Aga Khan Foundation

A detailed model of a full-conversion wind turbine (WT) is presented in this article. The developed model uses cosimulation by several freeware WT simulation tools-such as the turbulent wind simulator (TurbSim) and Fatigue, Aerodynamics, Structures, and Turbulence (FA ST), both from the National Renewable Energy Laboratory (NREL)-and commercial software to perform a detailed analysis of all WT components. An optimal level of model complexity is achieved to allow the design, analysis, and simulation of the controls and subsystem interactions within a turbine under various conditions. The article introduces a maximum power point tracking (MPPT) control for a variable-speed WT with stall power regulation and analyzes its influence on flexible blades and the drivetrain. The proposed simulation tools and the developed model reveal some stability issues and subsystem interaction complexities that are not visible in simpler models. In this article, modeling results are presented that detail the performance of the WT system.

There are challenges in monitoring and managing water quality due to spatial and temporal heterogeneity in contaminant sources, transport, and transformations. We demonstrate the importance of longitudinal stream synoptic (LSS) monitoring, which can track combinations of water quality parameters along flowpaths across space and time. Specifically, we analyze longitudinal patterns of chemical mixtures of carbon, nutrients, greenhouse gasses, salts, and metals concentrations along 10 flowpaths draining 1,765 km 2 of the Chesapeake Bay region. These 10 longitudinal stream flowpaths are drained by watersheds experiencing either urban degradation, forest and wetland conservation, or stream and floodplain restoration. Along the 10 longitudinal stream flowpaths, we monitored over 300 total sampling sites along a combined stream length of 337 km. Synoptic monitoring along longitudinal flowpaths revealed: (1) increasing, decreasing, piecewise, or no trends and transitions in water quality with increasing distance downstream, which provide insights into water quality processes along flowpaths; (2) longitudinal trends and transitions in water quality along flowpaths can be quantified and compared using simple linear and non-linear statistical relationships with distance downstream and/or land use/land cover attributes, (3) attenuation and transformation of chemical cocktails along flowpaths depend on: spatial scales, pollution sources, and transitions in land use and management, hydrology, and restoration. We compared our LSS patterns with others from the global literature to synthesize a typology of longitudinal water quality trends and transitions in streams and rivers based on hydrological, biological, and geochemical processes. Applications of LSS monitoring along flowpaths from our results and the literature reveal: (1) if there are shifts in pollution sources, trends, and transitions along flowpaths, (2) which pollution sources can spread further downstream to sensitive receiving waters such as drinking water supplies and coastal zones, and (3) if transitions in land use, conservation, management, or restoration can attenuate downstream transport of pollution sources. Our typology of longitudinal water quality responses along flowpaths combines many observations across suites of chemicals that can follow predictable patterns based on watershed characteristics. Our typology of longitudinal water quality responses also provides a foundation for future studies, watershed assessments, evaluating watershed management and stream restoration, and comparing watershed responses to non-point and point pollution sources along streams and rivers. LSS monitoring, which integrates both spatial and temporal dimensions and considers multiple contaminants together (a chemical cocktail approach), can be a comprehensive strategy for tracking sources, fate, and transport of pollutants along stream flowpaths and making comparisons of water quality patterns across different watersheds and regions.

Ultra-short-term wind forecasting (i.e. wind speed and power predictions issued for sub-hourly forecast horizons), are pivotal to the effective management and integration of wind farms into modern-day electricity systems. The dominant consensus in the forecasting literature and practice is that data-driven approaches may be best suited for such short-term horizons. This is in contrast to numerical weather predictions (NWP), or hybrid models thereof, for which the value is typically substantiated at relatively longer horizons (>1-3 hours). We propose a probabilistic data-driven model that actually makes use of NWP information (albeit indirectly) for ultra-short-term wind speed and power forecasting. Instead of directly using NWPs as input regressors (as in hybrid approaches), we indirectly invoke NWP information in selecting key parameters within the data science model, thereby guiding it to adhere to certain physical principles related to local wind field formation and propagation. We show that such indirect integration of NWPs within our data science model outperforms several prevalent forecasting methods, including but not limited to persistence forecasts, which are known to be highly competitive at ultra-short-term horizons. This work serves as an exemplar for leveraging the rich, yet coarser-resolution information of NWPs in benefiting data-science-based ultra-short-term wind forecasting models.

