bluuebunny/crossref_metadata_2025 huggingface dataset:
Implication of IL-7 receptor alpha chain expression by CD8+ T cells and its signature in defining biomarkers in aging
Authors: Shin Min Sun , Park Hong-Jai , Young Juan , Kang Insoo
Published: December 2022

CD8+T cells play an important role in host defense against infections and malignancies as well as contribute to the development of inflammatory disorders. Alterations in the frequency of naïve and memory CD8+T cells are one of the most significant changes in the immune system with age. As the world population rapidly ages, a better understanding of aging immune function or immunosenescence could become a basis for discovering treatments of illnesses that commonly occur in older adults. In particular, biomarkers for immune aging could be utilized to identify individuals at high risk of developing age-associated conditions and help monitor the efficacy of therapeutic interventions targeting such conditions. This review details the possible role of CD8+T cell subsets expressing different levels of the cytokine receptor IL-7 receptor alpha chain (IL-7Rα) and the gene signature associated with IL-7Rα as potential biomarkers for immune aging given the association of CD8+T cells in host defense, inflammation, and immunosenescence.
LncRNA EBLN3P attributes methotrexate resistance in osteosarcoma cells through miR-200a-3p/O-GlcNAc transferase pathway
Authors: Sun Ming-Xia , An Hai-Yan , Sun Yan-Bin , Sun Yan-bao , Bai Bing
Published: December 2022

Background

Osteosarcoma is highly malignant. The migration, invasion, and chemoresistance contribute to poor prognosis of osteosarcoma. Research reported that endogenous bornavirus-like nucleoprotein 3 pseudogene (EBLN3P) promotes the progression of osteosarcoma.

Methods

In this study, the expression of EBLN3P in osteosarcoma tissue with different methotrexate (MTX) treatment responses was measured. Osteosarcoma cell lines with MTX resistance were constructed, and bioinformatic analysis was performed to explore the potential involved targets and pathways.

Results

Higher EBLN3P was associated with MTX resistance. Downregulation of LncEBLN3P decreased the MTX resistance of osteosarcoma cells by sponging miR-200a-3p, an important microRNA that affects epithelial-mesenchymal transition (EMT). The decreased miR-200a-3p resulted in the upregulation of its target gene O-GlcNAc transferase (OGT), which in turn promoted the EMT process of osteosarcoma cells. Further analysis confirmed that the loss of OGT and over-expression of miR-200a-3p could partly abolish the MTX resistance induced by LncEBLN3P.

Conclusion

LncEBLN3P is upregulated in osteosarcoma and increases the MTX resistance in osteosarcoma cells through downregulating miR-200a-3p, which in turn promoted the EMT process of osteosarcoma cells by increasing the OGT.
Gentamicin-loaded chitosan/folic acid-based carbon quantum dots nanocomposite hydrogel films as potential antimicrobial wound dressing
Authors: Kazeminava Fahimeh , Javanbakht Siamak , Nouri Mohammad , Gholizadeh Pourya , Nezhad-Mokhtari Parinaz , Ganbarov Khudaverdi , Tanomand Asghar , Kafil Hossein Samadi
Published: December 2022

Background

To provide effective healing in the wound, various carbohydrate polymers are commonly utilized that are highly potent platforms as wound dressing films. In this work, novel antibacterial flexible polymeric hydrogel films were designed via crosslinking polymeric chitosan (CS) with folic acid-based carbon quantum dots (CQDs). To end this, folic acid as a bio-precursor is used to synthesize CQDs through the hydrothermal technique. The synthesized CQDs as a crosslinking agent was performed at different concentrations to construct nanocomposite hydrogel films via the casting technique. Also, gentamicin (GM), L-Arginine and glycerol were supplemented in the formulation of nanocomposite since their antibiotic, bioactivity and plasticizing ability, respectively.

Results

The successful construction of films were verified with different methods (FT-IR, UV-Vis, PL, SEM, and AFM analyses). The GM release profile displayed a controlled release manner over 48 h with a low initial burst release in the simulated wound media (PBS, pH 7.4). Antibacterial and in vitro cytotoxicity results showed a significant activity toward different gram-positive and negative bacterial strains (about 2.5 ± 0.1 cm inhibition zones) and a desired cytocompatibility against Human skin fibroblast (HFF-1) cells (over 80% cell viability), respectively.

Conclusion

The obtained results recommend CQDs-crosslinked CS (CS/CQD) nanocomposite as a potent antimicrobial wound dressing.

Graphical Abstract
Breast cancer worry, uncertainty, and perceived risk following breast density notification in a longitudinal mammography screening cohort
Authors: Lee Argov Erica J. , Rodriguez Carmen B. , Agovino Mariangela , Wei Ying , Shelton Rachel C. , Kukafka Rita , Schmitt Karen M. , Desperito Elise , Terry Mary Beth , Tehranifar Parisa
Published: December 2022

Background

Dense breast notification (DBN) legislation aims to increase a woman’s awareness of her personal breast density and the implications of having dense breasts for breast cancer detection and risk. This information may adversely affect women’s breast cancer worry, perceptions of risk, and uncertainty about screening, which may persist over time or vary by sociodemographic factors. We examined short- and long-term psychological responses to DBN and awareness of breast density (BD).

