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Article ; Online: Sustainable Development of Business Economy Based on Big Data Algorithm under the Background of Low-Carbon Economy

Xuefeng Liu / Li Ma

Sustainability, Vol 15, Iss 5840, p

2023 Volume 5840

Abstract: After the low-carbon economy (LCE) was proposed, countries all over the world examined their national economic structures and found the necessity for developing a LCE. Therefore, it is necessary to vigorously develop low-carbon technologies and improve ... ...

Abstract	After the low-carbon economy (LCE) was proposed, countries all over the world examined their national economic structures and found the necessity for developing a LCE. Therefore, it is necessary to vigorously develop low-carbon technologies and improve technological and policy innovation capabilities. From the perspective of promoting the coordinated development of the low-carbon economic system and regional sustainable development, this paper conducted an in-depth analysis of the coordinated development of the low-carbon economic system and regional environmental issues by using the relevant theories of sustainable development, low-carbon economics, and environmental economics. The index system of the low-carbon economic system and regional sustainable development was constructed, and the coupling degree model and regional coupling coordination degree model suitable for the development of the low-carbon economic system and regional sustainable development were established. On the basis of analyzing the status quo of a LCE and the environment in a coastal area, it was finally concluded that in the next five years, the value of the coupling coordination degree of the LCE and its sustainable system development would continue to approach 1 and grow steadily.
Keywords	low-carbon economy ; big data algorithm ; business economy ; sustainable development ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	333
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Strategies for Environmental Protection and Optimization of Ecological Business Economic Growth from the Perspective of Sustainable Development

Li Ma / Xuefeng Liu

Sustainability, Vol 15, Iss 2758, p

2023 Volume 2758

Abstract: The concept of ecological commercial economy refers to the use of ecological economics principles and system engineering methods to change production and consumption patterns within the scope of the carrying capacity of the ecosystem in order to tap into ...

Abstract	The concept of ecological commercial economy refers to the use of ecological economics principles and system engineering methods to change production and consumption patterns within the scope of the carrying capacity of the ecosystem in order to tap into all of the available resource potential. It develops some economically developed and ecologically efficient industries and builds a culture with reasonable systems, a harmonious society, and a healthy ecological environment. This paper aims to use deep learning algorithms to study environmental protection and the optimization of ecological business economic growth from the perspective of sustainable development. In this regard, this paper proposes a theoretical model of environmental regulation, which aids in the study of the sustainable development of the ecological economy. Through experimental analysis, this study determined that the non-renewable resources of the two cities designated M and N dropped from 82% and 99% in 2017 to 78% and 79% in 2021, a decrease of 3% and 20%, respectively. This shows that the non-renewable resources of the four cities in area A generally showed a downward trend. The experimental results show that the deep learning theory and the environmental regulation model play a specific and effective role in the researching of the ecological business economy.
Keywords	ecological business economy ; deep learning ; environmental regulation model ; environmental protection ; sustainable development ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	333
Language	English
Publishing date	2023-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Can neurocognition, brain neurotrophic factor, triglyceride, and total cholesterol predict suicidal ideation in first-episode Han Chinese patients with schizophrenia?

Dongxia, Li / Li, Ma / Yingying, Feng

Brain and behavior

2024 Volume 14, Issue 5, Page(s) e3499

Abstract: Objective: Previous studies have suggested that the suicide rate of patients with schizophrenia is high. This study investigates factors influencing suicidal ideation in first-episode schizophrenia patients, focusing on cognitive function, brain-derived ...

