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Article: A Review of Recent Advances for the Detection of Biological, Chemical, and Physical Hazards in Foodstuffs Using Spectral Imaging Techniques.

Xie, Chuanqi / Zhou, Weidong

2023 Volume 12, Issue 11

Abstract: Traditional methods for detecting foodstuff hazards are time-consuming, inefficient, and destructive. Spectral imaging techniques have been proven to overcome these disadvantages in detecting foodstuff hazards. Compared with traditional methods, spectral ...

Abstract	Traditional methods for detecting foodstuff hazards are time-consuming, inefficient, and destructive. Spectral imaging techniques have been proven to overcome these disadvantages in detecting foodstuff hazards. Compared with traditional methods, spectral imaging could also increase the throughput and frequency of detection. This study reviewed the techniques used to detect biological, chemical, and physical hazards in foodstuffs including ultraviolet, visible and near-infrared (UV-Vis-NIR) spectroscopy, terahertz (THz) spectroscopy, hyperspectral imaging, and Raman spectroscopy. The advantages and disadvantages of these techniques were discussed and compared. The latest studies regarding machine learning algorithms for detecting foodstuff hazards were also summarized. It can be found that spectral imaging techniques are useful in the detection of foodstuff hazards. Thus, this review provides updated information regarding the spectral imaging techniques that can be used by food industries and as a foundation for further studies.
Language	English
Publishing date	2023-06-05
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2704223-6
ISSN	2304-8158
ISSN	2304-8158
DOI	10.3390/foods12112266
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A structure-preserving linearly homomorphic signature scheme with designated combiner.

Zhou, Xuan / Tian, Yuan / Zhong, Weidong / Zhou, Tanping / Yang, Xiaoyuan

PeerJ. Computer science

2024 Volume 10, Page(s) e1978

Abstract: Linearly homomorphic signature (LHS) allows the acquisition of a new legal signature using the homomorphic operation of the original signatures. However, the public composability of LHS also prevents it from being used in some scenarios where the ... ...

Abstract	Linearly homomorphic signature (LHS) allows the acquisition of a new legal signature using the homomorphic operation of the original signatures. However, the public composability of LHS also prevents it from being used in some scenarios where the combiner needs to be designated. The LZZ22 scheme designates a combiner and preserves the signature structure by having the signer and the designated combiner share a secret. However, LZZ22 is not secure enough because the secret is constant. Here, we first prove that there is a polynomial time adversary that can crack the secret in LZZ22 through multiple signature queries. Then, we propose a new scheme, which realizes all the functions of LZZ22 and fixes the security problem by changing the secret with the message. The proposed scheme is shown to be secure against existential forgery on adaptively chosen subspace attacks under the random oracle model. Finally, we detail how to apply our scheme to the proxy signature and perform it on a personal computer, and the results show that our scheme is efficient.
Language	English
Publishing date	2024-03-28
Publishing country	United States
Document type	Journal Article
ISSN	2376-5992
ISSN (online)	2376-5992
DOI	10.7717/peerj-cs.1978
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Does the "Belt and Road Initiative" benefit the environment? Insight from analysis of intra-industry trade in environment goods.

Zhou, Yacheng / Liu, Feiyu / Huo, Weidong / Peng, Changjiang

PloS one

2024 Volume 19, Issue 4, Page(s) e0300603

Abstract: The expansion of the Belt and Road Initiative (BRI) has raised a wide range of concerns about its environmental impact. Therefore, from the perspective of environmental impacts, this study used the two-way fixed effect staggered differences in ... ...

