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Abstract The advancement of Photovoltaic technology has undergone rapid acceleration in recent years. Nonetheless, the most significant drawback of Photovoltaic is its intermittence, making it an obvious source of power fluctuation. This study proposes a novel scheme for real‐time or intraday PV power forecasting by adopting two predictive models, namely, White‐box and Combination. The White‐box model is implemented employing mathematical calculations and statistics called Exceedance Probability. Meanwhile, the Combination model is an aggregation of several predictive models' outputs including the White‐box model and benchmark ones by dynamically adjusting the weight coefficient of each model based on their forecasting accuracy. The experimental results, which are verified on two PV systems corresponding to two case studies located at Vietnam and Australia, indicate that the two proposed models outperform other referenced models as nMAPE improves approximately 40% and 38% in terms of the first and second case study, respectively. In particular, the White‐box model shows superiority by updating the forecast every 10 min, which can adapt to the fluctuation of weather conditions whereas the Combination one yields acceptable precision, indicating its flexible application.

Abstract The gap between electricity supply and demand, which is the electricity imbalance, can have negative economic impacts on retail electricity suppliers. This paper presents a methodology for designing demand response (DR) programs while mitigating the negative impacts. The DR programs require the retailers to set target electricity consumption and prices of economic incentives for customers who cooperate with the DR programs. First, the target electricity consumption is determined by solving a problem of social welfare maximization in which the objective function is the sum of economic surplus of the retailers and their customers and impacts of electricity imbalance. The optimal electricity prices or the optimal rebate levels are then calculated under the principle that rational customers act to maximize their economic surplus. Through numerical simulations, the authors confirmed that the proposed methodology mitigated the impacts of electricity imbalance. Meanwhile, results of the numerical simulations showed that in practical situations, there were cases where the retailers unable to reduce the electricity imbalance profitably. Therefore, the authors additionally discuss ways to assess the electricity imbalance, which motivates the retailers to reduce the imbalance, in such cases.

Medical image data often face the problem of data scarcity and costly annotation processes. To overcome this, our study introduces a novel transfer learning method for medical image classification. We present a multimodal learning framework that incorporates the pre-trained PubMedCLIP model and multimodal feature fusion. Prompts of different complexities are combined with images as inputs to the proposed model. Our findings demonstrate that this approach significantly enhances image classification tasks while reducing the burden of annotation costs. Our study underscores the potential of PubMedCLIP in revolutionizing medical image analysis through its prompt-based approach and showcases the value of multi-modality for training robust models in healthcare. Code is available at:https://github.com/HongJapan/MTL_prompt_medical.git.

In recent decades, the dramatic transformation from conventional energy to renewables, such as photovoltaic (PV), has been extensively occurred to address the increasing electricity demand and environmental issues. Nevertheless, the operation of PV systems is adversely affected by the intermittence of meteorological factors, such as solar irradiance. Therefore, accurate PV power generation forecast has played a vital role to stimulate the integration of renewable energy sources into the power grid. This study proposes a novel scheme for short-term PV power forecast based on Transformer Neural Network (TransNN) integrated with Convolutional Neural Network (CNN). In addition, Variational Mode Decomposition (VMD) is adopted in the data pre-processing stage to enhance the forecast accuracy. The performance of the proposed model is validated utilizing two real-world datasets, and five benchmark models are dedicated to forecast outcome comparison. The predicted results indicated the superiority of the proposed model compared to the referenced models by achieving the Mean Absolute Error (MAE) values under 1 kW in all cases.

Low-voltage ride-through (LVRT) capability is crucial for wind power plants that are grid-connected. A grid code requires wind farms to remain on-grid and inject a specific reactive current when a grid fault occurs. The requirements are satisfied by a cooperative control scheme of a battery energy storage system (BESS) and grid-side converter (GSC) for improving the LVRT capacity of wind turbine generators using permanent magnet synchronous generators. The proposed approach uses the BESS to absorb a power difference that appears in the back-to-back converters during the LVRT operation. Hence, the DC-link voltage is regulated by the BESS. In addition, the GSC control allows reactive current to be injected into the grid according to the grid code requirements. Finally, the wind turbine generators, which use the proposed approach, are built in MATLAB/Simulink. The theoretical analysis of the proposed method is validated by simulation.

