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Article ; Online: A case of multiple myeloma with unusual presentation

Ali Momeni / Rooholah Masoomi

Journal of Shahrekord University of Medical Sciences, Vol 25, Iss 1, Pp 56-

2023 Volume 58

Abstract: Extramedullary plasmacytoma is a rare and unusual complication of multiple myeloma (MM). Some sites for the extramedullary involvement of MM are the liver, spleen, lymph node, lung, and skin. Renal failure is another complication of MM due to myeloma ... ...

Abstract	Extramedullary plasmacytoma is a rare and unusual complication of multiple myeloma (MM). Some sites for the extramedullary involvement of MM are the liver, spleen, lymph node, lung, and skin. Renal failure is another complication of MM due to myeloma kidney, uric acid nephropathy, hemoconcentration, or light chain disease. This study reported a case of MM with unusual presentation. She was a 61-year-old woman who was admitted to the internal ward due to severe renal failure, anemia, mild proteinuria, hypertension, thrombocytopenia, and soft tissue mass in both lungs in the spiral computed tomography (CT) scan. In the skull X-ray, there was not any lytic lesion. Further, plasma cells greater than 30% were observed in serum protein electrophoresis pick of gamma region and in the bone marrow aspiration, so the final diagnosis of the patients was MM with extramedullary plasmacytoma.
Keywords	multiple myeloma ; soft tissue mass ; renal failure ; Medicine ; R
Subject code	610
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	Shahrekord University of Medical Sciences
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Free-text Keystroke Authentication using Transformers

Momeni, Saleh / BabaAli, Bagher

A Comparative Study of Architectures and Loss Functions

2023

Abstract: Keystroke biometrics is a promising approach for user identification and verification, leveraging the unique patterns in individuals' typing behavior. In this paper, we propose a Transformer-based network that employs self-attention to extract ... ...

Abstract	Keystroke biometrics is a promising approach for user identification and verification, leveraging the unique patterns in individuals' typing behavior. In this paper, we propose a Transformer-based network that employs self-attention to extract informative features from keystroke sequences, surpassing the performance of traditional Recurrent Neural Networks. We explore two distinct architectures, namely bi-encoder and cross-encoder, and compare their effectiveness in keystroke authentication. Furthermore, we investigate different loss functions, including triplet, batch-all triplet, and WDCL loss, along with various distance metrics such as Euclidean, Manhattan, and cosine distances. These experiments allow us to optimize the training process and enhance the performance of our model. To evaluate our proposed model, we employ the Aalto desktop keystroke dataset. The results demonstrate that the bi-encoder architecture with batch-all triplet loss and cosine distance achieves the best performance, yielding an exceptional Equal Error Rate of 0.0186%. Furthermore, alternative algorithms for calculating similarity scores are explored to enhance accuracy. Notably, the utilization of a one-class Support Vector Machine reduces the Equal Error Rate to an impressive 0.0163%. The outcomes of this study indicate that our model surpasses the previous state-of-the-art in free-text keystroke authentication. These findings contribute to advancing the field of keystroke authentication and offer practical implications for secure user verification systems.
Keywords	Computer Science - Cryptography and Security ; Computer Science - Machine Learning
Subject code	006
Publishing date	2023-10-17
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Electromagnetic wave-based extreme deep learning with nonlinear time-Floquet entanglement.

Momeni, Ali / Fleury, Romain

Nature communications

2022 Volume 13, Issue 1, Page(s) 2651

Abstract: Wave-based analog signal processing holds the promise of extremely fast, on-the-fly, power-efficient data processing, occurring as a wave propagates through an artificially engineered medium. Yet, due to the fundamentally weak non-linearities of ... ...

Abstract	Wave-based analog signal processing holds the promise of extremely fast, on-the-fly, power-efficient data processing, occurring as a wave propagates through an artificially engineered medium. Yet, due to the fundamentally weak non-linearities of traditional electromagnetic materials, such analog processors have been so far largely confined to simple linear projections such as image edge detection or matrix multiplications. Complex neuromorphic computing tasks, which inherently require strong non-linearities, have so far remained out-of-reach of wave-based solutions, with a few attempts that implemented non-linearities on the digital front, or used weak and inflexible non-linear sensors, restraining the learning performance. Here, we tackle this issue by demonstrating the relevance of time-Floquet physics to induce a strong non-linear entanglement between signal inputs at different frequencies, enabling a power-efficient and versatile wave platform for analog extreme deep learning involving a single, uniformly modulated dielectric layer and a scattering medium. We prove the efficiency of the method for extreme learning machines and reservoir computing to solve a range of challenging learning tasks, from forecasting chaotic time series to the simultaneous classification of distinct datasets. Our results open the way for optical wave-based machine learning with high energy efficiency, speed and scalability.
Language	English
Publishing date	2022-05-12
Publishing country	England
Document type	Journal Article
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-022-30297-5
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Relation between Biochemical Parameters and Bone Density in Postmenopausal Women with Osteoporosis.