Abstract	Objective: Previous studies have suggested that the suicide rate of patients with schizophrenia is high. This study investigates factors influencing suicidal ideation in first-episode schizophrenia patients, focusing on cognitive function, brain-derived neurotrophic factor (BDNF), triglyceride (TG), and total cholesterol (TC) in patients with first-episode schizophrenia. Methods: A total of 123 patients with first-episode schizophrenia and 38 healthy controls were included in the study. The patients were divided into suicidal and nonsuicidal ideation groups based on the Beck Scale for Suicidal Ideation, and they were assessed with Positive and Negative Syndrome Scale (PANSS). Cognitive function was assessed using the Chinese version of the MATRICS consensus cognitive battery (MCCB) and the serum BDNF, TG, and TC were detected. The main statistical methods include t-test, χ Results: 26.02% of patients exhibited suicidal ideation. Higher PANSS and TC levels were risk factors, while higher MCCB scores and BDNF levels were protective factors. ROC analysis indicated AUCs of 0.630, 0.724, and 0.762 for serum BDNF, PANSS, and MCCB, respectively, with a combined AUC of 0.870. Conclusion: Serum BDNF level, PANSS score, and MCCB score can be used as auxiliary predictors of suicidal ideation in schizophrenic patients. Combining these three indicators can effectively predict suicidal ideation in schizophrenic patients.
MeSH term(s)	Humans ; Brain-Derived Neurotrophic Factor/blood ; Schizophrenia/blood ; Male ; Female ; Suicidal Ideation ; Adult ; Triglycerides/blood ; Cholesterol/blood ; Young Adult ; China ; Schizophrenic Psychology ; Cognition/physiology ; Risk Factors
Chemical Substances	Brain-Derived Neurotrophic Factor ; Triglycerides ; Cholesterol (97C5T2UQ7J) ; BDNF protein, human (7171WSG8A2)
Language	English
Publishing date	2024-04-04
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2623587-0
ISSN	2162-3279 ; 2162-3279
ISSN (online)	2162-3279
ISSN	2162-3279
DOI	10.1002/brb3.3499
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Remote detection of Artemia slicks using multisatellite observations

Xin Wang / Jingyi Tian / Li Ma / Xianghan Sun / Liqiao Tian

International Journal of Digital Earth, Vol 17, Iss

spectral, spatial and temporal considerations

2024 Volume 1

Abstract: ABSTRACTArtemia has high commercial and ecological value, but few studies have considered the spectral, spatial and temporal requirements of Artemia multisatellite observations. Adopting Landsat-8 OLI and Sentinel-2 MSI as examples, we mainly analyzed ... ...

Abstract	ABSTRACTArtemia has high commercial and ecological value, but few studies have considered the spectral, spatial and temporal requirements of Artemia multisatellite observations. Adopting Landsat-8 OLI and Sentinel-2 MSI as examples, we mainly analyzed and compared their Artemia slick detection performance considering spectral sensitivity, spatial resolution and revisit cycle. First, the NIR bands of both sensors were most sensitive in Artemia slick detection. Second, compared to that of 2 m GF-6 PMS fusion images, the spatial uncertainty of MSI images was approximately ±16% using the brine shrimp index (BSI) to extract Artemia slicks, better than that of OLI images. The OLI and MSI detection limits under ideal conditions were 0.77% and 1.69%, corresponding to the smallest detectable Artemia slick sizes of approximately 6.93 and 1.69 m2. Third, multisatellite observations could improve dynamic Artemia slick monitoring ability. The OLI and MSI combination could enhance the monthly average observation frequency to 6.58 times. Finally, we examined the influences of the selected near-infrared (or red-edge) bands and Artemia slick width on the extraction results and analyzed detection limit changes and sensor consistency through practical considerations. Overall, these findings could provide support for remote Artemia observation, aiding in fishery management, global mapping and biomass estimation.
Keywords	Artemia slick detection ; spectral sensitivity ; spatial detection limit ; Landsat-8 OLI ; Sentinel-2 MSI ; Mathematical geography. Cartography ; GA1-1776
Subject code	333
Language	English
Publishing date	2024-12-01T00:00:00Z
Publisher	Taylor & Francis Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Generation of an induced pluripotent stem cell line (SHCDNi007-A) from a patient with pyruvate carboxylase deficiency carrying compound heterozygous (c.182 T > C/ c.2581G > A) variants in PC

Jingjing Sun / Pei Lu / Yunlin Shen / Li Ma

Stem Cell Research, Vol 66, Iss , Pp 102997- (2023)

1480

Abstract: Pyruvate carboxylase (PC) deficiency (PCD), due to biallelic PC variants, is a rare inherited metabolic disease, which is characterized by seizures, global developmental delay, as well as lactic acidosis, and elevated plasma pyruvate and alanine levels ... ...