Microgrids (MGs) with a high penetration of renewable energy are becoming increasingly popular, mainly due to the need for a sustainable and environmentally friendly power system. However, the stochastic characteristic of renewable energy sources makes it a considerable challenge when designing a microgrid. Appropriate installation of energy storage systems (ESSs) such as battery and hydrogen storage systems are needed to counter the intermittent nature of energy sources. This study presents a comparison and evaluation of eight different metaheuristic approaches for optimizing the size of a hydrogen storage-based microgrid, with the aims of minimizing the microgrid’s cost and ensuring the ability to regulate the energy flow within the system. In addition, the optimization algorithm considers the power of the photovoltaic (PV) system, electrolyzer, fuel cell, and the capacity of the battery and hydrogen tank as decision variables. Results of numerical simulations proved that, under the above problem framework, the particle swarm optimization algorithm outperforms the rest. The algorithm is able to produce an optimized microgrid with a 25.3% lower annual system cost compared to the worst-performing algorithm. Its ability to escape the local optimum solution is also showcased.

Here the authors propose an RNA interference-based switch for dynamic control of AAV transgene expression. In this approach, transgene expression may be silenced by RNAi and subsequently recovered using REVERSIR oligonucleotides.

Battery energy storage systems (BESSs) play extremely important roles in managing power supply and demand in a microgrid. The BESSs, on the other hand, have problems of high initial investment costs and limited lifetime. In this paper, a problem formulation and its solution are presented for sizing an aggregated BESS in a microgrid that minimizes the sum of initial costs of the aggregated BESS and operational costs of the microgrid. The target problem is originally categorized into a bilevel optimization because it comprises two optimization problems: the sizing of aggregated BESS and the operational scheduling of microgrid’s components. The authors, however, apply the Karush–Kuhn–Tucker approach and reformulate the target problem as a single-level optimization problem. This reformulation enables us to treat the problem as if it was a type of operation scheduling problems. That is, the solution techniques developed to obtain the optimal operation scheduling are applicable by the problem reformulation. As the basis for the solution method, an algorithm combining binary particle swarm optimization and quadratic programming is applied in this paper. To verify the validity of the proposal, numerical simulations are performed, and their results are discussed.

Renewable energy (solar and wind) sources have evolved dramatically in recent years around the globe, primarily because they have the potential to generate environmentally friendly energy. However, operating systems with high renewable energy penetration remain challenging due to the stochastic nature of these energy sources. To tackle these problems, the authors propose a state machine-based energy management strategy combined with a hysteresis band control strategy for renewable energy hybrid microgrids that integrates hydrogen storage systems. By considering the power difference between the renewable energy source, and the demand, the battery’s state of charge, and the hydrogen storage level, the proposed energy management strategy can control the power of fuel cells, electrolyzers, and batteries in a microgrid and the power imported into/exported from the main grid. The results showed that the energy management strategy provides the following advantages: (1) the power supply and demand balance in the microgrid was balanced, (2) the lifespans of the electrolyzer and fuel cell were extended, and (3) the state of charge of the battery and the stored level of the hydrogen were appropriately ensured.

Output characteristics of photovoltaic (PV) systems are greatly affected by both external and internal aspects. The external features, such as irradiance and temperature, are measured by the weather station. However, the irradiance and the temperature measured from measurement instruments are not representative of the energy and the heat that the PV modules receive. The internal factors, such as resistance, are difficult to identify since they are not physically present in the PV modules. One of the trending research directions is to utilize the output characteristics of the PV module to determine the operating conditions of the PV module. This paper presents a method to identify external features (solar irradiance and temperature) and internal resistances by employing the I–V characteristics of the PV module. The proposed method is based on the regression model, which uses the experimental I–V values from the I–V​ tracer. In addition, a method to obtain irradiance from the maximum power point current in the recent literature is employed for the comparison. The simulation results show that the estimation accuracy of the proposed method is higher than that of the referenced method.

Transparent flexible electrodes based on silver nanowires (AgNWs) have great potential for practical applications and many studies have been carried out to improve their conductivity, transparency, and surface roughness. In this study, we demonstrate a new approach for the fabrication of high-performance transparent flexible electrodes based on AgNWs and graphene oxide (GO) on polymer substrates using the pressing method. The surface morphology of the pressed AgNW/GO electrode was characterised by atomic force microscopy (AFM) and observed by scanning electron microscope (SEM). The electrode had a low surface roughness with the root mean square (Rq) of 7 nm. The electrode exhibits a low sheet resistance of 22 Ω/sq, a high transmittance of ~88%, resulted in a figures-of-merit (FoM) value of ~12.6. The optical and electrical properties of the electrode are comparable to that of the flexible ITO electrode. In addition, the electrodes also displayed outstanding durability and mechanical stability. This simple and scalable fabrication method is expected to contribute to future studies on flexible transparent conductive electrodes.