Methods

In a predominantly Hispanic New York City screening cohort (63% Spanish-speaking), ages 40–60 years, we assessed breast cancer worry, perceived breast cancer risk, and uncertainties about breast cancer risk and screening choices, in short (1–3 months)- and long-term (9–18 months) surveys following the enrollment screening mammogram (between 2016 and 2018). We compared psychological responses by women’s dense breast status (as a proxy for DBN receipt) and BD awareness and examined multiplicative interaction by education, health literacy, nativity, and preferred interview language.

Results

In multivariable models using short-term surveys, BD awareness was associated with increased perceived risk (odds ratio (OR) 2.27, 95% confidence interval (CI) 0.99, 5.20 for high, OR 2.19, 95% CI 1.34, 3.58 for moderate, vs. low risk) in the overall sample, and with increased uncertainty about risk (OR 1.97 per 1-unit increase, 95% CI 1.15, 3.39) and uncertainty about screening choices (OR 1.73 per 1-unit increase, 95% CI 1.01, 2.9) in Spanish-speaking women. DBN was associated with decreased perceived risk among women with at least some college education (OR 0.32, 95% CI 0.11, 0.89, for high, OR 0.50, 95% CI 0.29, 0.89, for moderate vs. low risk), while those with a high school education or less experienced an increase (OR 3.01, 95% CI 1.05, 8.67 high vs. low risk). There were no associations observed between DBN or BD awareness and short-term breast cancer worry, nor with any psychological outcomes at long-term surveys.

Conclusions

Associations of BD awareness and notification with breast cancer-related psychological outcomes were limited to short-term increases in perceived breast cancer risk dependent on educational attainment, and increases in uncertainty around breast cancer risk and screening choices among Spanish-speaking women.
Sample size requirement in trials that use the composite endpoint major adverse cardiovascular events (MACE): new insights
Authors: Marsal Josep Ramon , Urreta-Barallobre Iratxe , Ubeda-Carrillo Marimar , Osorio Dimelza , Lumbreras Blanca , Lora David , Fernández-Felix Borja M. , Oristrell Gerard , Ródenas-Alesina Eduard , Herrador Lorena , Ballesteros Mónica , Zamora Javier , Pijoan Jose I. , Ribera Aida , Ferreira-González Ignacio
Published: December 2022

Background

The real impact of the degree of association (DoA) between endpoint components of a composite endpoint (CE) on sample size requirement (SSR) has not been explored. We estimate the impact of the DoA between death and acute myocardial infarction (AMI) on SSR of trials using use the CE of major adverse cardiac events (MACE).

Methods

A systematic review and quantitative synthesis of trials that include MACE as the primary outcome through search strategies in MEDLINE and EMBASE electronic databases. We limited to articles published in journals indexed in the first quartile of the Cardiac & Cardiovascular Systems category (Journal Citation Reports, 2015–2020). The authors were contacted to estimate the DoA between death and AMI using joint probability and correlation. We analyzed the SSR variation using the DoA estimated from RCTs.

Results

Sixty-three of 134 publications that reported event rates and the therapy effect in all component endpoints were included in the quantitative synthesis. The most frequent combination was death, AMI, and revascularization (n = 20; 31.8%). The correlation between death and AMI, estimated from 5 trials¸ oscillated between − 0.02 and 0.31. SSR varied from 14,602 in the scenario with the strongest correlation to 12,259 in the scenario with the weakest correlation; the relative impact was 16%.

Conclusions

The DoA between death and AMI is highly variable and may lead to a considerable SSR variation in a trial including MACE.
Genetic polymorphism, constitutive expression and tissue localization of Dirofilaria immitis P-glycoprotein 11: a putative marker of macrocyclic lactone resistance
Authors: Curry Emily , Prichard Roger , Lespine Anne
Published: December 2022

Background

Dirofilaria immitis causes dirofilariosis, a potentially fatal condition in canids. Dirofilaria infections can be prevented with a macrocyclic lactone (ML) prophylactic regimen. However, some D. immitis isolates have become resistant to MLs. Genetic changes on the P-glycoprotein 11 gene, encoding an ABCB transporter, have been linked to the ML-resistant phenotypes and have been proposed as markers of drug resistance. However, nothing is known about the expression and the localization of this transporter in D. immitis, despite its strong link to ML-resistant phenotypes.

Methods

We examined the clinically validated D. immitis P-glycoprotein 11 (DimPgp-11) single nucleotide polymorphism (SNP) via MiSeq analysis in three ML-susceptible isolates (Missouri, MP3 and Yazoo) and two ML-resistant isolates (JYD-34 and Metairie), and correlated the data with previously published MiSeq results of USA laboratory-maintained D. immitis isolates. The level of the expression of the DimPgp-11 messenger RNA transcript was analyzed by droplet digital PCR (ddPCR) and compared in the USA laboratory-maintained isolates, namely the ML-susceptible Missouri and Berkeley isolates, the putative ML-susceptible Georgia III and Big Head isolates and the ML-resistant isolate JYD-34. The immunolocalization of DimPgp-11 was visualized in the microfilaria (mf) life stage of the Missouri isolate using confocal microscopy.

