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Article ; Online: Packing up the genome

Bálint Kiss / Miklós Kellermayer

eLife, Vol

2023 Volume 12

Abstract: Nucleotide and force-dependent mechanisms control how the viral genome of lambda bacteriophage is inserted into capsids. ...

Abstract	Nucleotide and force-dependent mechanisms control how the viral genome of lambda bacteriophage is inserted into capsids.
Keywords	genome packaging ; bacteriophage ; structural biology ; viruses ; packaging motor ; Medicine ; R ; Science ; Q ; Biology (General) ; QH301-705.5
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	eLife Sciences Publications Ltd
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Packing up the genome.

Kiss, Bálint / Kellermayer, Miklós

eLife

2023 Volume 12

Abstract: Nucleotide and force-dependent mechanisms control how the viral genome of lambda bacteriophage is inserted into capsids. ...

Abstract	Nucleotide and force-dependent mechanisms control how the viral genome of lambda bacteriophage is inserted into capsids.
MeSH term(s)	DNA, Viral/genetics ; Bacteriophage lambda/genetics ; Capsid ; Genome, Viral ; Nucleotides ; Virus Assembly/genetics
Chemical Substances	DNA, Viral ; Nucleotides
Language	English
Publishing date	2023-12-14
Publishing country	England
Document type	Editorial
ZDB-ID	2687154-3
ISSN	2050-084X ; 2050-084X
ISSN (online)	2050-084X
ISSN	2050-084X
DOI	10.7554/eLife.94128
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: 4–10 éves magyar gyermekek tápanyagbeviteli és tápláltsági állapotának felmérése.

Sárga, Diána / Biró, Lajos / Kiss-Tóth, Bernadett / Veresné Bálint, Márta

Orvosi hetilap

2023 Volume 164, Issue 14, Page(s) 533–540

Abstract: Introduction and objective: The growing trend of childhood obesity is a major public health issue. Collaborations between medical and healthcare professionals, preventive and health preservative programs, dietary habit and nutrient intake studies are ... ...

Title translation	Nutrient intake and nutritional status of 4-10-year-old Hungarian children.
Abstract	Introduction and objective: The growing trend of childhood obesity is a major public health issue. Collaborations between medical and healthcare professionals, preventive and health preservative programs, dietary habit and nutrient intake studies are indispensable. Method: A representative study has been performed among 4-10-year-old Hungarian children by gender, age, size of settlement and region. The study included 733 assessable questionnaires and 666 dietary records. Data on children's eating habits were collected by using the internationally recommended three-day dietary record method. Body weight and height measurements were taken for each child to determine nutritional status. Data were analyzed with statistical methods. Results: The rate of overweight and obesity is 23%. Energy intake differs significantly between body mass index groups. The children's fat intake is excessive (34.2 energy%), the saturated fatty acid intake exceeds the recommended 10 energy%, omega fatty acid ratio is disadvantageous and the children's cholesterol intake is high. The average energy from carbohydrates is below the recommended 57 energy%, from added sugar it is 11%, which affects 52% of the children. Their low fibre intake (19.4 g/day) is due to low fruit, vegetable (263 g/day) and whole grain consumption. Of the micronutrients, sodium intake is 3-4 times higher than the recommended. In 35% of the children, the calcium intake is below the critical threshold, due to unfavourable milk and milk product consumption (290 g/day). Vitamin D intake was low in 98-100% of the children. Conclusion: Compared to the results of other European and national studies performed among children, adolescent and adults, the nutritional status and nutrient intake of our sample is unfavourable. Comprehensive intervention, education of the children with the involvement of their parents is essential to reduce obesity. Orv Hetil. 2023; 164(14): 533-540.
MeSH term(s)	Adult ; Adolescent ; Child ; Humans ; Child, Preschool ; Nutritional Status ; Hungary ; Pediatric Obesity/epidemiology ; Pediatric Obesity/prevention & control ; Energy Intake ; Eating ; Child Nutritional Physiological Phenomena ; Diet
Language	Hungarian
Publishing date	2023-04-09
Publishing country	Hungary
Document type	English Abstract ; Journal Article
ZDB-ID	123879-6
ISSN	1788-6120 ; 0030-6002
ISSN (online)	1788-6120
ISSN	0030-6002
DOI	10.1556/650.2023.32713
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Article ; Online: Selective and optimal dynamic pricing strategy for residential electricity consumers based on genetic algorithms

Salma Taik / Bálint Kiss

Heliyon, Vol 8, Iss 11, Pp e11696- (2022)

2022

Abstract: The continuous increase in residential population implies an increase in electricity demand. The demand prediction performed by the utility company (UC) to schedule and plan the next energy purchase from the market may not be efficient since the actual ... ...