Abstract	The expansion of the Belt and Road Initiative (BRI) has raised a wide range of concerns about its environmental impact. Therefore, from the perspective of environmental impacts, this study used the two-way fixed effect staggered differences in differences (TWFE Staggered DID) method to examine the impact of the BRI on the Environment Goods (EGs) intra-industry trade (IIT) between China and other Belt and Road (B&R) countries, including a sample of 191 countries, covering the period from 2010 to 2019 for eliminating the impact of COVID-19 and the financial crisis in 2008 and 2009. Because only 135 countries signed a Memorandum of Understanding between 2010 and 2019, this study treated these B&R countries as the study group, and the other 73 countries (non-B&R countries) as the control group. This study described EGs using the 54 6-digit code Environment Goods in Harmonized Commodity Description and Coding System listed in the "APEC LIST OF ENVIRONMENT GOODS" published by the Asia-Pacific Economic Cooperation in 2012, and used the intra-industry trade index proposed by Grubel and Lloyd in 1971 to measuring dependent variable. The research results indicated that the BRI has significantly promoted bilateral EGs IIT. The mechanism test implied that, in addition to direct impacts, the BRI also has indirect impacts by boosting the energy restructuring of B&R countries. These results prove that the BRI has positive impacts on the environment. The heterogeneity test showed that there is a heterogeneous impact depending on the type of IIT, product categorization, B&R countries' income levels, and geographic environment. This study not only gives theoretical and empirical evidence of the positive environmental impacts of the BRI, but also provides practical guidance for the development of EGS IIT between China and B&R countries, thereby contributing to global carbon emissions reduction and environmental governance to some degree.
MeSH term(s)	Conservation of Natural Resources ; Environmental Policy ; Asia ; China ; Industry ; Economic Development ; Carbon Dioxide/analysis
Chemical Substances	Carbon Dioxide (142M471B3J)
Language	English
Publishing date	2024-04-02
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0300603
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Tuning of excitons in phosphorene atomic chains.

Huang, Wenzhuo / Zhong, Jun / Sheng, Weidong / Zhou, Aiping

Journal of physics. Condensed matter : an Institute of Physics journal

2023 Volume 36, Issue 7

Abstract: An universal scaling between the exciton binding energy and quasiparticle (QP) band gap was first discovered in two-dimensional (2D) semiconductors such as graphene derivatives, various transition materials dichalcogenides, and black phosphorus ( ... ...

Abstract	An universal scaling between the exciton binding energy and quasiparticle (QP) band gap was first discovered in two-dimensional (2D) semiconductors such as graphene derivatives, various transition materials dichalcogenides, and black phosphorus (Choi
Language	English
Publishing date	2023-11-15
Publishing country	England
Document type	Journal Article
ZDB-ID	1472968-4
ISSN	1361-648X ; 0953-8984
ISSN (online)	1361-648X
ISSN	0953-8984
DOI	10.1088/1361-648X/ad06f1
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Detection of the 5-hydroxymethylfurfural content in roasted coffee using machine learning based on near-infrared spectroscopy.

Xie, Chuanqi / Wang, Changyan / Zhao, Mengyao / Zhou, Weidong

Food chemistry

2023 Volume 422, Page(s) 136199

Abstract: Since 5-hydroxymethylfurfural (5-HMF) is carcinogenic to humans, its detection in foods is essential. This study performed near-infrared (NIR) spectroscopy (11998-4000 ... ...

Abstract	Since 5-hydroxymethylfurfural (5-HMF) is carcinogenic to humans, its detection in foods is essential. This study performed near-infrared (NIR) spectroscopy (11998-4000 cm
MeSH term(s)	Humans ; Coffee/chemistry ; Spectroscopy, Near-Infrared/methods ; Least-Squares Analysis ; Seeds/chemistry ; Support Vector Machine
Chemical Substances	Coffee ; 5-hydroxymethylfurfural (70ETD81LF0)
Language	English
Publishing date	2023-04-20
Publishing country	England
Document type	Journal Article
ZDB-ID	243123-3
ISSN	1873-7072 ; 0308-8146
ISSN (online)	1873-7072
ISSN	0308-8146
DOI	10.1016/j.foodchem.2023.136199
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Toward Estimating CO

Zou, Xinyuan / Zhu, Yingting / Lv, Jing / Zhou, Yuchi / Ding, Bin / Liu, Weidong / Xiao, Kai / Zhang, Qun

ACS omega

2024 Volume 9, Issue 4, Page(s) 4705–4720

Abstract: Predicting carbon dioxide ( ... ...