Abstract	Pyruvate carboxylase (PC) deficiency (PCD), due to biallelic PC variants, is a rare inherited metabolic disease, which is characterized by seizures, global developmental delay, as well as lactic acidosis, and elevated plasma pyruvate and alanine levels in affected individuals. In the present study, a new induced pluripotent stem cell line (SHCDNi007-A) was generated from the peripheral blood mononuclear cells of a 2-month-old male infant with biallelic PC mutations c.(182 T > C;2581G > A), i.e. p.(Ile61Thr;Val861Met). This cell line is expected to facilitate the in vitro modeling of the disease pathophysiology and the development of future therapeutics for PCD.
Keywords	Biology (General) ; QH301-705.5
Language	English
Publishing date	2023-02-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Impacts of microphysical parameterizations on banded convective system in convection-permitting simulation

Di Wu / Li Ma / Tiantian Hu / Ruixi Zhang

Frontiers in Earth Science, Vol

a case study

2023 Volume 11

Abstract: The representation of cloud microphysical processes in models has always been a challenge leading to uncertainty in convective simulations. This paper evaluates the effect of cloud microphysical parameterizations on the simulation of mesoscale convective ...

Abstract	The representation of cloud microphysical processes in models has always been a challenge leading to uncertainty in convective simulations. This paper evaluates the effect of cloud microphysical parameterizations on the simulation of mesoscale convective systems (MCSs) through a realistic banded convection process. A series of numerical simulation experiments are performed using the Weather Research and Forecasting (WRF) model at a convection-permitting scale with a 3 km horizontal grid spacing. Specifically, four experiments considering different hydrometeor species within the WRF single-moment-microphysics schemes (WSMMPs) are conducted, and three additional sensitivity tests change the graupel particle properties. The results indicate that the significant differences in the times of convection initiation across the experiments reach 120 min, and more hydrometeor species may lead to later convection initiation. Moreover, the frozen graupel hydrometeor characteristics can appreciably alter the simulated convective morphology, even more than other hydrometeor species. When the graupel becomes smaller (such as Graupel-like), the fall speed of the graupel particles decreases. Therefore, more numerous graupel particles reside in clouds for a longer time, and experience more atmospheric diabatic heating and cooling effects. As a result, the simulated convective systems exhibit strong banded convective echo characteristics, the surface 10-m wind gust increases, and the cold pools associated with additional melting and evaporation become stronger, accelerating the propagation of the system. In contrast, larger and less abundant graupels (e.g., Hail-like) have a faster fall speed, and the atmospheric diabatic heating and cooling decrease by shortening the duration of their residence time within the clouds, resulting in a weak quasi-linear convective system, weak surface 10-m wind gust, unobvious cold pool, and slower propagation. Comparisons of the experiments further demonstrate that the fall speeds of frozen graupel ...
Keywords	WRF ; cloud microphysics parameters ; diabatic heating and cooling ; graupel particles ; banded convection ; Science ; Q
Subject code	551
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Research Trends of Written Corrective Feedback in L2 Writing

Jia Miao / Jiangmei Chang / Li Ma

SAGE Open, Vol

A Bibliometric Analysis

2023 Volume 13

Abstract: Written corrective feedback in Second Language Writing is one of the most important parts in L2 Acquisition and Language Teaching. CiteSpace is a convenient and effective bibliometric analysis tool which is widely used by researchers to explore the ... ...