We describe the MalariaGEN Pf7 data resource, the seventh release of Plasmodium falciparum genome variation data from the MalariaGEN network. It comprises over 20,000 samples from 82 partner studies in 33 countries, including several malaria endemic regions that were previously underrepresented. For the first time we include dried blood spot samples that were sequenced after selective whole genome amplification, necessitating new methods to genotype copy number variations. We identify a large number of newly emerging crt mutations in parts of Southeast Asia, and show examples of heterogeneities in patterns of drug resistance within Africa and within the Indian subcontinent. We describe the profile of variations in the C-terminal of the csp gene and relate this to the sequence used in the RTS,S and R21 malaria vaccines. Pf7 provides high-quality data on genotype calls for 6 million SNPs and short indels, analysis of large deletions that cause failure of rapid diagnostic tests, and systematic characterisation of six major drug resistance loci, all of which can be freely downloaded from the MalariaGEN website.

Attention to technology integration in teaching and learning has created a big change in the education landscape. There is no limit to the application of information technology in education in general and in mathematics education in particular. Although there have been many studies on the opportunities and applications of ICT in Mathematics education in the world, many aspects remain unexplored. In this study, the authors apply bibliometric analysis for the purpose of evaluating the scientific results of publications involving in the use of ICT in Mathematics education, which were indexed in the Scopus database. 205 publications were cited to analyze growth trends, contributions of authors, research institutions, co-authors in the research field and the development of research direction. The analysis results show that publications that mainly appear in recent years are published on sources with low citation index; Indonesia, Malaysia and Australia are the most influential countries in studies on this topic; Research cooperation in this field is not strong; The main research topics and trends are online teaching, realistic mathematics education, and computer-aided teaching. From the research results obtained, the authors also furnish some recommendations in the article for future research in this field.

Abstract Background Over recent decades, Vietnam has experienced rapid economic growth, a nutrition transition from the traditional diet to highly-processed and calorie-dense foods and beverages, and an increasing prevalence of childhood overweight/obesity (ow/ob). The goal of this study is to describe the patterns of ow/ob in a longitudinal sample of Vietnamese children from ages 1 to 8, and the sociodemographic and behavioral factors associated with ow/ob at age 8. Methods This study is a secondary data analysis of a geographically-representative, longitudinal cohort of 1961 Vietnamese children from the Young Lives Cohort Study from 2002 to 2009. Thirty-one communities were selected with oversampling in rural communities, and children age 1 were recruited from each community using simple random sampling. Surveys of families and measurements of children were collected at child ages 1, 5, and 8. Our specified outcome measure was childhood ow/ob at age 8, defined by the World Health Organization’s thresholds for body-mass-index (BMI) for age Z-scores. Associations between early and concurrent socio-behavioral factors, childhood nutrition and physical activity variables were analyzed using STATA 15. Bivariate and multivariable analyses were completed utilizing logistic regression models. Results The prevalence of ow/ob increased from 1.1% in both sexes at age 1 to 7% in females and 13% in males at age 8. Bivariate analyses show greater likelihood of ow/ob at age 8 was significantly associated with early life sociodemographic factors (at age 1), male sex (OR = 2.2, 1.6–3.1), higher wealth (OR = 1.1–1.4), and urban residence (OR = 4.3, 3–6). In adjusted analyses, ow/ob at age 8 was associated with early nutrition practices at age 5, including frequent consumption of powdered milk (OR = 2.8, 1.6–4.6), honey/sugar (OR = 2.7, 1.8–4.1), prepared restaurant/fast foods (OR = 4.6, 2.6–8.2), and packaged sweets (OR = 3.4, 2.3–4.9). In addition, breastfeeding for 6 months or longer was protective against obesity at age 8 (OR = 0.3, 0.1–0.9). Conclusions We found that increased consumption of powdered milk, honey/sugar, packaged sweets, and prepared restaurants/fast foods are associated with childhood ow/ob. In contrast, breastfeeding for 6 months or longer was protective against childhood ow/ob. These findings suggest that public health programs and campaigns aimed to prevent childhood ow/ob in Vietnam should target early feeding practices.