Abstract	Predicting carbon dioxide (CO
Language	English
Publishing date	2024-01-17
Publishing country	United States
Document type	Journal Article
ISSN	2470-1343
ISSN (online)	2470-1343
DOI	10.1021/acsomega.3c07962
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A Review of Recent Advances for the Detection of Biological, Chemical, and Physical Hazards in Foodstuffs Using Spectral Imaging Techniques

Xie, Chuanqi / Zhou, Weidong

Foods. 2023 June 05, v. 12, no. 11

2023

Abstract	Traditional methods for detecting foodstuff hazards are time-consuming, inefficient, and destructive. Spectral imaging techniques have been proven to overcome these disadvantages in detecting foodstuff hazards. Compared with traditional methods, spectral imaging could also increase the throughput and frequency of detection. This study reviewed the techniques used to detect biological, chemical, and physical hazards in foodstuffs including ultraviolet, visible and near-infrared (UV-Vis-NIR) spectroscopy, terahertz (THz) spectroscopy, hyperspectral imaging, and Raman spectroscopy. The advantages and disadvantages of these techniques were discussed and compared. The latest studies regarding machine learning algorithms for detecting foodstuff hazards were also summarized. It can be found that spectral imaging techniques are useful in the detection of foodstuff hazards. Thus, this review provides updated information regarding the spectral imaging techniques that can be used by food industries and as a foundation for further studies.
Keywords	Raman spectroscopy ; algorithms ; artificial intelligence ; foods ; hyperspectral imagery ; image analysis
Language	English
Dates of publication	2023-0605
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article ; Online
ZDB-ID	2704223-6
ISSN	2304-8158
ISSN	2304-8158
DOI	10.3390/foods12112266
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: m1A Regulatory gene signatures are associated with certain immune cell compositions of the tumor microenvironment and predict survival in kidney renal clear cell carcinoma.

Zhou, Linjun / Zhou, Weidong / Li, Yuan / Hua, Ruifang

European journal of medical research

2023 Volume 28, Issue 1, Page(s) 321

Abstract: Adenosine N1 methylation (m1A) of RNA, a type of post-transcriptional modification, has been shown to play a significant role in the progression of cancer. The objective of the current research was to analyze the genetic alteration and prognostic ... ...

Abstract	Adenosine N1 methylation (m1A) of RNA, a type of post-transcriptional modification, has been shown to play a significant role in the progression of cancer. The objective of the current research was to analyze the genetic alteration and prognostic significance of m1A regulators in kidney renal clear cell carcinoma (KIRC). Genomic and clinicopathological characteristics were obtained from 558 KIRC patients in the Cancer Genome Atlas (TCGA) and Gene Omnibus Expression (GEO) databases. Alterations in the gene expression of ten m1A-regulators were analyzed and survival analysis was performed using the Cox regression method. We also identified three clusters of patients based on their distinct m1A alteration patterns, using integrated analysis of the ten m1A-related regulators, which were significantly related to overall survival (OS), disease-free survival (DFS) and tumor microenvironment (TME) immune cell infiltration cells in KIRC. Our findings showed that m1A alteration patterns have critical roles in determining TME complexity and its immune cell composition. Furthermore, different m1A expression patterns were significantly associated with DFS and OS rates in KIRC patients. In conclusion, the identified m1A RNA modification patterns offer a potentially effective way to classify KIRC patients based on their TME immune cell infiltration, enabling the development of more personalized and successful treatment strategies for these patients.
MeSH term(s)	Kidney Neoplasms/epidemiology ; Kidney Neoplasms/genetics ; Kidney Neoplasms/immunology ; Kidney Neoplasms/pathology ; RNA Processing, Post-Transcriptional ; Carcinoma, Renal Cell/epidemiology ; Carcinoma, Renal Cell/genetics ; Carcinoma, Renal Cell/immunology ; Carcinoma, Renal Cell/pathology ; Humans ; Tumor Microenvironment ; Adenosine/metabolism ; Methylation ; Cluster Analysis ; Neoplastic Stem Cells ; Gene Expression Profiling ; Prognosis ; Disease-Free Survival ; Genes, Regulator
Chemical Substances	Adenosine (K72T3FS567)
Language	English
Publishing date	2023-09-07
Publishing country	England
Document type	Journal Article
ZDB-ID	1329381-3
ISSN	2047-783X ; 0949-2321
ISSN (online)	2047-783X
ISSN	0949-2321
DOI	10.1186/s40001-023-01292-3
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Zs.A 4636: Show issues

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Article ; Online: Cosine convolutional neural network and its application for seizure detection.

