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1. Optimal fractional sliding mode control for the frequency stability of a hybrid industrial microgrid

Author

Dipak R. Swain, Sunita S. Biswal, Pravat Kumar Rout, P. K. Ray, and R. K. Jena

Subjects
microgrid (mg), hybrid microgrid (hmg), fractional sliding mode controller (fsmc) controller, iterative teaching-learning based optimizer (itlbo), distributed generator (dg), Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

The rising proportion of inverter-based renewable energy sources in current power systems has reduced the rotational inertia of overall microgrid systems. This may cause high-frequency fluctuations in the system leading to system instability. Several initiatives have been suggested concerning inertia emulation based on other integrated external energy sources, such as energy storage systems, to combat the ever-declining issue of inertia. Hence, to deal with the aforementioned issue, we suggest the development of an optimal fractional sliding mode control (FSMC)-based frequency stabilization strategy for an industrial hybrid microgrid. An explicit state-space industrial microgrids model comprised of several coordinated energy sources along with loads, storage systems, photovoltaic and wind farms, is considered. In addition to this, the impact of electric vehicles and batteries with adequate control of the state of charge was investigated due to their short regulation times and this helps to balance the power supply and demand that in turn brings the minimization of the frequency deviations. The performance of the FSMC controller is enhanced by setting optimal parameters by employing the tuning strategy based on an iterative teaching-learning-based optimizer (ITLBO). To justify the efficacy of the proposed controller, the simulated results were obtained under several system conditions by using a vehicle simulator in a MATLAB/Simulink environment. The results reveal the enhanced performance of the ITLBO optimized fractional sliding mode control to effectively damp the frequency oscillations and retain the frequency stability with robustness, quick damping, and reliability under different system conditions.

Published
2023
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2. Distilling physical origins of hardness in multi-principal element alloys directly from ensemble neural network models

Author

D. Beniwal, P. Singh, S. Gupta, M. J. Kramer, D. D. Johnson, and P. K. Ray

Subjects
Materials of engineering and construction. Mechanics of materials, TA401-492, Computer software, QA76.75-76.765
Abstract

Abstract Despite a plethora of data being generated on the mechanical behavior of multi-principal element alloys, a systematic assessment remains inaccessible via Edisonian approaches. We approach this challenge by considering the specific case of alloy hardness, and present a machine-learning framework that captures the essential physical features contributing to hardness and allows high-throughput exploration of multi-dimensional compositional space. The model, tested on diverse datasets, was used to explore and successfully predict hardness in Al x Ti y (CrFeNi)1-x-y , Hf x Co y (CrFeNi)1-x-y and Al x (TiZrHf)1-x systems supported by data from density-functional theory predicted phase stability and ordering behavior. The experimental validation of hardness was done on TiZrHfAl x . The selected systems pose diverse challenges due to the presence of ordering and clustering pairs, as well as vacancy-stabilized novel structures. We also present a detailed model analysis that integrates local partial-dependencies with a compositional-stimulus and model-response study to derive material-specific insights from the decision-making process.

Published
2022
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3. Eliminating H[subscript 2]S and Any Sulfide Reagents from Qualitative Inorganic Analysis: An Ultimate Solution to a Long-Standing Problem

Author

Gagan Chandra Mandal, Forid Saikh, Sumit K. Ray, Kuheli Pramanik, and Laboni Giri

Abstract

Detection of metal ions in solution has been performed without employing H[subscript 2]S or any other sulfide materials. The new method is free from the interference from anions. Identification of Na[superscript +], K[superscript +], and NH[subscript 4][superscript +] has been made possible directly from an aqueous extract of the sample mixture. A technique has been developed to identify Mg[superscript 2+] directly without group separation. Metal ions have been classified into four groups by sequential treatment with 5 N HCl, Na[subscript 2]SO[subscript 4], and 5 N NaOH as group reagents. In comparison to the existing method, it is much faster and, at the same time, reliable enough.