Abstract	Written corrective feedback in Second Language Writing is one of the most important parts in L2 Acquisition and Language Teaching. CiteSpace is a convenient and effective bibliometric analysis tool which is widely used by researchers to explore the development tends of a certain field. The Web of Science core collection database was used as the primary source for data collection. There were 272 effective articles were selected from 2001 to 2021. The hot research topics in recent 20 years and emerging trends were showed. It was found that the research of written corrective feedback has entered a period of rapid development after the accumulation of basic knowledge in the early stage. Many empirical studies have been carried out. The distribution, cooperation, development trends and hotpots of current research are presented through visual map analysis in this study. In the future, the written corrective feedback research could try to concentrate on the psychological process and feedback providers, and it is also suggested to combine interdisciplinary knowledge such as education, psychology, neurology, etc., and use new research and measurement methods to promote the development of written corrective feedback.
Keywords	History of scholarship and learning. The humanities ; AZ20-999 ; Social Sciences ; H
Subject code	001
Language	English
Publishing date	2023-02-01T00:00:00Z
Publisher	SAGE Publishing
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A dual alignment-based multi-source domain adaptation framework for motor imagery EEG classification.

Xu, Dong-Qin / Li, Ming-Ai

Applied intelligence (Dordrecht, Netherlands)

2022 Volume 53, Issue 9, Page(s) 10766–10788

Abstract: Domain adaptation, as an important branch of transfer learning, can be applied to cope with data insufficiency and high subject variabilities in motor imagery electroencephalogram (MI-EEG) based brain-computer interfaces. The existing methods generally ... ...

Abstract	Domain adaptation, as an important branch of transfer learning, can be applied to cope with data insufficiency and high subject variabilities in motor imagery electroencephalogram (MI-EEG) based brain-computer interfaces. The existing methods generally focus on aligning data and feature distribution; however, aligning each source domain with the informative samples of the target domain and seeking the most appropriate source domains to enhance the classification effect has not been considered. In this paper, we propose a dual alignment-based multi-source domain adaptation framework, denoted DAMSDAF. Based on continuous wavelet transform, all channels of MI-EEG signals are converted respectively and the generated time-frequency spectrum images are stitched to construct multi-source domains and target domain. Then, the informative samples close to the decision boundary are found in the target domain by using entropy, and they are employed to align and reassign each source domain with normalized mutual information. Furthermore, a multi-branch deep network (MBDN) is designed, and the maximum mean discrepancy is embedded in each branch to realign the specific feature distribution. Each branch is separately trained by an aligned source domain, and all the single branch transfer accuracies are arranged in descending order and utilized for weighted prediction of MBDN. Therefore, the most suitable number of source domains with top weights can be automatically determined. Extensive experiments are conducted based on 3 public MI-EEG datasets. DAMSDAF achieves the classification accuracies of 92.56%, 69.45% and 89.57%, and the statistical analysis is performed by the kappa value and
Language	English
Publishing date	2022-08-25
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	1479519-X
ISSN	1573-7497 ; 0924-669X
ISSN (online)	1573-7497
ISSN	0924-669X
DOI	10.1007/s10489-022-04077-z
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Decoding motor imagery with a simplified distributed dipoles model at source level.

Li, Ming-Ai / Ruan, Zi-Wei

Cognitive neurodynamics

2022 Volume 17, Issue 2, Page(s) 445–457

Abstract: Motor imagery (MI) based brain computer interface significantly oriented the development of neuro-rehabilitation, and the crucial issue is how to accurately detect the changes of cerebral cortex for MI decoding. The brain activity can be calculated based ...