Background: We determined the occurrence frequency of Clinical signs, subclinical characteristics on positive anti-IgG Toxocara ELISA cases, and clinical response results after 1 month of albendazole-specific treatment. Methods: A number of 103 clinically treated patients were studied between 2018 and 2019 in two hospitals. Relevant data are collected from examination and medical records such as age, sex, job, resident, clinical and sub-clinical signs. Sera samples were subjected to anti-IgG Toxocara antigen using ELISA. Results: The median age of the patient was 43.6 ± 14.4 years. The most common symptom groups were the skin and mucosa (88.3%), followed by neurological symptoms (44%). There are 76.7% of patients with risk factors for contact with pet dogs and cats. The majority of eosinophils in the normal range (< 8%) accounted for 85.4%, the major results of the OD value of ELISA were in the group (≥ 0.3-< 1.5) accounted for 75.7%. The skin and mucosa lesions in toxocariasis patients related to IgE values were statistically significant (P

The usage of batteries and supercapacitors in the field of electric vehicles is becoming increasingly prominent in both research and development. Due to the complementary advantages of the two systems, high energy density, and high power density, a combined battery/supercapacitor system offers potential. To effectively utilise the potential of such a hybrid energy storage system (HESS), one requires an intelligent energy management system (EMS). The EMS is responsible for controlling the electrical power between the battery and the supercapacitor in such a way that the required power can be optimally distributed at all times (currently and in the future). For this purpose, the energy management system utilises information on the driving route and, based on this information, shall calculate a global strategy for the continuous power distribution. The controlled power distribution should take place in real time and be robust against discrepancies so that unpredictable or unreliably predictable events do not significantly influence the functionality. For the implementation of the concept, a rule-based power distribution is implemented in combination with a predictive energy management. Here, the energy management is combined with a rule-based strategy calculation based on data on the route to be driven with a global optimization for the calculation of a route-specific strategy. Depending on the selected objective, the increase in energy efficiency, or lifetime, the operation of the power control is optimised. Due to the functional separation, the continuous power control can operate in real time, while more computational time can be spent on the calculations of the power management strategy, which accordingly does not need to be executed in real time. The results show that by using the presented EMS, especially in combination with a route-specific parameterisation, a significant effect on the energy efficiency and/or battery lifetime can be achieved. The average battery energy consumption can be reduced by up to 9.14% on urban routes. Regarding battery lifetime, the average battery usage can be reduced up to 13.35% and the battery energy losses even up to 62.72%.

The operation of the photovoltaic (PV) system under partial shading conditions (PSC) is complicated since the output characteristic of the PV system is profoundly affected by the heterogeneous irradiance of PSC. This paper proposes a dynamic reconfiguration framework to tackle PSC in the PV array. Continuous operation of the dynamic PV array reconfiguration under cloud-induced partial shading is considered by developing an emulator of the moving cloud. In addition, the Particle Swarm Optimization and Rao algorithms are improved to obtain the optimal PV array configuration under PSC. The operation of switching is enhanced by simultaneously considering the total switching times and the operation of highly active switches. The simulation results on the 9×9 PV array demonstrate the effectiveness of the proposed framework in terms of reducing the number of local maximum power points on the power-voltage characteristic, enhancing power output, and relieving stress on the switching operation of the PV array under different PSC.

In the context of the increasing penetration of intermittent renewable energy resources (RES), one of the significant challenges facing traditional bulk power systems and microgrids is the scheduling generation units problem. Many studies have focused on solving the energy management problem for microgrids integrating RES. To address the intermittency caused by RES, flexible components such as battery energy storage systems (BESS) or demand response (DR) are considered. To clarify the problem of integrating these flexible components, a mixed-integer programming (MIP) approach for the unit commitment (UC) problem for microgrids with BESS and DR is proposed in this paper. An incentive-based demand response model as a negative power source and a detailed model for the vanadium redox battery (VRB) are introduced to improve the efficiency and reliability of microgrids. The objective optimization function, including the costs of generation, emissions, and maintenance, is minimized considering the uncertainty of the load and renewable energy sources. The obtained simulation results are compared with the genetic algorithm (GA) method as the basis for verification in different case studies. The obtained results have clarified the effect of using the BESS model and DR program on system operation.

