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  1. Book ; Online: Resilient Strong Structural Controllability in Networks using Leaky Forcing in Graphs

    Abbas, Waseem

    2023  

    Abstract: This paper studies the problem of selecting input nodes (leaders) to make networks strong structurally controllable despite misbehaving nodes and edges. We utilize a graph-based characterization of network strong structural controllability (SSC) in terms ...

    Abstract This paper studies the problem of selecting input nodes (leaders) to make networks strong structurally controllable despite misbehaving nodes and edges. We utilize a graph-based characterization of network strong structural controllability (SSC) in terms of zero forcing in graphs, which is a dynamic coloring of nodes. We consider three types of misbehaving nodes and edges that disrupt the zero forcing process in graphs, thus, deteriorating the network SSC. Then, we examine a leader selection guaranteeing network SSC by ensuring the accuracy of the zero forcing process, despite $k$ misbehaving nodes/edges. Our main result shows that a network is resilient to $k$ misbehaving nodes/edges under one threat model if and only if it is resilient to the same number of failures under the other threat models. Thus, resilience against one threat model implies resilience against the other models. We then discuss the computational aspects of leader selection for resilient SSC and present a numerical evaluation.
    Keywords Electrical Engineering and Systems Science - Systems and Control
    Subject code 000
    Publishing date 2023-03-04
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Gas exchange patterns for a small, stored-grain insect pest,

    Abbas, Waseem / Withers, Philip C / Evans, Theodore A

    Bulletin of entomological research

    2023  Volume 113, Issue 3, Page(s) 361–367

    Abstract: Insects breathe using one or a combination of three gas exchange patterns; continuous, cyclic and discontinuous, which vary in their rates of exchange of oxygen, carbon dioxide and water. In general, there is a trade-off between lowering gas exchange ... ...

    Abstract Insects breathe using one or a combination of three gas exchange patterns; continuous, cyclic and discontinuous, which vary in their rates of exchange of oxygen, carbon dioxide and water. In general, there is a trade-off between lowering gas exchange using discontinuous exchange that limits water loss at the cost of lower metabolic rate. These patterns and hypotheses for the evolution of discontinuous exchange have been examined for relatively large insects (>20 mg) over relatively short periods (<4 h), but smaller insects and longer time periods have yet to be examined. We measured gas exchange patterns and metabolic rates for adults of a small insect pest of grain, the red flour beetle,
    MeSH term(s) Animals ; Tribolium ; Coleoptera ; Insect Control/methods ; Carbon Dioxide
    Chemical Substances Carbon Dioxide (142M471B3J)
    Language English
    Publishing date 2023-02-23
    Publishing country England
    Document type Journal Article
    ZDB-ID 280516-9
    ISSN 1475-2670 ; 0007-4853
    ISSN (online) 1475-2670
    ISSN 0007-4853
    DOI 10.1017/S0007485322000657
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    In stock of ZB MED Cologne/Königswinter

    Zs.B 514: Show issues Location:
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  3. Article ; Online: Thermal efficiency of radiated tetra-hybrid nanofluid [(Al

    Adnan / Abbas, Waseem / Z Bani-Fwaz, Mutasem / Kenneth Asogwa, Kanayo

    Science progress

    2023  Volume 106, Issue 1, Page(s) 368504221149797

    Abstract: Applications: The nanofluids and their upgraded version (ternary and tetra nanofluids) have a very rich thermal mechanism and convinced engineers and industrialist because of their dominant characteristics. These broadly use in chemical, applied thermal, ...

    Abstract Applications: The nanofluids and their upgraded version (ternary and tetra nanofluids) have a very rich thermal mechanism and convinced engineers and industrialist because of their dominant characteristics. These broadly use in chemical, applied thermal, mechanical engineering, and biotechnology. Particularly, heat transfer over a cylindrical surface is important in automobiles and heavy machinery.
    Purpose and methodology: Keeping in front the heat transfer applications, a model for Tetra-Composite Nanofluid [(Al
    Major findings: The mathematical analysis was performed via RK and determined the results graphically. The study gives suitable parametric ranges for high thermal efficiency and fluid movement. Applied magnetics forces were observed excellent to control the fluid motion, whereas curvature and buoyancy forces favor the motion. Thermal mechanism in Tetra nanofluid is dominant over ternary nanoliquid and nonlinear thermal radiations increased the heat transfer rate.
    Language English
    Publishing date 2023-01-08
    Publishing country England
    Document type Journal Article
    ZDB-ID 128412-5
    ISSN 2047-7163 ; 0036-8504 ; 0302-1785
    ISSN (online) 2047-7163
    ISSN 0036-8504 ; 0302-1785
    DOI 10.1177/00368504221149797
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    In stock of ZB MED Cologne/Königswinter