Abstract As renewable energy developers start venturing into deeper waters, the floating offshore wind turbines (FOWTs) are becoming the preferred solutions over fixed supporting structures. Many similarities can be identified between a FOWT and a floating oil & gas facility, such as floater concepts (spar, semi-submersible, tension leg platform, etc) and their mooring system designs. This paper focuses on the mooring designs for FOWTs by leveraging the extensive experience gained from the offshore oil & gas industry. Similarities and differences are highlighted in design criteria, mooring analysis, long-term integrity management, installation method and project execution. The established practices regarding mooring design and analysis are reviewed. Anchor radius is recommended based on water depth by referencing sample mooring designs from the oil & gas industry. Long-term mooring integrity and failure rates are summarized. Meanwhile, a few well-known issues are discussed, such as line break due to fatigue, corrosion on chain, and known issues with components such as clump weights. Regarding mooring installation, the established method for prelay and hook-up is reviewed. Finally, opportunities for cost reduction of mooring systems of FOWTs are presented related to project execution of large scale wind farms as well as potential areas of innovation, such as installation methods, use of synthetic fiber rope, and digitalization. In summary, the state-of-the-art practices from the oil & gas industry are reviewed and documented to benefit the developments of upcoming FOWT projects.

Voluntary agreements with polluting industries are becoming a popular alternative to
\ntraditional environmental regulation. One reason may be that voluntary agreements can
\nreduce compliance costs of polluting industries. In this paper we develop a family of
\nsimple policy formulation and implementation models enabling us to formally
\ncharacterize the policy environments that make voluntary agreements possible. The
\nmain message of this paper is one of caution. Voluntary agreements that increase
\ncompliance costs and reduce social welfare can not be ruled out. The analyses also
\nsuggests that giving the legislative branch of government an effective power of veto
\nreduces (but does not eliminate) the possibility of welfare reducing voluntary agreements.

Denne undersøgelse handler om økonomiske sanktioner over for kontanthjælpsmodtagere. Nogle kommuner anvender sanktioner hyppigere end andre, men antallet af sanktioner har generelt været stigende. Det gælder også sanktioner over for de kontanthjælpsmodtagere, der har problemer ud over ledighed.

Invasive alien species (IAS) are a direct driver of global biodiversity loss, and can also affect societies, economies and human health. Maintaining up-to-date alien species inventories is important for informing policy and management decisions. Here we present the Cyprus Database of Alien Species (CyDAS), an openly accessible, online dataset providing informational resources on alien species on the island of Cyprus. The dataset (up to end of December 2023) includes information on 1,293 terrestrial, freshwater and marine introduced taxa, with species profiles being constantly updated to keep track of new arrivals. The CyDAS aims to catalogue and supplement our knowledge on the alien species of Cyprus; to help develop and enhance early warning and rapid response systems; to raise public awareness of the risks posed by the IAS subset; to strengthen and enhance engagement and public participation in surveys in the field of biological invasions; and to inform IAS policy. CyDAS is a free, online database and we would like to encourage other researchers and decision-makers to provide information on IAS.

Abstract Managing aquatic ecosystems for people and nature can be improved by collaboration among scientists, managers, decision‐makers, and other stakeholders. Many collaborative and interdisciplinary approaches have been developed to address the management of freshwater ecosystems; however, there are still barriers to overcome. We worked as part of a regional stakeholder group comprising municipal water utility operators, conservation organizations, academic partners, and other stakeholders to understand the effects of low‐flow and drought on ecological functions of the upper Flint River, Georgia (USA), a free‐flowing river important for municipal water supply, recreation, and native biota. We used published literature and locally targeted studies to identify quantitative flow targets that could be used to inform water management and drought planning. Drawing from principles of Translational Ecology, we relied on an iterative process to develop information needs for the group and maintained communication and engagement throughout data collection, analysis, and synthesis. We identified three quantitative flow benchmarks to evaluate the ecological impacts of drought in the river. The results were valuable to both the water utilities represented in the working group and State regional water planning, which is used to guide water management strategies and permitting for the basin. We identified principles that were important for the successful engagement in the working group and helped to overcome the challenge of working across sectors and without direct authority guiding the implementation of our work. Interdisciplinary work and creative solutions are crucial to plan for and adapt to greater pressure on our water resources.

