equal to 5.2267. In terms of efficiency of computation, the proposed hybrid machine learning model PCA+LER took 12.4 ms better than other models. This proposed research work of correlation analysis and prediction can help policymakers and governments in the mitigation and management of carbon emissions.

SARS-CoV-2 transmission patterns in educational settings during the Alpha wave in Reggio-Emilia, Italy

Different monitoring and control policies have been implemented in schools to minimize the spread of SARS-CoV-2. Transmission in schools has been hard to quantify due to the large proportion of asymptomatic carriers in young individuals. We applied a Bayesian approach to reconstruct the transmission chains between 284 SARS-CoV-2 infections ascertained during 87 school outbreak investigations conducted between March and April 2021 in Italy. Under the policy of reactive quarantines, we found that 42.5% (95%CrI: 29.5–54.3%) of infections among school attendees were caused by school contacts. The mean number of secondary cases infected at school by a positive individual during in-person education was estimated to be 0.33 (95%CrI: 0.23–0.43), with marked heterogeneity across individuals. Specifically, we estimated that only 26.0% (95%CrI: 17.6–34.1%) of students and school personnel who tested positive during in-person education caused at least one secondary infection at school. Positive individuals who attended school for at least 6 days before being isolated or quarantined infected on average 0.49 (95%CrI: 0.14–0.83) secondary cases. Our findings provide quantitative insights on the contribution of school transmission to the spread of SARS-CoV-2 in young individuals. Identifying positive cases within 5 days after exposure to their infector could reduce onward transmission at school by at least 30%.

Cost-effective smartphone-based method for low range chemical oxygen demand analysis

Aiming the decentralization of monitoring policies and to facilitate the work of researchers, mainly in developing countries, the present method deals with the explanation of a simple and rapid protocol for chemical oxygen demand (COD) analysis through the use of digital smartphone devices coupled with a camera and a free app available for Android operating system that recognizes HSV (hue, saturation, value). The calibration of the method is done based on the theoretical values of potassium hydrogen phthalate for a proper and reliable build of the calibration curve by using the smartphone-based technique and the digested samples of COD. The coefficient of determination (R2) attained a value upper than 0.99, providing a high confidence levels, and the method achieved 97% of average accuracy in samples with COD values ranging from 0 to 150 mg L−1. Finally, the procedure here presented can be a great support for scientific laboratories and monitoring policies, once it can efficiently substitute expensive spectrophotometers and can improve and ensure the sustainable management of water sanitation, which is one of the sustainable goals proposed by the United Nations.•COD measurements, based on the use of a simple smartphone with a camera, can be a promising way for environmental analysis when spectrophotometers are not available, such as decentralized approaches.•The use of smartphone protocol is a novel initiative to fulfill sustainable development goal 6 on clean water and sanitation.•The smartphone is capable to read the difference of HSV values efficiently and can substitute the use of expensive spectrophotometers.

Developments in Unmanned Surface Vehicles (USVs): A Review

Unmanned Surface Vehicles (USVs) have witnessed significant advancements in recent years, revolutionizing various domains that require marine operations. This abstract presents a review of the developments in USVs, focusing on their applications, technological advancements, and associated benefits. USVs have emerged as invaluable tools for data collection studies, particularly in environmental monitoring and marine production policies. They offer a cost-effective and efficient means of gathering critical data, aiding decision-making processes in these fields. Additionally, USVs have proven instrumental in the surveillance of territorial waters, safeguarding offshore systems, and supporting oil and fuel activities in the Arctic regions. These capabilities have resulted in improved security, enhanced operational efficiency, and reduced risks for personnel involved in these operations. Technological advancements in USVs have played a pivotal role in their evolution. Enhanced autonomy, sensor integration, and communication systems have enabled USVs to operate autonomously or in collaboration with manned vessels, expanding their capabilities and versatility. Moreover, improvements in navigation systems, obstacle avoidance mechanisms, and power management have significantly enhanced the reliability and endurance of USVs, allowing them to undertake extended missions with minimal human intervention. In conclusion, the developments in unmanned surface vehicles have transformed the way marine operations are conducted. With their wide-ranging applications, technological advancements, and associated benefits, USVs have proven to be indispensable assets in various domains. As research and innovation continue to propel the field forward, USVs are poised to play an even more significant role in the future of marine operations, further improving efficiency, safety, and sustainability.

Amplitude–Frequency Noise Models for Seismic Building Monitoring in a Weak-to-Moderate Seismic Region

AbstractHerein, we discuss amplitude–frequency noise models for high-quality accelerometric monitoring of a civil engineering building and the benefits of seismic building monitoring policies in weak-to-moderate seismic regions. Since 2004, the city hall building in Grenoble (French Alps) has been monitored continuously. First, accelerometric data from one continuous year are used to derive broadband noise models for the bottom and top of the building. The noise models are compared with (1) the noise sensitivity of the high-gain accelerometer installed in the building and low-cost sensor sensitivity models; (2) the typical earthquake response curves given by Clinton and Heaton (2002); and (3) the earthquakes recorded in the Northern Alps. Then, using earthquakes data, this study highlights threshold values for signal-to-noise ratio (≥3 or 9 dB) recordings of earthquake as a function of magnitude and distance for weak-to-moderate earthquakes. We present a preliminary cost-benefit analysis of instrumentation for such regions according to seismic hazard and instrumentation quality. For weak-to-moderate seismic regions like Grenoble area, the capability of high-dynamic accelerometers to record low-amplitude ground motions and building responses is confirmed and encouraged to enable high-quality observation of building response over a broad range of frequencies. Bearing in mind that full-scale building test data are of greater interest for improving our understanding of building response than even the most sophisticated models, the recording of weak-to-moderate earthquakes in building must be broadened using high dynamic instruments to obtain more comprehensive and advanced results.