Published
2024
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10. Gastrointestinal barriers to levodopa transport and absorption in Parkinson's disease

Author

Leta, Valentina, Klingelhoefer, Lisa, Longardner, Katherine, Campagnolo, Marta, Levent, Hafize Çotur, Aureli, Federico, Metta, Vinod, Bhidayasiri, Roongroj, Chung‐Faye, Guy, Falup‐Pecurariu, Cristian, Stocchi, Fabrizio, Jenner, Peter, Warnecke, Tobias, Chaudhuri, K Ray, and Group, International Parkinson and Movement Disorders Society Non‐Motor Parkinson's Disease Study

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Parkinson's Disease, Digestive Diseases, Aging, Neurodegenerative, Brain Disorders, 2.1 Biological and endogenous factors, Aetiology, Neurological, Oral and gastrointestinal, Humans, Levodopa, Parkinson Disease, Antiparkinson Agents, Helicobacter Infections, Helicobacter pylori, Gastrointestinal Tract, absorption, constipation, delayed gastric emptying, diet, dysphagia, levodopa, medication, microbiota, Parkinson's disease, pharmacokinetics, transport, International Parkinson and Movement Disorders Society Non-Motor Parkinson's Disease Study Group, Neurology & Neurosurgery, Clinical sciences
Abstract

Levodopa is the gold standard for the symptomatic treatment of Parkinson's disease (PD). There are well documented motor and non-motor fluctuations, however, that occur almost inevitably once levodopa is started after a variable period in people with PD. Whilst brain neurodegenerative processes play a part in the pathogenesis of these fluctuations, a range of barriers across the gastrointestinal (GI) tract can alter levodopa pharmacokinetics, ultimately contributing to non-optimal levodopa response and symptoms fluctuations. GI barriers to levodopa transport and absorption include dysphagia, delayed gastric emptying, constipation, Helicobacter pylori infection, small intestinal bacterial overgrowth and gut dysbiosis. In addition, a protein-rich diet and concomitant medication intake can further alter levodopa pharmacokinetics. This can result in unpredictable or sub-optimal levodopa response, 'delayed on' or 'no on' phenomena. In this narrative review, we provided an overview on the plethora of GI obstacles to levodopa transport and absorption in PD and their implications on levodopa pharmacokinetics and development of motor fluctuations. In addition, management strategies to address GI dysfunction in PD are highlighted, including use of non-oral therapies to bypass the GI tract.

Published
2023

13. A 12-month prospective real-life study of opicapone efficacy and tolerability in Emirati and non-White subjects with Parkinson’s disease based in United Arab Emirates

Author

Metta, Vinod, Ibrahim, Huzaifa, Muralidharan, Neha, Rodriguez, Kislyn, Masagnay, Therese, Mohan, Judith, Lacsina, Arlet, Ahmed, Abdullah, Benamer, Hani T. S., Chung-Faye, Guy, Mrudula, Rukmini, Falup-Pecurariu, Cristian, Rodriguez-Blazquez, Carmen, Borgohain, Rupam, Goyal, Vinay, Bhattacharya, Kalyan, and Chaudhuri, K. Ray

Published
2024
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14. Continuous Subcutaneous Foslevodopa/Foscarbidopa in Parkinson’s Disease: Safety and Efficacy Results From a 12-Month, Single-Arm, Open-Label, Phase 3 Study

Author

Aldred, Jason, Freire-Alvarez, Eric, Amelin, Alexander V., Antonini, Angelo, Bergmans, Bruno, Bergquist, Filip, Bouchard, Manon, Budur, Kumar, Carroll, Camille, Chaudhuri, K. Ray, Criswell, Susan R., Danielsen, Erik H., Gandor, Florin, Jia, Jia, Kimber, Thomas E., Mochizuki, Hideki, Robieson, Weining Z., Spiegel, Amy M., Standaert, David G., Talapala, Saritha, Facheris, Maurizio F., and Fung, Victor S. C.