Research shows that the higher the level of academic positions at universities the lower the percentage of women among employees also applies at Danish universities. This may be due to a historical backlog or merely to a 'Leaky pipeline', as earlier studies have revealed that an increasing proportion of women among university graduates has not resulted in an increasing proportion of women among university academics. This study based on data from Aalborg University documents by the use of longitudinal analyses that the ‘pipeline’ leaks women at the very first steps of the career ladder.

Generative Artificial Intelligence has revolutionized various aspects of the modern world, ranging from individual users leveraging tools to answer queries to companies developing advanced chatbots. However, it may still be premature to assert that all the potential applications of Generative AI have been fully explored. Among these unexplored possibilities, the integration with immersive technologies, such as virtual reality, augmented reality, and mixed reality, remains a domain with substantial room for development. This paper explores the opportunities related to Generative AI in the context of immersive technologies, as well as the challenges associated with its broader adoption in virtual worlds.

Bu çalışmanın amacı, BIST 100 Endeksi’nde yer alan 57 işletmenin serbest nakit akışları ve nakit akış oranları ile karlılık oranları arasındaki ilişkiyi tespit etmektir. Bu amaç doğrultusunda ilgili endeksteki işletmelerin 2005-2021 yılları arasındaki verileri dikkate alınmıştır. Araştırma kapsamında panel regresyon analizi kullanmıştır. Ayrıca araştırmada bağımlı değişken olarak Aktif ve Özkaynak Kârlılığı, bağımsız değişken olarak serbest nakit akışları ile nakit akış oranları (İşletme, Yatırım ve Finansman Faaliyetlerinden Nakit Akışları/Toplam Aktif) ve son olarak kontrol değişkenleri olarak ise İşletme Büyüklüğü, Finansal Kaldıraç Oranı, Satışlardaki Büyüme Oranı dikkate alınmıştır. Çalışmanın sonucunda Aktif ve Özkaynak Kârlılığı ile serbest nakit akışları ve İşletme Faaliyetlerinden Nakit Akışları arasında pozitif yönlü bir ilişki ortaya konmuştur. Ayrıca Aktif Kârlılığı ile Finansman Faaliyetlerinden Nakit Akışları arasında da pozitif bir ilişki tespit edilmiştir. Kontrol değişkenleri bakımından ise Aktif Kârlılığı ile Satışlardaki Büyüme Oranı ile pozitif yönlü, Finansal Kaldıraç Oranı ile ise negatif yönlü bir ilişki bulunmuştur.

A reconfigurable substrate integrated waveguide (SIW) filtenna operating in the 5G millimeter Wave (mmWave) band is presented, where varactors are integrated into the filtering-antenna structure to change the resonant frequency and coupling between the SIW resonators. The proposed structure allows for the reconfigurability of the antenna radiation frequency band in the range of $24-27 \mathrm{GHz}$, covering most of the 3GPP n258 band, with a constant bandwidth of 400 MHz and broadside radiation pattern. A prototype of the proposed mmWave filtenna is designed and fabricated, where the measurement results are in good agreement with the simulation. The proposed cost-effective and scalable filtenna is an ideal candidate for deployment in 5G wireless networks, with the ability to reduce adjacent channel interference (ACI) and enable passive spectrum coexistence with weather sensors in the 23.8 GHz band.