    Zs.B 731: Show issues Location:
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  4. Book ; Online: Distributed Design of Controllable and Robust Networks using Zero Forcing and Graph Grammars

    Patel, Priyanshkumar I. / Suresh, Johir / Abbas, Waseem

    2023  

    Abstract: This paper studies the problem of designing networks that are strong structurally controllable, and robust simultaneously. For given network specifications, including the number of nodes $N$, the number of leaders $N_L$, and diameter $D$, where $2 \le D \ ...

    Abstract This paper studies the problem of designing networks that are strong structurally controllable, and robust simultaneously. For given network specifications, including the number of nodes $N$, the number of leaders $N_L$, and diameter $D$, where $2 \le D \le N/N_L$, we propose graph constructions generating strong structurally controllable networks. We also compute the number of edges in graphs, which are maximal for improved robustness measured by the algebraic connectivity and Kirchhoff index. For the controllability analysis, we utilize the notion of zero forcing sets in graphs. Additionally, we present graph grammars, which are sets of rules that agents apply in a distributed manner to construct the graphs mentioned above. We also numerically evaluate our methods. This work exploits the trade-off between network controllability and robustness and generates networks satisfying multiple design criteria.

    Comment: American Control Conference (ACC 2023)
    Keywords Electrical Engineering and Systems Science - Systems and Control
    Subject code 000
    Publishing date 2023-03-09
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Computer Methods for Automatic Locomotion and Gesture Tracking in Mice and Small Animals for Neuroscience Applications: A Survey.

    Abbas, Waseem / Masip Rodo, David

    Sensors (Basel, Switzerland)

    2019  Volume 19, Issue 15

    Abstract: Neuroscience has traditionally relied on manually observing laboratory animals in controlled environments. Researchers usually record animals behaving freely or in a restrained manner and then annotate the data manually. The manual annotation is not ... ...

    Abstract Neuroscience has traditionally relied on manually observing laboratory animals in controlled environments. Researchers usually record animals behaving freely or in a restrained manner and then annotate the data manually. The manual annotation is not desirable for three reasons; (i) it is time-consuming, (ii) it is prone to human errors, and (iii) no two human annotators will 100% agree on annotation, therefore, it is not reproducible. Consequently, automated annotation for such data has gained traction because it is efficient and replicable. Usually, the automatic annotation of neuroscience data relies on computer vision and machine learning techniques. In this article, we have covered most of the approaches taken by researchers for locomotion and gesture tracking of specific laboratory animals, i.e. rodents. We have divided these papers into categories based upon the hardware they use and the software approach they take. We have also summarized their strengths and weaknesses.
    MeSH term(s) Algorithms ; Animals ; Behavior, Animal/physiology ; Gestures ; Image Processing, Computer-Assisted ; Locomotion/physiology ; Machine Learning ; Mice ; Neurosciences/trends ; Software ; Surveys and Questionnaires
    Language English
    Publishing date 2019-07-25
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s19153274
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  6. Article ; Online: Revisiting adjuvant ovarian suppression in premenopausal breast cancer patients.

    Abbas, Waseem / Rao, Ranga Raju

    Indian journal of cancer

    2019  Volume 56, Issue 4, Page(s) 293–296

    Abstract: Adjuvant ovarian suppression, on addition to chemotherapy, reduces the risk of breast cancer in pre-menopausal women after surgery and adjuvant hormonal therapy. Suppression of Ovarian Function Trial (SOFT) and Tamoxifen and Exemestane Trial (TEXT) ... ...