Abstract	The continuous increase in residential population implies an increase in electricity demand. The demand prediction performed by the utility company (UC) to schedule and plan the next energy purchase from the market may not be efficient since the actual demand consistently exceeds the supply. To use the energy production infrastructure efficiently and decrease the grid system's overload, the UC seeks to match the demand with the supply. Dynamic pricing is a simple yet effective way to influence consumption as price-sensitive consumers may reschedule the operation of some of the appliances. This paper presents a novel, consumption data-driven, selective and dynamic Time-of-Use (ToU) electricity pricing strategy applicable by the UC for residential electricity consumers. The method consists of clustering real consumption data using the k-means clustering technique and heuristically categorizing clusters based only on their consumption data to simplify the design of the ToU tariffs and limit the number of different tariffs in the same population. The method includes a heuristic determination of the time period for the ToU tariff changes for each category. The ToU tariff parameters are determined by minimizing a single cost function using genetic algorithms and considering all consumer clusters such that the consumer behavior model is based on price elasticity. The optimal ToU tariffs result in decreasing the demand in power peaks by targeting the overconsumer categories in the latter. Implementing the ToU tariff results in a profit margin distributed among the UC and the consumer. Moreover, the optimal prices guarantee positive gains for both of them with the presence of a wide range of parameter uncertainties. The proposed pricing strategy necessitates the presence of consumption data only, which implies the conservation of the consumers' privacy. Real consumption data obtained for two towns in Hungary over three years is used to show the efficiency of the proposed pricing strategy.
Keywords	Consumer behavior model ; Consumers categorization ; Consumption data clustering ; Demand-side management program ; Parameter uncertainty ; Price sensitivity ; Science (General) ; Q1-390 ; Social sciences (General) ; H1-99
Subject code	330 ; 690
Language	English
Publishing date	2022-11-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Selective and optimal dynamic pricing strategy for residential electricity consumers based on genetic algorithms.

Taik, Salma / Kiss, Bálint

Heliyon

2022 Volume 8, Issue 11, Page(s) e11696

Abstract	The continuous increase in residential population implies an increase in electricity demand. The demand prediction performed by the utility company (UC) to schedule and plan the next energy purchase from the market may not be efficient since the actual demand consistently exceeds the supply. To use the energy production infrastructure efficiently and decrease the grid system's overload, the UC seeks to match the demand with the supply. Dynamic pricing is a simple yet effective way to influence consumption as price-sensitive consumers may reschedule the operation of some of the appliances. This paper presents a novel, consumption data-driven, selective and dynamic Time-of-Use (ToU) electricity pricing strategy applicable by the UC for residential electricity consumers. The method consists of clustering real consumption data using the k-means clustering technique and heuristically categorizing clusters based only on their consumption data to simplify the design of the ToU tariffs and limit the number of different tariffs in the same population. The method includes a heuristic determination of the time period for the ToU tariff changes for each category. The ToU tariff parameters are determined by minimizing a single cost function using genetic algorithms and considering all consumer clusters such that the consumer behavior model is based on price elasticity. The optimal ToU tariffs result in decreasing the demand in power peaks by targeting the overconsumer categories in the latter. Implementing the ToU tariff results in a profit margin distributed among the UC and the consumer. Moreover, the optimal prices guarantee positive gains for both of them with the presence of a wide range of parameter uncertainties. The proposed pricing strategy necessitates the presence of consumption data only, which implies the conservation of the consumers' privacy. Real consumption data obtained for two towns in Hungary over three years is used to show the efficiency of the proposed pricing strategy.
Language	English
Publishing date	2022-11-16
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2022.e11696
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Article ; Online: Selective and optimal dynamic pricing strategy for residential electricity consumers based on genetic algorithms