Liu, Guoyang / Tian, Lan / Wen, Yiming / Yu, Weize / Zhou, Weidong

Neural networks : the official journal of the International Neural Network Society

2024 Volume 174, Page(s) 106267

Abstract: Traditional convolutional neural networks (CNNs) often suffer from high memory consumption and redundancy in their kernel representations, leading to overfitting problems and limiting their application in real-time, low-power scenarios such as seizure ... ...

Abstract	Traditional convolutional neural networks (CNNs) often suffer from high memory consumption and redundancy in their kernel representations, leading to overfitting problems and limiting their application in real-time, low-power scenarios such as seizure detection systems. In this work, a novel cosine convolutional neural network (CosCNN), which replaces traditional kernels with the robust cosine kernel modulated by only two learnable factors, is presented, and its effectiveness is validated on the tasks of seizure detection. Meanwhile, based on the cosine lookup table and KL-divergence, an effective post-training quantization algorithm is proposed for CosCNN hardware implementation. With quantization, CosCNN can achieve a nearly 75% reduction in the memory cost with almost no accuracy loss. Moreover, we design a configurable cosine convolution accelerator on Field Programmable Gate Array (FPGA) and deploy the quantized CosCNN on Zedboard, proving the proposed seizure detection system can operate in real-time and low-power scenarios. Extensive experiments and comparisons were conducted using two publicly available epileptic EEG databases, the Bonn database and the CHB-MIT database. The results highlight the performance superiority of the CosCNN over traditional CNNs as well as other seizure detection methods.
MeSH term(s)	Humans ; Electroencephalography/methods ; Seizures/diagnosis ; Neural Networks, Computer ; Epilepsy/diagnosis ; Algorithms
Language	English
Publishing date	2024-03-24
Publishing country	United States
Document type	Journal Article
ZDB-ID	740542-x
ISSN	1879-2782 ; 0893-6080
ISSN (online)	1879-2782
ISSN	0893-6080
DOI	10.1016/j.neunet.2024.106267
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Zs.A 2365: Show issues

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Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

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Article ; Online: In-field and non-destructive determination of comprehensive maturity index and maturity stages of Camellia oleifera fruits using a portable hyperspectral imager.

Yuan, Weidong / Zhou, Hongping / Zhou, Yu / Zhang, Cong / Jiang, Xuesong / Jiang, Hongzhe

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy

2024 Volume 315, Page(s) 124266

Abstract: To efficiently detect the maturity stages of Camellia oleifera fruits, this study proposed a non-invasive method based on hyperspectral imaging technology. First, a portable hyperspectral imager was used for the in-field image acquisition of Camellia ... ...

Abstract	To efficiently detect the maturity stages of Camellia oleifera fruits, this study proposed a non-invasive method based on hyperspectral imaging technology. First, a portable hyperspectral imager was used for the in-field image acquisition of Camellia oleifera fruits at three maturity stages, and ten quality indexes were measured as reference standards. Then, factor analysis was performed to obtain the comprehensive maturity index (CMI) by analyzing the change trends and correlations of different indexes. To reduce the high dimensionality of spectral data, the successive projection algorithm (SPA) was employed to select effective feature wavelengths. The prediction models for CMI, including partial least squares regression (PLSR), support vector regression (SVR), extreme learning machine (ELM), and convolutional neural network regression (CNNR), were constructed based on full spectra and feature wavelengths; for CNNR, only the raw spectra were used as input. The SPA-CNNR model exhibited more promising performance (R
Language	English
Publishing date	2024-04-07
Publishing country	England
Document type	Journal Article
ZDB-ID	210413-1
ISSN	1873-3557 ; 0370-8322 ; 0584-8539 ; 1386-1425
ISSN (online)	1873-3557
ISSN	0370-8322 ; 0584-8539 ; 1386-1425
DOI	10.1016/j.saa.2024.124266
Database	MEDical Literature Analysis and Retrieval System OnLINE

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