    Abstract Adjuvant ovarian suppression, on addition to chemotherapy, reduces the risk of breast cancer in pre-menopausal women after surgery and adjuvant hormonal therapy. Suppression of Ovarian Function Trial (SOFT) and Tamoxifen and Exemestane Trial (TEXT) showed greater benefit with exemestane in high risk females in comparison to Tamoxifen. Ovarian Function Suppression (OFS) and exemestane became the standard of care, with 30% patients experiencing grade 3 and more side effects. Much higher benefit was seen in high risk group. But there are concerns about incomplete OFS (estrogen escape) with exemestane plus OFS. Updated analysis of TEXT AND SOFT showed better survival benefit with OFS plus Tamoxifen as compared to OFS plus exemestane. Overall survival is a better end point. Should preference be given to Tamoxifen over exemestane? Further research is required to get the final answer.
    MeSH term(s) Androstadienes/therapeutic use ; Antineoplastic Agents, Hormonal/therapeutic use ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use ; Breast Neoplasms/drug therapy ; Breast Neoplasms/mortality ; Chemotherapy, Adjuvant/methods ; Clinical Trials as Topic ; Female ; Humans ; Ovary/drug effects ; Ovary/physiology ; Premenopause ; Quality of Life ; Risk ; Survival Analysis ; Tamoxifen/therapeutic use ; Treatment Outcome
    Chemical Substances Androstadienes ; Antineoplastic Agents, Hormonal ; Tamoxifen (094ZI81Y45) ; exemestane (NY22HMQ4BX)
    Language English
    Publishing date 2019-10-10
    Publishing country India
    Document type Journal Article ; Review
    ZDB-ID 410194-7
    ISSN 1998-4774 ; 0019-509X
    ISSN (online) 1998-4774
    ISSN 0019-509X
    DOI 10.4103/ijc.IJC_697_18
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    In stock of ZB MED Cologne/Königswinter

    Zs.B 581: Show issues Location:
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  7. Article ; Online: The GW5-WRKY53-SGW5 module regulates grain size variation in rice.

    Abbas, Waseem / Shalmani, Abdullah / Zhang, Jian / Sun, Qi / Zhang, Chunyu / Li, Wei / Cui, Yana / Xiong, Meng / Li, Yibo

    The New phytologist

    2024  Volume 242, Issue 5, Page(s) 2011–2025

    Abstract: Grain size is a crucial agronomic trait that affects stable yield, appearance, milling quality, and domestication in rice. However, the molecular and genetic relationships among QTL genes (QTGs) underlying natural variation for grain size remain elusive. ...

    Abstract Grain size is a crucial agronomic trait that affects stable yield, appearance, milling quality, and domestication in rice. However, the molecular and genetic relationships among QTL genes (QTGs) underlying natural variation for grain size remain elusive. Here, we identified a novel QTG SGW5 (suppressor of gw5) by map-based cloning using an F
    MeSH term(s) Oryza/genetics ; Oryza/anatomy & histology ; Oryza/growth & development ; Plant Proteins/genetics ; Plant Proteins/metabolism ; Gene Expression Regulation, Plant ; Quantitative Trait Loci/genetics ; Edible Grain/genetics ; Edible Grain/anatomy & histology ; Edible Grain/growth & development ; Genes, Plant ; Promoter Regions, Genetic/genetics ; Alleles ; Phenotype ; Transcription Factors/genetics ; Transcription Factors/metabolism ; Seeds/genetics ; Seeds/growth & development ; Seeds/anatomy & histology ; Protein Binding
    Chemical Substances Plant Proteins ; Transcription Factors
    Language English
    Publishing date 2024-03-22
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 208885-x
    ISSN 1469-8137 ; 0028-646X
    ISSN (online) 1469-8137
    ISSN 0028-646X
    DOI 10.1111/nph.19704
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    In stock of ZB MED Bonn / Germany

    Z 868: Show issues

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  8. Article: Prevalence of rheumatoid arthritis following COVID-19 vaccine: An autoimmune disorder.