Taik, Salma / Kiss, Bálint

Heliyon. 2022 Nov., v. 8, no. 11 p.e11696-

2022

Abstract	The continuous increase in residential population implies an increase in electricity demand. The demand prediction performed by the utility company (UC) to schedule and plan the next energy purchase from the market may not be efficient since the actual demand consistently exceeds the supply. To use the energy production infrastructure efficiently and decrease the grid system's overload, the UC seeks to match the demand with the supply. Dynamic pricing is a simple yet effective way to influence consumption as price-sensitive consumers may reschedule the operation of some of the appliances. This paper presents a novel, consumption data-driven, selective and dynamic Time-of-Use (ToU) electricity pricing strategy applicable by the UC for residential electricity consumers. The method consists of clustering real consumption data using the k-means clustering technique and heuristically categorizing clusters based only on their consumption data to simplify the design of the ToU tariffs and limit the number of different tariffs in the same population. The method includes a heuristic determination of the time period for the ToU tariff changes for each category. The ToU tariff parameters are determined by minimizing a single cost function using genetic algorithms and considering all consumer clusters such that the consumer behavior model is based on price elasticity. The optimal ToU tariffs result in decreasing the demand in power peaks by targeting the overconsumer categories in the latter. Implementing the ToU tariff results in a profit margin distributed among the UC and the consumer. Moreover, the optimal prices guarantee positive gains for both of them with the presence of a wide range of parameter uncertainties. The proposed pricing strategy necessitates the presence of consumption data only, which implies the conservation of the consumers' privacy. Real consumption data obtained for two towns in Hungary over three years is used to show the efficiency of the proposed pricing strategy.
Keywords	consumer behavior ; demand elasticities ; electricity ; energy ; markets ; models ; prediction ; profits and margins ; tariffs ; utilities ; Hungary ; Consumer behavior model ; Consumers categorization ; Consumption data clustering ; Demand-side management program ; Parameter uncertainty ; Price sensitivity ; Time-of-Use electricity tariffs
Language	English
Dates of publication	2022-11
Publishing place	Elsevier Ltd
Document type	Article ; Online
Note	Use and reproduction
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2022.e11696
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Simulation of Intelligence Evolution in Object-Oriented Systems

Bálint Fazekas / Attila Kiss

Vietnam Journal of Computer Science, Vol 7, Iss 3, Pp 209-

2020 Volume 229

Abstract: In classical artificial intelligence and machine learning fields, the aim is to teach a certain program to find the most convenient and efficient way of solving a particular problem. However, these approaches are not suitable for simulating the evolution ...

Abstract	In classical artificial intelligence and machine learning fields, the aim is to teach a certain program to find the most convenient and efficient way of solving a particular problem. However, these approaches are not suitable for simulating the evolution of human intelligence, since intelligence is a dynamically changing, volatile behavior, which greatly depends on the environment an agent is exposed to. In this paper, we present several models of what should be considered, when trying to simulate the evolution of intelligence of agents within a given environment. We explain several types of entropies, and introduce a dominant function model. By unifying these models, we explain how and why our ideas can be formally detailed and implemented using object-oriented technologies. The difference between our approach and that described in other papers also — approaching evolution from the point of view of entropies — is that our approach focuses on a general system, modern implementation solutions, and extended models for each component in the system.
Keywords	simulation ; intelligence evolution ; object-oriented ; java ; gis ; Information technology ; T58.5-58.64 ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	401
Language	English
Publishing date	2020-08-01T00:00:00Z
Publisher	World Scientific Publishing
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Compensatory muscle activation and spinal curve changes in response to fatigue among adolescent male athletes

Anna Gál-Pottyondy / Bálint Petró / Mária Takács / János Négyesi / Ryoichi Nagatomi / Rita M Kiss

BMC Sports Science, Medicine and Rehabilitation, Vol 15, Iss 1, Pp 1-

2023 Volume 10

Abstract: Abstract Background The prone plank test has been often used to assess the strength and endurance of trunk muscles. We aimed to develop a new measurement protocol to objectively monitor the changes in spinal curves and muscle activity simultaneously. ... ...

Abstract	Abstract Background The prone plank test has been often used to assess the strength and endurance of trunk muscles. We aimed to develop a new measurement protocol to objectively monitor the changes in spinal curves and muscle activity simultaneously. Methods Eleven adolescent male basketball athletes (13–17 years) performed a one-minute plank test. Spinal curvatures (thoracic kyphosis (TK) and lumbar lordosis (LL)) were determined at each time point by optical tracking of markers placed on the spinous processes of 10 vertebrae. Eleven muscles were measured by surface electromyography to determine muscle fatigue via changes in median frequency. Results TK significantly increased (p = 0.003) from the first to the last 10 s of the plank test; changes in LL were mixed within the group. Only the rectus abdominis showed consistent and significant fatigue (p < 0.001). The increased spinal curves significantly correlated with the fatigue of biceps femoris (TK: r = -0.75, p = 0.012; LL: r = -0.71, p = 0.019) indicating a compensatory muscle activation and spinal curve changes in response to fatigue. Conclusion Our protocol may support future researches that aim to objectively evaluate the prone plank test and which posture-related muscles need strengthening for the individual.
Keywords	Basketball ; Electromyography ; Optical tracking ; Prone plank test ; Spine ; Sports medicine ; RC1200-1245
Subject code	796
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Water level prediction using long short-term memory neural network model for a lowland river