Published
2023
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15. Detecting Parkinsonian Tremor from IMU Data Collected In-The-Wild using Deep Multiple-Instance Learning

Author

Papadopoulos, Alexandros, Kyritsis, Konstantinos, Klingelhoefer, Lisa, Bostanjopoulou, Sevasti, Chaudhuri, K. Ray, and Delopoulos, Anastasios

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Machine Learning
Abstract

Parkinson's Disease (PD) is a slowly evolving neuro-logical disease that affects about 1% of the population above 60 years old, causing symptoms that are subtle at first, but whose intensity increases as the disease progresses. Automated detection of these symptoms could offer clues as to the early onset of the disease, thus improving the expected clinical outcomes of the patients via appropriately targeted interventions. This potential has led many researchers to develop methods that use widely available sensors to measure and quantify the presence of PD symptoms such as tremor, rigidity and braykinesia. However, most of these approaches operate under controlled settings, such as in lab or at home, thus limiting their applicability under free-living conditions. In this work, we present a method for automatically identifying tremorous episodes related to PD, based on IMU signals captured via a smartphone device. We propose a Multiple-Instance Learning approach, wherein a subject is represented as an unordered bag of accelerometer signal segments and a single, expert-provided, tremor annotation. Our method combines deep feature learning with a learnable pooling stage that is able to identify key instances within the subject bag, while still being trainable end-to-end. We validate our algorithm on a newly introduced dataset of 45 subjects, containing accelerometer signals collected entirely in-the-wild. The good classification performance obtained in the conducted experiments suggests that the proposed method can efficiently navigate the noisy environment of in-the-wild recordings.

Published
2020
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17. Non-motor predictors of 36-month quality of life after subthalamic stimulation in Parkinson disease

Author

Jost, Stefanie T, Visser-Vandewalle, Veerle, Rizos, Alexandra, Loehrer, Philipp A, Silverdale, Monty, Evans, Julian, Samuel, Michael, Petry-Schmelzer, Jan Niklas, Sauerbier, Anna, Gronostay, Alexandra, Barbe, Michael T, Fink, Gereon R, Ashkan, Keyoumars, Antonini, Angelo, Martinez-Martin, Pablo, Chaudhuri, K Ray, Timmermann, Lars, and Dafsari, Haidar S

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Aging, Brain Disorders, Neurosciences, Parkinson's Disease, Clinical Research, Rehabilitation, Neurodegenerative, Neurological, EUROPAR and the International Parkinson and Movement Disorders Society Non-Motor Parkinson’s Disease Study Group, Biological psychology, Cognitive and computational psychology
Abstract

To identify predictors of 36-month follow-up quality of life (QoL) outcome after bilateral subthalamic nucleus deep brain stimulation (STN-DBS) in Parkinson's disease (PD). In this ongoing, prospective, multicenter international study (Cologne, Manchester, London) including 73 patients undergoing STN-DBS, we assessed the following scales preoperatively and at 6-month and 36-month follow-up: PD Questionnaire-8 (PDQ-8), NMSScale (NMSS), Scales for Outcomes in PD (SCOPA)-motor examination, -activities of daily living, and -complications, and levodopa equivalent daily dose (LEDD). We analyzed factors associated with QoL improvement at 36-month follow-up based on (1) correlations between baseline test scores and QoL improvement, (2) step-wise linear regressions with baseline test scores as independent and QoL improvement as dependent variables, (3) logistic regressions and receiver operating characteristic curves using a dichotomized variable "QoL responders"/"non-responders". At both follow-ups, NMSS total score, SCOPA-motor examination, and -complications improved and LEDD was reduced significantly. PDQ-8 improved at 6-month follow-up with subsequent decrements in gains at 36-month follow-up when 61.6% of patients were categorized as "QoL non-responders". Correlations, linear, and logistic regression analyses found greater PDQ-8 improvements in patients with younger age, worse PDQ-8, and worse specific NMS at baseline, such as 'difficulties experiencing pleasure' and 'problems sustaining concentration'. Baseline SCOPA scores were not associated with PDQ-8 changes. Our results provide evidence that 36-month QoL changes depend on baseline neuropsychological and neuropsychiatric non-motor symptoms burden. These findings highlight the need for an assessment of a wide range of non-motor and motor symptoms when advising and selecting individuals for DBS therapy.