Results

The results confirmed that the SNP found on DimPgp-11 is differentially expressed in the USA laboratory-maintained isolates. The ML-susceptible isolates had an alternate allele frequency of between 0% and 15%, while it ranged between 17% and 56% in the ML-resistant isolates. The constitutive expression of DimPgp-11 was similar in the Berkeley, Georgia III and Big Head isolates, while it was significantly decreased in the ML-resistant JYD-34 isolate (P < 0.05), when compared to the ML-susceptible Missouri isolate. The DimPgp-11 protein was distinctly localized within the excretory-secretory (ES) duct, pore cells and the excretory cell and, more faintly, along the mf body wall.

Conclusion

Our data confirm that genetic polymorphism of DimPgp-11 is associated with ML resistance in USA laboratory-maintained D. imminits isolates. A link between DimPgp-11 and ML resistance in D. immitis is further supported by the lower protein expression in the ML-resistant JYD-34 isolate when compared with the ML-susceptible Missouri isolate. Interestingly, DimPgp-11 is strategically located surrounding the ES pore where it could play an active role in ML efflux.

Graphical Abstract
Transient Polycomb activity represses developmental genes in growing oocytes
Authors: Jarred Ellen G. , Qu Zhipeng , Tsai Tesha , Oberin Ruby , Petautschnig Sigrid , Bildsoe Heidi , Pederson Stephen , Zhang Qing-hua , Stringer Jessica M. , Carroll John , Gardner David K. , Van den Buuse Maarten , Sims Natalie A. , Gibson William T. , Adelson David L. , Western Patrick S.
Published: December 2022

Background

Non-genetic disease inheritance and offspring phenotype are substantially influenced by germline epigenetic programming, including genomic imprinting. Loss of Polycomb Repressive Complex 2 (PRC2) function in oocytes causes non-genetically inherited effects on offspring, including embryonic growth restriction followed by post-natal offspring overgrowth. While PRC2-dependent non-canonical imprinting is likely to contribute, less is known about germline epigenetic programming of non-imprinted genes during oocyte growth. In addition, de novo germline mutations in genes encoding PRC2 lead to overgrowth syndromes in human patients, but the extent to which PRC2 activity is conserved in human oocytes is poorly understood.

Results

In this study, we identify a discrete period of early oocyte growth during which PRC2 is expressed in mouse growing oocytes. Deletion of Eed during this window led to the de-repression of 343 genes. A high proportion of these were developmental regulators, and the vast majority were not imprinted genes. Many of the de-repressed genes were also marked by the PRC2-dependent epigenetic modification histone 3 lysine 27 trimethylation (H3K27me3) in primary–secondary mouse oocytes, at a time concurrent with PRC2 expression. In addition, we found H3K27me3 was also enriched on many of these genes by the germinal vesicle (GV) stage in human oocytes, strongly indicating that this PRC2 function is conserved in the human germline. However, while the 343 genes were de-repressed in mouse oocytes lacking EED, they were not de-repressed in pre-implantation embryos and lost H3K27me3 during pre-implantation development. This implies that H3K27me3 is a transient feature that represses a wide range of genes in oocytes.

Conclusions

Together, these data indicate that EED has spatially and temporally distinct functions in the female germline to repress a wide range of developmentally important genes and that this activity is conserved in the mouse and human germlines.
Development and validation of MRI-based model for the preoperative prediction of macrotrabecular hepatocellular carcinoma subtype
Authors: Bilal Masokano Ismail , Pei Yigang , Chen Juan , Liu Wenguang , Xie Simin , Liu Huaping , Feng Deyun , He Qiongqiong , Li Wenzheng
Published: December 2022

Background

Macrotrabecular hepatocellular carcinoma (MTHCC) has a poor prognosis and is difficult to diagnose preoperatively. The purpose is to build and validate MRI-based models to predict the MTHCC subtype.

Methods

Two hundred eight patients with confirmed HCC were enrolled. Three models (model 1: clinicoradiologic model; model 2: fusion radiomics signature; model 3: combined model 1 and model 2) were built based on their clinical data and MR images to predict MTHCC in training and validation cohorts. The performance of the models was assessed using the area under the curve (AUC). The clinical utility of the models was estimated by decision curve analysis (DCA). A nomogram was constructed, and its calibration was evaluated.

Results

Model 1 is easier to build than models 2 and 3, with a good AUC of 0.773 (95% CI 0.696–0.838) and 0.801 (95% CI 0.681–0.891) in predicting MTHCC in training and validation cohorts, respectively. It performed slightly superior to model 2 in both training (AUC 0.747; 95% CI 0.689–0.806; p = 0.548) and validation (AUC 0.718; 95% CI 0.618–0.810; p = 0.089) cohorts and was similar to model 3 in the validation (AUC 0.866; 95% CI 0.801–0.928; p = 0.321) but inferior in the training (AUC 0.889; 95% CI 0.851–0.926; p = 0.001) cohorts. The DCA of model 1 had a higher net benefit than the treat-all and treat-none strategy at a threshold probability of 10%. The calibration curves of model 1 closely aligned with the true MTHCC rates in the training (p = 0.355) and validation sets (p = 0.364).