The allocation of the 5G mmWave spectrum in the 26 GHz range, known as 3GPP band $\mathbf{n 2 5 8}$, has raised wide concern among the remote sensing and weather forecast communities due to the adjacency of this band with a frequency band used by passive sensors in Earth Exploration-Satellite Service (EESS). The concern stems from the potential radio frequency interference (RFI) caused by transmissions in the $\mathbf{n} 258$ band into the 23.8 GHz frequency, one of the key frequencies employed by weather satellite passive sensing instruments, such as AMSUA and ATMS, to measure atmospheric water vapor using its emission spectrum. Such RFI can bias satellite observations and compromise weather forecasting. In this paper, we develop a modeling and numerical framework to evaluate the potential effect of the 5G mmWave $\mathbf{n} 258$ band’s commercial deployment on numerical weather forecast accuracy. We first estimate and map the spatio-temporal distribution of 5G mmWave base stations at the county-level throughout the contiguous United States (US) using a model for technology adoption prediction. Then, the interference power received by the AMSU-A radiometer is estimated for a single base station based on models for signal transmission, out-of-band radiation, and radio propagation. Then, the aggregate interference power for each satellite observation footprint is calculated. Using the contaminated microwave observations, a series of simulations using a numerical weather prediction (NWP) model are conducted to study the impact of $\mathbf{5 G}$-induced contamination on weather forecasting accuracy. For example, our results show that when the interference power at the radiometer from a single base station is at a level of $-\mathbf{1 7 5} \mathrm{dBW}$ for a network of base stations with spectral efficiency of $15 \mathrm{bit} / \mathrm{s} / \mathrm{Hz} / \mathrm{BS}$, the aggregate interference power has limited impact in the year 2025 but can result in an induced noise in brightness temperature (contamination) of up to 17 K in the year 2040. Furthermore, that level of RFI can significantly impact the $\mathbf{1 2}$-hour forecast of a severe weather event such as the Super Tuesday Tornado Outbreak with forecasting errors of up to 10 mm in precipitation or a mean absolute error of $\mathbf{1 2. 5 \%}$. It is also estimated that when the level of interference power received by the radiometer from a single base station is $-\mathbf{2 0 0} \mathrm{dBW}$, then there is no impact on forecasting errors even in 2040.

Background: A proven strategy for saving lives from vaccine-preventable diseases is the timely vaccination of the people. In Ghana, there is considerable hesitation about the Covid-19 vaccines due to anxieties and uncertainties about their safety. With varying perceptions and believes being developed about Covid-19 vaccines, there is a likely negative effect on vaccine acceptance or otherwise. This study aims to ascertain the levels of acceptance of potential Covid-19 vaccine among Ghanaian adults, to identify predictors of vaccine acceptance or hesitance. Methodology: A web based cross-sectional survey conducted among Ghanaians above 18 years, conducted between the month of February and March, 2021. Data were collected by administering online google forms (Questionnaire). The questionnaire was shared through social media platforms. A snowball sampling technique was used where researchers shared google forms to close friends and family. Analyses were conducted at p-value <0.05 using descriptive statistics, cross-tabula­tions and logistic regression. Results: A total of 350 responses were achieved by end of data collection. Out of these, only 348 were considered for analysis based on the inclusion and exclusion criteria. Majority of the respondents (65.2%) were male, a third (30%) of them live in rural areas and about 57.5% were married. Factors such as age, educational level, prior vaccine acceptance history, personal vulnerability and self-feeling of health were significantly associated with covid-19 vaccine acceptance. Conclusion: The results depict low acceptance rate for potential covid-19 vaccine among Ghanaians. Government and MoH should engage the media on its role in combating misinformation with regards the Covid-19 vaccine. Key words: coronavirus disease 2019 (Covid-19), vaccine, hesitance, acceptance.