Published
2021

18. Correction: Continuous Subcutaneous Foslevodopa/Foscarbidopa in Parkinson’s Disease: Safety and Efficacy Results From a 12-Month, Single-Arm, Open-Label, Phase 3 Study

Author

Aldred, Jason, Freire-Alvarez, Eric, Amelin, Alexander V., Antonini, Angelo, Bergmans, Bruno, Bergquist, Filip, Bouchard, Manon, Budur, Kumar, Carroll, Camille, Chaudhuri, K. Ray, Criswell, Susan R., Danielsen, Erik H., Gandor, Florin, Jia, Jia, Kimber, Thomas E., Mochizuki, Hideki, Robieson, Weining Z., Spiegel, Amy M., Standaert, David G., Talapala, Saritha, Facheris, Maurizio F., and Fung, Victor S. C.

Published
2023
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23. Opicapone versus placebo in the treatment of Parkinson’s disease patients with end-of-dose motor fluctuation-associated pain: rationale and design of the randomised, double-blind OCEAN (OpiCapone Effect on motor fluctuations and pAiN) trial

Author

Chaudhuri, K. Ray, Odin, Per, Ferreira, Joaquim J., Antonini, Angelo, Rascol, Olivier, Kurtis, Mónica M., Storch, Alexander, Bannister, Kirsty, Soares-da-Silva, Patrício, Costa, Raquel, Magalhães, Diogo, and Rocha, José Francisco

Published
2022
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27. Does the 5–2-1 criteria identify patients with advanced Parkinson's disease? Real-world screening accuracy and burden of 5–2-1-positive patients in 7 countries

Author

Malaty, Irene A., Martinez-Martin, Pablo, Chaudhuri, K. Ray, Odin, Per, Skorvanek, Matej, Jimenez-Shahed, Joohi, Soileau, Michael J., Lindvall, Susanna, Domingos, Josefa, Jones, Sarah, Alobaidi, Ali, Jalundhwala, Yash J., Kandukuri, Prasanna L., Onuk, Koray, Bergmann, Lars, Femia, Samira, Lee, Michelle Y., Wright, Jack, and Antonini, Angelo

Published
2022
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35. Cross-sectional analysis of the Parkinson’s disease Non-motor International Longitudinal Study baseline non-motor characteristics, geographical distribution and impact on quality of life

Author

van Wamelen, Daniel J., Sauerbier, Anna, Leta, Valentina, Rodriguez-Blazquez, Carmen, Falup-Pecurariu, Cristian, Rodriguez‐Violante, Mayela, Rizos, Alexandra, Tsuboi, Y., Metta, Vinod, Bhidayasiri, Roongroj, Bhattacharya, Kalyan, Borgohain, Rupam, Prashanth, L. K., Rosales, Raymond, Lewis, Simon, Fung, Victor, Behari, Madhuri, Goyal, Vinay, Kishore, Asha, Lloret, Santiago Perez, Martinez-Martin, Pablo, and Chaudhuri, K. Ray

Published
2021
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38. Validation Study of the Parkinson’s Disease Stigma Questionnaire (PDStigmaQuest)

Author

Stopic, Vasilija, Jost, Stefanie T., Haupt, Julius, Brandt, Gregor A., van der Linden, Christina, Petry-Schmelzer, Jan Niklas, Dembek, Till A., Fink, Gereon R., Batzu, Lucia, Rizos, Alexandra, Chaudhuri, K. Ray, Dafsari, Haidar S., Gruber, Doreen, Ebersbach, Georg, Kessler, Josef, Barbe, Michael T., and Sauerbier, Anna

Abstract

Background: Stigma is a relevant aspect of Parkinson’s disease (PD). Specific stigma tools are needed to address the complex construct of stigma in PD comprehensively.Objective: To test the dimensionality and psychometric properties of the newly developed Parkinson’s Disease Stigma Questionnaire (PDStigmaQuest).Methods: In this multi-center, cross-sectional study including PD patients and healthy controls, the dimensionality of the PDStigmaQuest was examined through exploratory factor analysis. Acceptability and psychometric properties were investigated. PDStigmaQuest scores of patients and healthy controls were compared.Results: In total, 201 PD patients and 101 healthy controls were included in the final analysis. Results suggested high data quality of the PDStigmaQuest (0.0001% missing data for patients). The exploratory factor analysis produced four factors: felt stigma, hiding, enacted stigma: rejection, and enacted stigma: patronization, explaining 47.9% of variance. An optional work domain for employed patients was included. Moderate floor effects and skewness, but no ceiling effects were found. Cronbach’s alpha of 0.85 indicated high internal consistency. Calculated item-total correlations met standard criteria. Test-retest reliability was high (rs= 0.83). PDStigmaQuest scores correlated significantly with other stigma measures (rs= 0.56–0.69) and were significantly higher in patients than in healthy controls and higher in patients with depressive symptoms than in those without.Conclusions: The patient-reported 18-item PDStigmaQuest showed strong psychometric properties of validity and reliability. Our results suggest that the PDStigmaQuest can be used to assess and evaluate stigma comprehensively in PD, which will improve our understanding of the construct of PD stigma.