Conclusion

The clinicoradiologic model has a good performance in diagnosing MTHCC, and it is simpler and easier to implement, making it a valuable tool for pretherapeutic decision-making in patients.
The prevalence of low muscle mass associated with obesity in the USA
Authors: Murdock Dana J. , Wu Ning , Grimsby Joseph S. , Calle Roberto A. , Donahue Stephen , Glass David J. , Sleeman Mark W. , Sanchez Robert J.
Published: December 2022

Background

Sarcopenia is defined as age-related low muscle mass and function, and can also describe the loss of muscle mass in certain medical conditions, such as sarcopenic obesity. Sarcopenic obesity describes loss of muscle and function in obese individuals; however, as sarcopenia is an age-related condition and obesity can occur in any age group, a more accurate term is obesity with low lean muscle mass (OLLMM). Given limited data on OLLMM (particularly in those aged < 65 years), the purpose of this study was to estimate the prevalence of OLLMM in adults aged ≥ 20 years in the USA.

Methods

Data from the National Health and Nutrition Examination Survey (NHANES) 2017–2018 and 1999–2006 were used. OLLMM was defined as an appendicular lean mass, adjusted for body mass index (BMI), cut-off point < 0.789 for males and < 0.512 for females, measured by dual-energy X-ray absorptiometry (DXA). DXA was only measured in individuals 20–59 years old in NHANES 2017–2018; we therefore utilized logistic regression models to predict OLLMM from NHANES 1999–2006 for those aged ≥ 60 years. The prevalence of OLLMM was estimated overall, and by sex, age, race/ethnicity, and clinical subgroup (high BMI, prediabetes, type 2 diabetes mellitus [T2DM], non-alcoholic fatty liver disease [NAFLD] with fibrosis, or post-bariatric surgery). Prevalence estimates were extrapolated to the USA population using NHANES sampling weights.

Results

We estimated that, during 2017–2018, 28.7 million or 15.9% of the USA population had OLLMM. The prevalence of OLLMM was greater in older individuals (8.1%, aged 20–59 years vs 28.3%, aged ≥ 60 years), highest (66.6%) in Mexican-American females aged ≥ 60 years, and lowest (2.6%) in non-Hispanic Black males aged 20–59 years. There was a higher prevalence of OLLMM in adults with prediabetes (19.7%), T2DM (34.5%), NAFLD with fibrosis (25.4%), or post-bariatric surgery (21.8%), compared with those without each condition.

Conclusions

Overall, the burden of OLLMM in the USA is substantial, affecting almost 30 million adults. The prevalence of OLLMM increased with age, and among those with prediabetes, T2DM, NAFLD with fibrosis, or post-bariatric surgery. A unified definition of OLLMM will aid diagnosis and treatment strategies.
A deep learning based steganography integration framework for ad-hoc cloud computing data security augmentation using the V-BOINC system
Authors: Mawgoud Ahmed A. , Taha Mohamed Hamed N. , Abu-Talleb Amr , Kotb Amira
Published: December 2022

In the early days of digital transformation, the automation, scalability, and availability of cloud computing made a big difference for business. Nonetheless, significant concerns have been raised regarding the security and privacy levels that cloud systems can provide, as enterprises have accelerated their cloud migration journeys in an effort to provide a remote working environment for their employees, primarily in light of the COVID-19 outbreak. The goal of this study is to come up with a way to improve steganography in ad hoc cloud systems by using deep learning. This research implementation is separated into two sections. In Phase 1, the “Ad-hoc Cloud System” idea and deployment plan were set up with the help of V-BOINC. In Phase 2, a modified form of steganography and deep learning were used to study the security of data transmission in ad-hoc cloud networks. In the majority of prior studies, attempts to employ deep learning models to augment or replace data-hiding systems did not achieve a high success rate. The implemented model inserts data images through colored images in the developed ad hoc cloud system. A systematic steganography model conceals from statistics lower message detection rates. Additionally, it may be necessary to incorporate small images beneath huge cover images. The implemented ad-hoc system outperformed Amazon AC2 in terms of performance, while the execution of the proposed deep steganography approach gave a high rate of evaluation for concealing both data and images when evaluated against several attacks in an ad-hoc cloud system environment.
Improved Jellyfish Algorithm-based multi-aspect task scheduling model for IoT tasks over fog integrated cloud environment
Authors: Jangu Nupur , Raza Zahid
Published: December 2022

Corporations and enterprises creating IoT-based systems frequently use fog computing integrated with cloud computing to harness the benefits offered by both. These computing paradigms use virtualization and a pay-as-you-go strategy to provide IT resources, including CPU, memory, network and storage. Resource management in such a hybrid environment becomes a challenging task. This problem is exacerbated in the IoT environment, as it generates deadline-driven and heterogeneous data demanding real-time processing. This work proposes an efficient two-step scheduling algorithm comprising a Bi-factor classification task phase based on deadline and priority and a scheduling phase using an enhanced artificial Jellyfish Search Optimizer (JS) proposed as an Improved Jellyfish Algorithm (IJFA). The model considers a variety of cloud and fog resource parameters, including speed, capacity, task size, number of tasks, and number of virtual machines for resource provisioning in a fog integrated cloud environment. The model has been tested for the real-time task scenario with the number of tasks considering both the smaller workload and the relatively higher workload scenario matching the real-time situation. The model addresses the Quality of Service (QoS) parameters of minimizing the batch’s make-span time, lowering the batch execution costs, and increasing the resource utilization. Simulation results prove the effectiveness of the proposed model.
Distributed fuzzy clustering algorithm for mixed-mode data in Apache SPARK
Authors: Akram Abdul Wahab , Alamgir Zareen
Published: December 2022