Abstract	Motor imagery (MI) based brain computer interface significantly oriented the development of neuro-rehabilitation, and the crucial issue is how to accurately detect the changes of cerebral cortex for MI decoding. The brain activity can be calculated based on the head model and observed scalp EEG, providing insights regarding cortical dynamics by using equivalent current dipoles with high spatial and temporal resolution. Now, all the dipoles within entire cortex or partial regions of interest are directly applied to data representation, this may make the key information weakened or lost, and it is worth studying how to choose the most important from numerous dipoles. In this paper, we devote to building a simplified distributed dipoles model (SDDM), which is combined with convolutional neural network (CNN), generating a MI decoding method at source level (called SDDM-CNN). First, all channels of raw MI-EEG signals are subdivided by a series of bandpass filters with width of 1 Hz, the average energies associated with any sub-band signals are calculated and ranked in a descending order to screen the top
Language	English
Publishing date	2022-06-22
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2276890-7
ISSN	1871-4099 ; 1871-4080
ISSN (online)	1871-4099
ISSN	1871-4080
DOI	10.1007/s11571-022-09826-x
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Article ; Online: Inosine pretreatment of pregnant rats ameliorates maternal inflammation-mediated hypomyelination in pups via microglia polarization switch.

Han, Yong / Sun, Jinping / Xiaojuan / Li, Ma Xin / Ma, Quanrui

Brain research

2024 Volume 1834, Page(s) 148844

Abstract: Periventricular leukomalacia (PVL) is a neurological condition observed in premature infants, characterized by hypomyelination and activation of microglia. Maternal inflammation-induced brain injury in offspring significantly contributes to the ... ...

Abstract	Periventricular leukomalacia (PVL) is a neurological condition observed in premature infants, characterized by hypomyelination and activation of microglia. Maternal inflammation-induced brain injury in offspring significantly contributes to the development of PVL. Currently, there are no clinical pharmaceutical interventions available for pregnant women to prevent maternal inflammation-mediated brain injury in their offspring. Inosine has been shown to modulate the immune response in diverse stressful circumstances, such as injury, ischemia, and inflammation. The aim of this investigation was to examine the potential prophylactic impact of inosine on offspring PVL induced by maternal inflammation. This was accomplished by administering a 1 mg/ml inosine solution (40 ml daily) to pregnant Sprague-Dawley (SD) rats for 16 consecutive days prior to their intraperitoneal injection of lipopolysaccharide (350 µg/kg, once a day, for two days). The results showed that maternal inosine pretreatment significantly reversed the reduction in MBP and CNPase (myelin-related markers), CC-1 and Olig2 (oligodendrocyte-related markers) in their PVL pups (P7), suggesting that inosine administration during pregnancy could improve hypomyelination and enhance the differentiation of oligodendrocyte precursor cells (OPCs) in their PVL pups. Furthermore, the protective mechanism of inosine against PVL is closely associated with the activation and polarization of microglia. This is evidenced by a notable reduction in the quantity of IBA 1-positive microglia, a decrease in the level of CD86 (a marker for M1 microglia), an increase in the level of Arg 1 (a marker for M2 microglia), as well as a decrease in the level of pro-inflammatory factors TNF-α, IL-1β, and IL-6, and an increase in the level of anti-inflammatory factors IL-4 and IL-10 in the brain of PVL pups following maternal inosine pretreatment. Taken together, inosine pretreatment of pregnant rats can improve hypomyelination in their PVL offspring by triggering the M1/M2 switch of microglia.
MeSH term(s)	Animals ; Female ; Pregnancy ; Microglia/drug effects ; Microglia/metabolism ; Rats, Sprague-Dawley ; Rats ; Inosine/pharmacology ; Inflammation/metabolism ; Lipopolysaccharides/pharmacology ; Leukomalacia, Periventricular/metabolism ; Myelin Sheath/metabolism ; Myelin Sheath/drug effects ; Animals, Newborn ; Prenatal Exposure Delayed Effects
Chemical Substances	Inosine (5A614L51CT) ; Lipopolysaccharides
Language	English
Publishing date	2024-03-01
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1200-2
ISSN	1872-6240 ; 0006-8993
ISSN (online)	1872-6240
ISSN	0006-8993
DOI	10.1016/j.brainres.2024.148844
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