This article examines in detail the characteristics of Dien Bien earthquake on 19 February 2001 and its aftershocks. On the basis of the temporal development of aftershocks and the spatial distribution of tectonic faults, five aftershock series have been determined. The analysis of spatial distribution and temporal evolution of these five aftershock series has clarified the development in the source zone of Dien Bien earthquake, which is closely related to the active and recent activities of tectonic faults in the area, especially Lai Chau Dien Bien fault. The comparison between characteristics of aftershock activities of Dien Bien earthquake and geomorphological features as well as tectonic activities in the area has indicated that the magnitude of these aftershocks and their temporal evolution (early or late) depend not only on the closer or further distance compared to the mainshock and the active faults that cause them but also on terrain elevation, slope index, lineament density and their positions relative to other tectonic faults in the studied area.

Complement-mediated damage to the neuromuscular junction (NMJ) is a key mechanism of pathology in myasthenia gravis (MG), and therapeutics inhibiting complement have shown evidence of efficacy in the treatment of MG. In this study, we describe the development of a subcutaneously administered N-acetylgalactosamine (GalNAc)-conjugated small interfering RNA (siRNA) targeting the C5 component of complement that silences C5 expression in the liver (ALN-CC5). Treatment of wild-type rodents with ALN-CC5 resulted in robust and durable suppression of liver C5 expression. Dose-dependent serum C5 suppression was observed in non-human primates, with a lowering of serum C5 of up to 97.5% and the concomitant inhibition of serum complement activity. C5 silencing was efficacious in ameliorating disease symptoms in two standard rat models of MG, demonstrating the key role of circulating C5 in pathology at the NMJ. Improvement in disease activity scores and NMJ pathology was observed at intermediate levels of complement activity inhibition, suggesting that complete ablation of complement activity may not be required for efficacy in MG. The pre-clinical studies of ALN-CC5 and efficacy of C5 silencing in rat models of MG support further clinical development of ALN-CC5 as a potential therapeutic for the treatment of MG and other complement-mediated disorders. Keywords: myasthenia gravis, small-interfering RNA, complement pathway, siRNA therapeutic

Partial shading conditions (PSC) have negative effects on the operation of photovoltaic (PV) systems. In this paper, a PV array reconfiguration method is developed to minimize power losses of PV arrays under partial shading conditions. The proposed reconfiguration method is based on equalizing the reduction of the short-circuit current of the PV modules in the PV array. Eight state-of-the-art Convolutional Neural Network models are employed to estimate the effect of shading on the short-circuit current of a PV module. These models include LeNet-5, AlexNet, VGG 11, VGG 19, Inception V3, ResNet 18, ResNet 34, and ResNet 50. Among eight models, the VGG 19 achieves the best accuracy on 1842 sample images. Therefore, this model is used to estimate the ratio of the actual short-circuit current and the estimated short-circuit current in four studied shading scenarios. This ratio decides the switching rule between PV modules throughout the PV array under PSC. A 2×2 experimental PV array shows that the proposed reconfiguration method improves the output power from 5.81% to 25.19% in four shading patterns. Accordingly, the power losses are reduced from 1.32% to 13.75%. The power improvement and the reduction of power losses of the proposed dynamic PV array reconfiguration system under four case studies demonstrates its effectiveness in addressing the effects of PSC on the PV array.

Hybrid energy storage systems (HESS) for electric vehicles, which consist of lithium-ion batteries and supercapacitors, have become an increasing focus of research and development in recent years. The combination of the two combines the advantages of each storage technology (high energy density in batteries and high power density in supercapacitors) in one system. To effectively manage the energy flow between these two different storage technologies, an intelligent energy management system (EMS) is required. In the development of the EMS, it is usual to run preliminary checks in a simulation environment that is as close to reality as feasible already during the development process. For this purpose, this paper presents a concept for the creation of a simulation environment consisting of realistic routes and a holistic vehicle model. The realistic route data are generated by a route-generating algorithm, which accesses different map services via application programming interfaces (API) and retrieves real route data to generate a simulated route. By integrating further online services (e.g., OpenWeather API), the routes are further specified with, for example, real weather data, traffic data, speed limits and altitude data. For the complete vehicle model, components including the suspension, chassis and auxiliary consumers are simulated as blackbox models. The components that can be accessed during the simulation are simulated as white box models. These are the battery, the supercapacitor, the DC/DC converter and the electric motor. This allows the EMS to control and regulate the HESS in real time during the simulation. To validate the simulation environment presented here, a real BMW i3 was driven on a real route, and its energy demand was measured. The same route was simulated in the simulation environment with environmental conditions that were as realistic as feasible (traffic volume, traffic facilities, weather) and the vehicle model of the BMW i3. The resulting energy demand from the simulation was recorded. The results show that the simulated energy consumption value differs by only 1.92% from the real measured value. This demonstrates the accuracy of the simulation environment presented here.