Fuzzy clustering is an invaluable data mining technique that allows each data point to belong to more than one cluster with some degree of membership. It is widely employed in exploratory data mining to discover overlapping communities in social networks, find structure in spectral data, and capture user interests in recommendation systems. Nowadays, the variety and volume of data are increasing at a tremendous rate. Data is power; the massive data, along with an effective technique, can unravel valuable information. The existing fuzzy clustering algorithms do not perform well on massive heterogeneous datasets. Processing an enormous amount of data is beyond the capacity of a single processor. The need of the hour is to develop fuzzy clustering techniques that can work on a distributed framework for Big Data processing and can handle heterogeneous data. In this research, we evaluate the performance of the recently proposed algorithm for the Fuzzy clustering of mixed-mode data FCMD-MD (D’Urso and Massari in Inf Sci 505:513–534, 2019) with different real-world datasets. We develop a distributed FCMD-MD, a fuzzy clustering algorithm for mixed-mode data in Apache SPARK. The experimental results show that the algorithm is scalable, performs well in a distributed environment, and clusters enormous heterogeneous data with high accuracy. We also compared the performance of distributed FCMD-MD and the distributed k-medoid algorithm.
An intervention to improve safe firearm storage for adolescents presenting with suicide ideation or attempt in a pediatric emergency department
Authors: Cleary Ashley , Kaczor Frannie , Finnegan Maisie , Schimek John , Egen-Schimek Abby , O’Donnell Erin , Melzer-Lange Marlene
Published: December 2022

Background

Firearm injuries are the second leading cause of death in American youth aged 15 to 24, and over half of these deaths are suicides. Self-harm deaths in Wisconsin among adolescents have increased by 34% since 2006. Each year, our pediatric emergency department (ED) staff care for over 1100 children and adolescents who present with suicidal ideation or self-harming behaviors. We implemented an ED-based program aimed at improving the education given to families on reducing self-directed violence and providing firearm storage devices to families with the goal of reducing access to lethal means.

Program description

Our program takes place in the pediatric ED of an academic children’s hospital and seeks to assist families of all patients who present with suicidal ideation or suicide attempt (SI/SA). In collaboration with our social workers, we reviewed their processes for interviewing and counseling families of patients who present with SI/SA. Social workers previously used a hospital-wide patient and family education sheet for safety planning that included information about safely storing medications and community mental health services. We teamed with our hospital’s health literacy and education committees and revised the teaching sheet to include more in-depth information about safe firearm storage. For families who were interested, we developed a process to provide up to two firearm lockboxes equipped with a combination lock. Working with risk management, the parent injury prevention product liability form was updated to include firearm lockboxes.

Conclusion

We implemented a safe firearm storage program including development of a patient and family education sheet and provision of firearm lockboxes to families. Next steps under consideration include providing lockboxes for safe medication storage and establishing a follow-up system to assess proper use of firearm lockboxes and family and social worker satisfaction.
Residential electricity current and appliance dataset for AC-event detection from Indian dwellings
Authors: Tejaswini Dharani , Ramapragada Pavan , Gundepudi Sraavani , Kandukuri Prabhakar Rao , Garg Vishal , Mathur Jyotirmay , Gupta Rajat
Published: December 2022

Air Conditioners (ACs) have become a major contributor to residential electricity consumption in India. Non-intrusive Load Monitoring (NILM) can be used to understand residential AC use and its contribution to electricity consumption. NILM techniques use ground truth information along with meter readings to train disaggregation algorithms. There are datasets available for disaggregation, but no dataset is available for a hot tropical country like India especially for AC event detection. Our dataset’s primary objective is to help train NILM algorithms for AC event detection and compressor operations. The dataset comprises of home-level electrical current consumption and manually tagged AC ground truth (ON/OFF status) data at 1-min interval, indoor environment temperature and relative humidity readings at 5-min interval and dwelling, AC and household characteristics. The data was collected from 11 homes located in a composite climate zone-Hyderabad, India for 19 summer days (May) 2019. The dataset consists of 1.6 million data points and 450 AC cycles with each cycle having a runtime of more than 60 min (> 2000 compressor ON/OF cycles). Public availability of such a dataset will allow researchers to develop, train and test NILM algorithms that recognize AC and identify compressor operations.
SGLSim: tool for smart glazing energy performance analysis
Authors: Raihan Md Anam , Chattopadhyay Kuntal , Bhatia Aviruch , Garg Vishal , Hussain Aftab M.
Published: December 2022

A tool Smart Glazing Simulator (SGLSim), has been developed to perform parametric simulation analysis of different window systems with several window-to-wall ratios and orientations to compute and compare the annual energy performance. The net annual energy performance of the building is based on the electricity consumption in heating, cooling, interior lighting, and appliances, along with the electricity generation by the photovoltaic (PV) glazing, which is used to evaluate the energy performance of smart glazing. Performing parametric energy simulations and calculating the net annual electricity consumption of different combinations requires building modeling and energy simulation expertise. A web-based parametric tool can assist the user in carrying out the desired studies without requiring extensive technical knowledge. A case study is prepared for India’s warm and humid climatic zone. This study examines the benefits of double pane semi-transparent photovoltaics (STPV) glazing, STPV glazing with dynamic internal blind, and electrochromic (EC) glazing over other traditional glazing systems. The study shows that the optimal net annual electricity consumption in the case of STPV windows is 10–12% less than the optimal value obtained in a simple glazing case. Additionally, the result suggested that glare-controlled interior blinds in the STPV window further reduce the net annual electricity consumption by up to 15% compared to conventional glazing. Similarly, installing the EC glazing reduces the yearly electricity consumption by up to 5% compared to standard glazing.
An agent-based modelling framework for the simulation of large-scale consumer participation in electricity market ecosystems
Authors: Fatras Nicolas , Ma Zheng , Jørgensen Bo Nørregaard
Published: December 2022