Published
2024
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45. Characterization of duck germplasm of eastern hill and plateau region of Jharkhand

Author

REENA KAMAL, P C CHANDRAN, AMITAVA DEY, M S TANTIA, P K RAY, R KUMARI, and KAMAL SARMA

Subjects
General Veterinary, Animal Science and Zoology
Abstract

Information about phenotypic characteristics is a basic need in animal genetic resource conservation and improvement. Phenotypic characteristics of Jharkhand ducks from six districts (Palamu, Gadhwa, Latehar, Lohardaga, Khuti, and Simdega) were studied. Data on morphological and morphometric traits were analyzed. The results revealed that the predominant plumage colours of the head, neck, breast, wings and tails were black (56.25%) in drake, and black and white mix (65.33%) in duck; white and black/brown mix (62.50%) in drake, and white (79.33%) in duck; brown (41.25%) in drake, and white and black/brown mix (52.67%) in duck; black/brown and white mix (43.75%) in drake and duck (74.67%); black in drake (75%) and duck (90%) respectively. The dominant bill colour in drake was greenish black (56.25%) followed by orange (25%) and duck bill colour was black (58.67%) followed by orange (22%), whereas dominant eye colour was brown in both the sexes. The predominant shank and web colour were orange (65.0%) in drake and duck (68.0%) respectively. The Jharkhand ducks are unique in their morphological features with attractive black and white plumage colour pattern. The ducks are well acclimatised to local agro-climatic conditions with less input from duck farmers. The hatching and brooding process are natural. The average egg production was 66.92±2.00 eggs. The average adult body weights of drake and ducks were 1.64±23.19 and 1.51±30.09 kg, respectively. Variations were observed in qualitative traits. The observed phenotypic diversity in Jharkhand local ducks could be useful in designing breeding programs and selection.

Published
2022
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49. Optimal fractional sliding mode control for the frequency stability of a hybrid industrial microgrid

Author

Dipak R. Swain, Sunita S. Biswal, Pravat Kumar Rout, P. K. Ray, and R. K. Jena

Subjects
Control and Systems Engineering, Electrical and Electronic Engineering, Computer Science Applications
Abstract

The rising proportion of inverter-based renewable energy sources in current power systems has reduced the rotational inertia of overall microgrid systems. This may cause high-frequency fluctuations in the system leading to system instability. Several initiatives have been suggested concerning inertia emulation based on other integrated external energy sources, such as energy storage systems, to combat the ever-declining issue of inertia. Hence, to deal with the aforementioned issue, we suggest the development of an optimal fractional sliding mode control (FSMC)-based frequency stabilization strategy for an industrial hybrid microgrid. An explicit state-space industrial microgrids model comprised of several coordinated energy sources along with loads, storage systems, photovoltaic and wind farms, is considered. In addition to this, the impact of electric vehicles and batteries with adequate control of the state of charge was investigated due to their short regulation times and this helps to balance the power supply and demand that in turn brings the minimization of the frequency deviations. The performance of the FSMC controller is enhanced by setting optimal parameters by employing the tuning strategy based on an iterative teaching-learning-based optimizer (ITLBO). To justify the efficacy of the proposed controller, the simulated results were obtained under several system conditions by using a vehicle simulator in a MATLAB/Simulink environment. The results reveal the enhanced performance of the ITLBO optimized fractional sliding mode control to effectively damp the frequency oscillations and retain the frequency stability with robustness, quick damping, and reliability under different system conditions.

Published
2022
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