    Rai, Aneesh / Aashish / Priya / Karmani, Sundiya / Abbas, Waseem / Khatri, Govinda

    Annals of medicine and surgery (2012)

    2022  Volume 82, Page(s) 104628

    Language English
    Publishing date 2022-09-09
    Publishing country England
    Document type Journal Article
    ZDB-ID 2745440-X
    ISSN 2049-0801
    ISSN 2049-0801
    DOI 10.1016/j.amsu.2022.104628
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  9. Book ; Online: A Survey of Graph Unlearning

    Said, Anwar / Derr, Tyler / Shabbir, Mudassir / Abbas, Waseem / Koutsoukos, Xenofon

    2023  

    Abstract: Graph unlearning emerges as a crucial advancement in the pursuit of responsible AI, providing the means to remove sensitive data traces from trained models, thereby upholding the right to be forgotten. It is evident that graph machine learning exhibits ... ...

    Abstract Graph unlearning emerges as a crucial advancement in the pursuit of responsible AI, providing the means to remove sensitive data traces from trained models, thereby upholding the right to be forgotten. It is evident that graph machine learning exhibits sensitivity to data privacy and adversarial attacks, necessitating the application of graph unlearning techniques to address these concerns effectively. In this comprehensive survey paper, we present the first systematic review of graph unlearning approaches, encompassing a diverse array of methodologies and offering a detailed taxonomy and up-to-date literature overview to facilitate the understanding of researchers new to this field. Additionally, we establish the vital connections between graph unlearning and differential privacy, augmenting our understanding of the relevance of privacy-preserving techniques in this context. To ensure clarity, we provide lucid explanations of the fundamental concepts and evaluation measures used in graph unlearning, catering to a broader audience with varying levels of expertise. Delving into potential applications, we explore the versatility of graph unlearning across various domains, including but not limited to social networks, adversarial settings, and resource-constrained environments like the Internet of Things (IoT), illustrating its potential impact in safeguarding data privacy and enhancing AI systems' robustness. Finally, we shed light on promising research directions, encouraging further progress and innovation within the domain of graph unlearning. By laying a solid foundation and fostering continued progress, this survey seeks to inspire researchers to further advance the field of graph unlearning, thereby instilling confidence in the ethical growth of AI systems and reinforcing the responsible application of machine learning techniques in various domains.

    Comment: 22 page review paper on graph unlearning
    Keywords Computer Science - Machine Learning
    Subject code 005
    Publishing date 2023-08-23
    Publishing country us
    Document type Book ; Online
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  10. Book ; Online: Enhanced Graph Neural Networks with Ego-Centric Spectral Subgraph Embeddings Augmentation

    Said, Anwar / Shabbir, Mudassir / Derr, Tyler / Abbas, Waseem / Koutsoukos, Xenofon

    2023  

    Abstract: Graph Neural Networks (GNNs) have shown remarkable merit in performing various learning-based tasks in complex networks. The superior performance of GNNs often correlates with the availability and quality of node-level features in the input networks. ... ...

    Abstract Graph Neural Networks (GNNs) have shown remarkable merit in performing various learning-based tasks in complex networks. The superior performance of GNNs often correlates with the availability and quality of node-level features in the input networks. However, for many network applications, such node-level information may be missing or unreliable, thereby limiting the applicability and efficacy of GNNs. To address this limitation, we present a novel approach denoted as Ego-centric Spectral subGraph Embedding Augmentation (ESGEA), which aims to enhance and design node features, particularly in scenarios where information is lacking. Our method leverages the topological structure of the local subgraph to create topology-aware node features. The subgraph features are generated using an efficient spectral graph embedding technique, and they serve as node features that capture the local topological organization of the network. The explicit node features, if present, are then enhanced with the subgraph embeddings in order to improve the overall performance. ESGEA is compatible with any GNN-based architecture and is effective even in the absence of node features. We evaluate the proposed method in a social network graph classification task where node attributes are unavailable, as well as in a node classification task where node features are corrupted or even absent. The evaluation results on seven datasets and eight baseline models indicate up to a 10% improvement in AUC and a 7% improvement in accuracy for graph and node classification tasks, respectively.

    Comment: 22nd IEEE International Conference on Machine Learning and Applications 2023
    Keywords Computer Science - Social and Information Networks ; Computer Science - Machine Learning
    Subject code 006
    Publishing date 2023-10-10
    Publishing country us
    Document type Book ; Online
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