The role of consumers as price-sensitive participants in electricity markets is considered essential to ensure efficient and secure operations of electricity systems. Yet the uncertain or unknown consequences of active market participation remain a large barrier for active consumer-side market participation. Simulations are a powerful tool to reduce this uncertainty by giving consumers an insight on the potential benefits and costs of market participation. However, the simulation setup must be adapted to each market context and each consumer market participation strategy. To simplify the simulation development process and improve the comparability of simulation results, this paper proposes a modular yet systematic electricity market modelling framework. The framework applies object-oriented programming concepts for business ecosystem modelling presented in previous works to develop an agent-based model of a consumer-centric electricity market ecosystem. The market ecosystem is represented by a multitude of interacting submarkets with their own logic. Within submarkets, context-independent and context-dependent elements are distinguished to provide model abstraction which can be adapted to different contexts. This framework is illustrated by applying it to three different submarkets in the Western Danish electricity market context: the Nordpool day-ahead market, the Nordpool intraday market, and the Frequency Containment Reserve market. The submarket role abstractions allow to benefit from the commonalities between the analysed submarkets during model implementation, while the role parametrisations allow to quickly adapt the roles to each market context. The implementation of the modelling framework in the Nordic context highlights the benefits of a modular approach in a liberalised and unbundled market context.
A comparison study of co-simulation frameworks for multi-energy systems: the scalability problem
Authors: Barbierato Luca , Rando Mazzarino Pietro , Montarolo Marco , Macii Alberto , Patti Edoardo , Bottaccioli Lorenzo
Published: December 2022

The transition to a low-carbon society will completely change the structure of energy systems from a standalone hierarchical centralised vision to cooperative and distributed Multi-Energy Systems. The analysis of these complex systems requires the collaboration of researchers from different disciplines in the energy, ICT, social, economic, and political sectors. Combining such disparate disciplines into a single tool for modeling and analyzing such a complex environment as a Multi-Energy System requires tremendous effort. Researchers have overcome this effort by using co-simulation techniques that give the possibility of integrating existing domain-specific simulators in a single environment. Co-simulation frameworks, such as Mosaik and HELICS, have been developed to ease such integration. In this context, an additional challenge is the different temporal and spatial scales that are involved in the real world and that must be addressed during co-simulation. In particular, the huge number of heterogeneous actors populating the system makes it difficult to represent the system as a whole. In this paper, we propose a comparison of the scalability performance of two major co-simulation frameworks (i.e. HELICS and Mosaik) and a particular implementation of a well-known multi-agent systems library (i.e. AIOMAS). After describing a generic co-simulation framework infrastructure and its related challenges in managing a distributed co-simulation environment, the three selected frameworks are introduced and compared with each other to highlight their principal structure. Then, the scalability problem of co-simulation frameworks is introduced presenting four benchmark configurations to test their ability to scale in terms of a number of running instances. To carry out this comparison, a simplified multi-model energy scenario was used as a common testing environment. This work helps to understand which of the three frameworks and four configurations to select depending on the scenario to analyse. Experimental results show that a Multi-processing configuration of HELICS reaches the best performance in terms of KPIs defined to assess the scalability among the co-simulation frameworks.
Recursive training based physics-inspired neural network for electric water heater modeling
Authors: Pandiyan Surya Venkatesh , Rajasekharan Jayaprakash
Published: December 2022

Aggregating flexibility from residential electric water heaters (EWHs) is fast gaining commercial interest. Flexibility modeling of an EWH involves highly precise and quick simulation of EWH water temperature using the EWH thermal dynamics model for various flexibility control actions. Since EWH tank water temperature data is usually unavailable or costly to obtain, developing an accurate and computationally inexpensive EWH thermal dynamics model with limited sensor data is essential for devising advanced control strategies for EWH flexibility aggregation. In this paper, we present a novel recursive training-based unsupervised physics-informed neural network (PINN) model for predicting tank water temperature which requires only historical EWH power consumption data to train the model. PINN models enable the integration of domain knowledge from traditional physical processes and methods into neural network (NN) models. Single-zone thermal grey-box differential equation model (DEM) is used as the basis to develop and demonstrate proof-of-concept of the proposed approach. Physics from the single-zone model is encoded into the PINN loss function to incorporate domain knowledge and the PINN architecture is structured to mimic the single-zone DEM. The recursive training approach enables the use of previous-step water temperature as an input to the simulation model. Two separate models for EWH ON- and OFF-states are developed and trained with real-world EWH power consumption data. Water temperature prediction results indicate that the proposed approach has similar performance as the traditional single-zone DEM model, thereby demonstrating the ability of the proposed model to learn the underlying physics behind the single-zone model without water temperature data. The proposed model has high accuracy and performs well outside the control set point temperatures indicating its suitability for simulating load shifting and other DR events. Additionally, EWH simulation results for two different scenarios with different water demand compositions are presented to study the effects of propagation errors on temperature prediction. The proposed approach paves the way for developing advanced EWH flexibility modeling tools for the aggregator to precisely control a large portfolio of EWHs considering user comfort and rebound effects.
Impact of COVID-19 on energy consumption in a residential complex in Hyderabad, India
Authors: Chattopadhyay Kuntal , Garg Vishal , Paruchuri Praveen , Mathur Jyotirmay , Valluri Srinivas
Published: December 2022