Abstract The scarcity of suitable shallow waters for fixed-bottom offshore wind turbines has prompted developers to explore deeper waters, albeit with caution due to the significant capital expenditure (CAPEX) associated with Floating Offshore Wind Turbines (FOWTs). A major cost component in FOWTs is the mooring system, a concern exacerbated in regions with the presence of typhoons, necessitating a more robust and therefore expensive 3 × 3 mooring solution compared to 3 × 1 in areas such as the North Sea. This study tried to propose a 3 × 2 mooring arrangement tailored for FOWTs in the typhoon region, offering a potential cost reduction of up to one-third compared to the original 3 × 3 configuration. To achieve cost savings, an in-depth analysis of spreading angles from 10° to the widest angle of 126° is performed using the pre-tension-diameter vs offset-tension 3D response surfaces technique. The research reveals that, theoretically, a 60° mooring angle minimizes floater offset with the least tension. However, the discrepancy in safety factors between intact and damaged conditions makes grouped mooring a more cost-effective choice. Utilizing the American Bureau of Shipping (ABS) safety factor, a 10° spread angle mooring system’s chain cost emerges as roughly one-tenth cheaper than alternative configurations. Additionally, the study explores an innovative V-Share mooring [1], wherein a single pile anchor connects to two different columns via two mooring lines. Depending on the anchoring conditions, it can be the most cost-effective. In conclusion, a 3 × 2 mooring pattern for a 15MW semi-submersible FOWT in typhoon regions might be theoretically achieved on paper. However, it may not be practically achieved, if the size limit of the manufactured chain is considered.

The two key predictions of hedonic wage theory are that there is a trade-off between wages and nonmonetary rewards and that the latter can be used as a sorting device by firms to attract and retain the kind of employees they desire. Empirical analysis of these topics are scarce as they require detailed data on all monetary as well as nonmonetary rewards, not only for the job chosen but also for alternative offers. In this paper this data predicament is solved by the use of the vignettes method to estimate individuals' willingness to pay for fringe benefits and job amenities. We find clear negative wage-fringe trade-offs, considerable heterogeneity in willingness to pay for fringe benefits, and signs of sorting. The findings imply that personnel economics models can be applied also to the analysis of nonmonetary rewards.

Prompt-injection and jailbreak attacks can coerce large language models (LLMs) into revealing system prompts or producing unsafe content, threatening real-world deployments. We present Proxy Barrier (ProB), a lightweight defense that interposes a repeater proxy LLM between the user and the target model. The repeater acts to verbatim-echo benign user input, and any divergence indicates adversarial tampering, causing the request to be dropped before it reaches the target model, so that attempts to bypass safety boundaries are blocked. ProB therefore requires no access to model weights or prompts, is model-agnostic, and deployable entirely at the API level. Experiments across multiple model families demonstrate that ProB achieves state-of-the-art resilience against prompt leakage and jailbreak attacks. Notably, our approach achieves up to 98.8% improvement in defense effectiveness over baselines, and shows robust protection across both open and closed-source LLMs when suitably paired with proxy models.

Passive microwave observations near 23.8 GHz are central to numerical weather prediction but lie adjacent to frequencies increasingly used for fifth-generation (5G) telecommunications. Here we present the first end-to-end quantification of how terrestrial 5G interference affects weather forecasts, particularly for extreme weather events, using an operational forecasting system. By assimilating synthetically contaminated microwave radiances into a data assimilation framework, we show that aggregate out-of-band emissions introduce structured biases that propagate dynamically through the forecasting system. In simulations of Hurricane Ida’s extratropical transition, these biases trigger the rejection of moisture-sensitive observations and distort atmospheric states, producing precipitation errors of up to 15% and near-surface temperature deviations exceeding 2 °C, even far from interference sources. Our results demonstrate that anthropogenic spectral interference can systematically degrade forecasts of extreme weather, revealing a previously unquantified vulnerability in global early warning systems.

Økonomiske sanktioner er ingen mirakelkur, når det handler om at regulere borgernes adfærd. For eksempel viser en ny AKF-rapport, at kontanthjælpsmodtagere, der sanktioneres, sjældent kommer i job. Det sætter spørgsmålstegn ved, hvordan kontanthjælpsmodtagere mest effektivt integreres på arbejdsmarkedet.

Undersøgelsen har til formål at identificere sammenhængen mellem de pædagogiske paradigmer inden for autismeområdet, de konflikter som kendetegner samspillet mellem beboere og personale og den psykiske belastning, personalet oplever i deres arbejde.