Abstract Energy storage devices that efficiently use energy, in particular renewable energy, are being actively pursued. Aqueous redox supercapacitors, which operate in high ionic conductivity and environmentally friendly aqueous electrolytes, storing and releasing high amounts of charge with rapid response rate and long cycling life, are emerging as a solution for energy storage applications. At the core of these devices, electrode materials and their assembling into rational configurations are the main factors governing the charge storage properties of supercapacitors. Redox‐active metal compounds, particularly oxides and hydroxides that store charge via reversible valence change redox reactions with electrolyte ions, are prospective candidates to optimize the electrochemical performance of supercapacitors. To address this target, collaborative investigations, addressing different streams, from fundamental charge storage mechanisms and electrode materials engineering to need‐tailored device assemblies, are the key. Over the last few years, significant achievements in metal oxide and hydroxide–based aqueous supercapacitors have been reported. This work discusses the most recent achievements and trends in this field and brings into the spotlight the authors' viewpoints.

In this paper, the seven traditional models of photovoltaic (PV) modules are reviewed comprehensively to find out the appropriate model for reliability. All the models are validated using the Matlab code and graphical comparisons between models are made. The accuracy and convergence of each model is evaluated using the data of manufactured PV panels. Then, a novel model is proposed showing its consistent performance. The three most key parameters of the single-diode model are self-revised to adapt to various types of PV modules. This new method is verified in three types of PV panels’ data measured by the National Renewable Energy Laboratory (NREL), USA. The validated data show promising results when the error RMSEs’ range of the proposed model is under 0.36.

Nghiên cứu nhằm mục đích khảo sát khả năng của chitosan trong việc ức chế nấm Colletotrichum gloeosporioides gây bệnh thán thư trên xoài cát Hòa Lộc ở những điều kiện khác nhau. Thông qua nội dung nghiên cứu, một số yếu tố ảnh hưởng đến khả năng phát triển của nấm như điều kiện pH, nồng độ chitosan đã được khảo sát. Qua quá trình tiến hành phân lập nấm C. gloeosporioides đã quan sát được đặc điểm hình thái học, bào tử, khả năng phát triển và thời gian gây bệnh của nấm. Kết quả giải trình tự chuỗi gen 28S rRNA và so sánh trên ngân hàng gen bằng phần mềm BLAST cho thấy chủng nấm phân lập là C. gloeosporioides với mức độ tương đồng là 99. Từ các kết quả thí nghiệm tiến hành ức chế nấm mốc trên môi trường PDA, đối với môi trường ức chế PDA đặc thì nấm C. gloeosporioides bị ức chế tốt nhất ở pH là 5 và nồng độ chitosan 1%. Dựa vào kết quả in vitro, nghiên cứu tiến hành gây nhiễm nấm nhân tạo trên trái và khả năng ức chế của chitosan với nấm C. gloeosporioides. Kết quả cho thấy là chitosan có khả năng ức chế nấm trên trái đã gây nhiễm nhân tạo.

Objective. Thyrotoxic periodic paralysis (TPP), a known condition in Asian men, is becoming increasingly common in men from Western countries. Since suspicion for TPP as a differential in diagnosis is of utmost importance to avoid overcorrection of hypokalemia and other complications, we are reporting a case of TPP in a 25-year-old Caucasian male. Methods. The patient presented with intermittent lower extremity weakness after consumption of a large high-carbohydrate meal. Clinical examination revealed diffusely enlarged thyroid gland, no muscle power in lower extremities, tremors, and brisk deep tendon reflexes. Results. Clinical and laboratory findings were consistent with Graves’ disease and the patient had hypokalemia. The patient responded to potassium repletion and was treated with propylthiouracil and propranolol. After treatment with radioactive iodine, the patient developed postablative hypothyroidism for which he was treated with levothyroxine. Conclusion. Since this condition is overlooked by physicians in Western countries, we present a case of TPP in a Caucasian male thus showing the importance of consideration of TPP in Caucasians despite its rare occurrence and the need for prompt diagnosis to avoid the danger of hyperkalemia in management of the paralytic attack in TPP patients.