When the Indian government declared the first lockdown on 25 March 2020 to control the increasing number of COVID-19 cases, people were forced to stay and work from home. The aim of this study is to quantify the impact of stay-at-home orders on residential Air Conditioning (AC) energy and household electricity consumption (excluding AC energy). This was done using monitored data from 380 homes in a group of five buildings in Hyderabad, India. We gathered AC energy and household electricity consumption data at a 30-min interval for each home individually in April 2019 and April 2020. Descriptive and inferential statistical analysis was done on this data. To offset the difference in temperatures for the month of April in 2019 and 2020, only those weekdays were selected where the average temperature in 2019 was same as the average temperature in 2020. The study establishes that the average number of hours the AC was used per day in each home increased in the range 4.90–7.45% depending on the temperature for the year 2020. Correspondingly, the overall AC consumption increased in the range 3.60–4.5%, however the daytime (8:00 AM to 8:00 PM) AC energy consumption increased in the range 22–26% and nighttime (8:00 PM to 8:00 AM) AC energy consumption decreased by 5–7% in the year 2020. The study showed a rise in household electricity consumption of about 15% for the entire day in the year 2020. The household electricity consumption increased during daytime by 22- 27.50% and 1.90- 6.6% during the nighttime. It was observed that the morning household electricity peak demand shifted from 7:00 AM in 2019 to 9:00 AM in 2020. Conversely, the evening peak demand shifted from 9:00 PM in 2019 to 7:00 PM in 2020. An additional peak was observed during afternoon hours in the lockdown.
Revealing interactions between HVDC cross-area flows and frequency stability with explainable AI
Authors: Pütz Sebastian , Schäfer Benjamin , Witthaut Dirk , Kruse Johannes
Published: December 2022

The transition to renewable energy sources challenges the operation and stability of the electric power system. Wind and solar power generation are volatile and uncertain, and energy sources may be located far away from the centers of the load. High Voltage Direct Current (HVDC) lines enable long-distance power transmission at low losses, both within and between different synchronous power grids. HVDC interconnectors between different synchronous areas can be used to balance volatile generation by leveraging their fast control behavior, but rapid switching may also disturb the power balance. In this article, we analyze the interaction of HVDC interconnector operation and load-frequency control in different European power grids from operational data. We use explainable machine learning to disentangle the various influences affecting the two systems, identify the key influences, and quantify the interrelations in a consistent way. Our results reveal two different types of interaction: Market-based HVDC flows introduce deterministic frequency deviations and thus increase control needs. Control-based HVDC flows mitigate frequency deviations on one side as desired but generally disturb frequency on the other side. The analysis further provides quantitative estimates for the control laws and operation strategies of individual HVDC links, for which there is little public information. Furthermore, we quantify the importance of HVDC links for the frequency dynamics, which is particularly large in the British grid.
An adapter-based architecture for evaluating candidate solutions in energy system scheduling
Authors: Chlosta Malte , Liu Jianlei , Poppenborg Rafael , Lutz Richard , Förderer Kevin , Schlachter Thorsten , Hagenmeyer Veit
Published: December 2022

Increasing shares of volatile generation and non-steerable demand raise the need for automated control of the Energy Systems (ESs). Various solutions for management and schedule-based control of energy facilities exist today. However, the amount and diversity of applications lead to a multitude of different automated energy management solutions. Different optimization algorithms have proven more or less effective for energy management. The multitude of optimization algorithms and energy management solutions require flexible, modular, and scalable integrations. We present a novel Optimization Service (OS) for easily integrating optimization algorithms while evaluating candidate solutions in the context of ESs applications. We propose an adapter-based architecture using metadata and domain knowledge to bridge between clients, e.g. smart grid applications and optimization algorithms. The architecture interfaces different clients with optimizers in a flexible and modular way. The clients provide metadata-based descriptions of optimization jobs translated by OS. OS then interacts with optimizers and evaluates candidate solutions. A consistent definition of interfaces for clients and optimization algorithms facilitates the modular evaluation of candidate solutions. OS’s separation of client and optimization algorithms increases scalability by managing computational resources independently. We evaluate the presented architecture for scheduling a so-called Energy Hub (EH) as a test case describing a simulation scenario of a renewable EH embedded in grid scenarios from an industrial area in Karlsruhe, Germany. OS utilizes an Evolutionary Algorithm (EA) to optimize schedules for cost and strain on the electrical grid. The use case exemplifies OS’s advantages in a proof-of-concept evaluation.
Satranidazole-loaded chitosan/locust bean gum/xanthan gum polysaccharide composite multiunit pellets for colon targeting: in vitro–in vivo investigation
Authors: Mazumder Rana , Mahanti Beduin , Majumdar Subhabrota , Pal Rabindranath , Pahari Nilanjan
Published: December 2022

Background

The colon has a significant site to deliver numerous active materials for colonic diseases. Highly biodegradable polymers hold significant promise among the several techniques available to deliver the drug to the colon. This research aimed to prepare chitosan, locust bean gum and xanthan gum polysaccharide composite satranidazole multiunit pellets for colonic release and assesses the bioavailability with pharmacokinetic parameters after administration of satranidazole raw drug compared to multiunit pellets. Satranidazole multiple unit pellets were prepared based on chitosan, locust bean gum and xanthan gum, which were inexpensive and harmless. The bioavailability study was done by crossover design in which satranidazole raw drug and test formulation was administered to six healthy white albino rats.