Zsolt Vizi / Bálint Batki / Luca Rátki / Szabolcs Szalánczi / István Fehérváry / Péter Kozák / Tímea Kiss

Environmental Sciences Europe, Vol 35, Iss 1, Pp 1-

a case study on the Tisza River, Central Europe

2023 Volume 18

Abstract: Abstract Background Precisely predicting the water levels of rivers is critical for planning and supporting flood hazard and risk assessments and maintaining navigation, irrigation, and water withdrawal for urban areas and industry. In Hungary, the water ...

Abstract	Abstract Background Precisely predicting the water levels of rivers is critical for planning and supporting flood hazard and risk assessments and maintaining navigation, irrigation, and water withdrawal for urban areas and industry. In Hungary, the water level of rivers has been recorded since the early nineteenth century, and various water level prediction methods were developed. The Discrete Linear Cascade Model (DLCM) has been used since 1980s. However, its performance is not always reliable under the current climate-driven hydrological changes. Therefore, we aimed to test machine learning algorithms to make 7-day ahead forecasts, choose the best-performing model, and compare it with the actual DLCM. Results According to the results, the Long Short-Term Memory (LSTM) model provided the best results in all time horizons, giving more precise predictions than the Baseline model, the Linear or Multilayer Perceptron Model. Despite underestimating water levels, the validation of the LSTM model revealed that 68.5‒76.1% of predictions fall within the required precision intervals. Predictions were relatively accurate for low (≤ 239 cm) and flood stages (≥ 650 cm), but became less reliable for medium stages (240–649 cm). Conclusions The LSTM model provided better results in all hydrological situations than the DLCM. Though, LSTM is not a novel concept, its encoder–decoder architecture is the best option for solving multi-horizon forecasting problems (or “Many-to-Many” problems), and it can be trained effectively on vast volumes of data. Thus, we recommend testing the LSTM model in similar hydrological conditions (e.g., lowland, medium-sized river with low slope and mobile channel) to get reliable water level forecasts under the rapidly changing climate and various human impacts. Graphical Abstract
Keywords	Discrete Linear Cascade Model ; Long short-term memory ; Multilayer Perceptron Model ; Linear Model ; Underestimation ; Environmental sciences ; GE1-350 ; Environmental law ; K3581-3598
Subject code	550
Language	English
Publishing date	2023-11-01T00:00:00Z
Publisher	SpringerOpen
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Compensatory muscle activation and spinal curve changes in response to fatigue among adolescent male athletes.

Gál-Pottyondy, Anna / Petró, Bálint / Takács, Mária / Négyesi, János / Nagatomi, Ryoichi / Kiss, Rita M

BMC sports science, medicine & rehabilitation

2023 Volume 15, Issue 1, Page(s) 57

Abstract: Background: The prone plank test has been often used to assess the strength and endurance of trunk muscles. We aimed to develop a new measurement protocol to objectively monitor the changes in spinal curves and muscle activity simultaneously.: Methods! ...

Abstract	Background: The prone plank test has been often used to assess the strength and endurance of trunk muscles. We aimed to develop a new measurement protocol to objectively monitor the changes in spinal curves and muscle activity simultaneously. Methods: Eleven adolescent male basketball athletes (13-17 years) performed a one-minute plank test. Spinal curvatures (thoracic kyphosis (TK) and lumbar lordosis (LL)) were determined at each time point by optical tracking of markers placed on the spinous processes of 10 vertebrae. Eleven muscles were measured by surface electromyography to determine muscle fatigue via changes in median frequency. Results: TK significantly increased (p = 0.003) from the first to the last 10 s of the plank test; changes in LL were mixed within the group. Only the rectus abdominis showed consistent and significant fatigue (p < 0.001). The increased spinal curves significantly correlated with the fatigue of biceps femoris (TK: r = -0.75, p = 0.012; LL: r = -0.71, p = 0.019) indicating a compensatory muscle activation and spinal curve changes in response to fatigue. Conclusion: Our protocol may support future researches that aim to objectively evaluate the prone plank test and which posture-related muscles need strengthening for the individual.
Language	English
Publishing date	2023-04-13
Publishing country	England
Document type	Journal Article
ZDB-ID	2719537-5
ISSN	2052-1847
ISSN	2052-1847
DOI	10.1186/s13102-023-00668-6
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