Results

The pharmacokinetic analyses were estimated using the deconvolution of the plasma profile. Compared to the satranidazole drug used as a reference, for the pellets, the maximum plasma concentration was lower (35.02 ± 3.91 ng/ml vs. 51.07 ± 1.21 ng/ml for the satranidazole drug), and the time to attain maximum concentration was 2.50 ± 0.55 h for both drugs and test formulation. Colonic drug content was significantly higher than that of free administered drug.

Conclusion

The results indicate the acquired pharmacokinetic studies and colonic analysis established the reliability of the pharmaceutical technique and the ability to release satranidazole at the colonic site.

Graphical Abstract
NOHA: A Promising Biomarker for Determining Estrogen Receptor Status Among Patients With Breast Cancer in Resource-Constrained Settings
Authors: Serventi Furaha , Musyoka Augustine , Saunders Jamie , Mremi Alex , Mmbaga Blandina Theophil , Patrick Elizabeth , Mwakyembe Theresia , Jones Michael , Lucas F. Lee. , Miesfeldt Susan , Mohan Srinidi
Published: December 2022

PURPOSE

Challenges to breast cancer control in low-and middle-income countries exist because of constrained access to care, including pathology services. Immunohistochemistry (IHC)–based estrogen receptor (ER) analysis is limited-nonexistent because of few and inadequately staffed and equipped pathology laboratories. We have identified Nw-hydroxy-L-Arginine (NOHA) as a blood-based biomarker to distinguish ER status in US patients with breast cancer. Here, we examine NOHA's clinical utility as an ER IHC alternative in Tanzanian patients.

MATERIALS AND METHODS

Following informed consent, 70 newly diagnosed, known or suspected patients with breast cancer were enrolled at Kilimanjaro Christian Medical Center; basic, deidentified clinical and sociodemographic data were collected. For each, a needle prick amount of blood was collected on a Noviplex plasma card and stored at −80°C. Plasma cards and unstained tumor pathology slides were shipped regularly to US laboratories for NOHA, histologic and IHC analysis. NOHA and IHC assay operators were blinded to each other's result and patient clinical status. Paired NOHA and IHC results were compared.

RESULTS

Slides from 43 participants were available for pathological analysis in the United States. Of those with confirmed malignancy (n = 39), 44%, 51%, 5% were ER-positive, ER-negative, and ER inconclusive, respectively. NOHA levels were available among 33 of 43 of those with pathological data and showed distinct threshold levels correlating 100% to tumor ER IHC and disease categorization where a level below 4 nM, from 4 to 8 nM, and above 8 nM signified ER-negative, ER-positive, and no cancer, respectively.

CONCLUSION

The results are consistent with findings from US patients and suggest NOHA's clinical utility as an accessible IHC replacement in determining ER status among low-and middle-income country patients with breast cancer, promising to extend access to cost-efficient, available hormonal agents and improve outcomes.
Inflecting the French
Authors: Grand Pre Tyler
Published: December 2022

Aimé Césaire’s long poem Cahier d’un retour au pays natal is the most expressive example of his ambitious effort “infléchir le français” (“to inflect the French”), as he famously put it in an interview, “pour exprimer, dison: ce moi, ce moi-nègre, ce moi-créole, ce moi-martiniquais, ce moi-antillais” (translated by Brent Edwards, this reads: “in order to express, let’s say: “this I, this nègre-I, this creole-I, this Martinican-I, this Antillean-I”). Many scholars have read the Cahier’s inflection of French language and discourse in terms of its elaborate use of Latinate neologisms, archaic terminology, and typographic wordplay; however, less attention has been given to the implications this poem’s tortuous shifts in address have as a radical critique of the formal desires and ontological exclusions of Enlightenment universalism. Through the way Césaire rearticulates the basic components of grammatical address in a vexed, lyric encounter with the colonial reality of Martinique, he gradually recalibrates the relationship between the poem’s speaker and the African-diasporic community of and beyond Martinique as that between a kind of intersubjective voice of négritude and a globally discursive locus of anticolonialism—what he later calls the “rendez-vous de la conquête” (“convocation of conquest”).
The legality of public pension reforms in times of financial crisis
Authors: Δηλιάγκα Δάφνη
Published: December 2022

Η διδακτορική διατριβή αναλύει και ερευνά τη συνταγματικότητα των περικοπών των δημοσίων συντάξεων σε περιόδους οικονομικής κρίσης. Ο κύριος σκοπός της διατριβής είναι να προτείνει ένα νομικό πλαίσιο, το οποίο αναλύει, εάν και υπό ποιες συνθήκες το δημόσιο συμφέρον μπορεί να δικαιολογήσει περικοπή των δημοσίων συντάξεων και ποια είναι τα κατοχυρωμένα δικαιώματα των συνταξιούχων.