Salamat, Mohammad Reza / Momeni, Shokouh / Rastegari, Ali Asghar

Advanced biomedical research

2023 Volume 12, Page(s) 162

Abstract: Background: Osteoporosis is the most prevalent metabolic bone disease in postmenopausal women associated with reduced bone mass and increased bone fracture. Measuring bone density in the lumbar spine and hip is a reliable measure of bone mass and can ... ...

Abstract	Background: Osteoporosis is the most prevalent metabolic bone disease in postmenopausal women associated with reduced bone mass and increased bone fracture. Measuring bone density in the lumbar spine and hip is a reliable measure of bone mass and can therefore specify the risk of fracture. Dual-energy X-ray absorptiometry (DXA) is an accurate non-invasive system measuring bone density, with a low margin of error and no complications. The present study aimed to investigate the relationship between biochemical parameters with bone density in postmenopausal women. Materials and methods: This cross-sectional study was conducted on 87 postmenopausal women referred to osteoporosis centers in Isfahan. Bone density was measured in the spine and hip area using the DXA system. Serum levels of calcium, phosphorus, alkaline phosphatase, and magnesium were measured by an autoanalyzer, and serum levels of vitamin D were measured by high-performance liquid chromatography (HPLC). Results: The mean parameters of calcium, phosphorus, alkaline phosphatase, vitamin D, and magnesium did not show a significant difference between the two groups ( Conclusion: There was no significant relationship between the values of calcium, phosphorus, alkaline phosphatase, vitamin D, and magnesium parameters and bone density (spine and hip) in postmenopausal women with osteopenia or osteoporosis.
Language	English
Publishing date	2023-06-30
Publishing country	India
Document type	Journal Article
ZDB-ID	2672524-1
ISSN	2277-9175
ISSN	2277-9175
DOI	10.4103/abr.abr_135_22
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Article ; Online: Electromagnetic wave-based extreme deep learning with nonlinear time-Floquet entanglement

Ali Momeni / Romain Fleury

Nature Communications, Vol 13, Iss 1, Pp 1-

2022 Volume 11

Abstract: Wave-based analog signal processing has been challenging for complex nonlinear operations such as data forecasting or classification. The authors propose here an analog neuromorphic platform for optical wave-based machine learning characterized by energy ...

Abstract	Wave-based analog signal processing has been challenging for complex nonlinear operations such as data forecasting or classification. The authors propose here an analog neuromorphic platform for optical wave-based machine learning characterized by energy efficiency, speed and scalability.
Keywords	Science ; Q
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Literacy Model of assessment and evaluation of primary school teachers' curriculum

MOHAMMAD ALI PIRKAMALI / hossein momeni mahmouei / Yoosef Mahdipoor

مطالعات روانشناسی تربیتی, Vol 19, Iss 48, Pp 38-

Meta-combination based on Erwin's Model

2023 Volume 15

Abstract: The purpose of the current research was to identify the dimensions and components of the literacy model of assessment and evaluation of the curriculum of primary school teachers. The approach of the current research was qualitative and its meta-composite ...

Abstract	The purpose of the current research was to identify the dimensions and components of the literacy model of assessment and evaluation of the curriculum of primary school teachers. The approach of the current research was qualitative and its meta-composite method was based on the model of Erwin et al. (2011). The research community consisted of 174 scientific-research articles published in reputable scientific journals, which were in the field of literacy assessment and evaluation of teachers and providing models in this field between 2010 and now. The research sample included 39 researches that were purposefully collected and selected based on thematic data monitoring. The research data were collected from the qualitative analysis of the studied documents: based on the analysis of the data, the dimensions and components of the teacher's curriculum assessment and evaluation literacy model were classified into 5 dimensions and 18 axes. These dimensions include the knowledge of the curriculum elements (including the axes of knowledge regarding the content, goals, approaches of education, the knowledge of the learners, the space and place of the program, the time and the knowledge of educational evaluation), meta-knowledge (including the axes of perceptual knowledge and knowledge management), knowledge of the program Curriculum planning (including the axes of knowledge of program design and compilation, knowledge of curriculum dissemination, knowledge of implementing curricula and knowledge of curriculum evaluation), background knowledge (including axes of cultural-social knowledge, professional skills) E-organizational and factors and indicators affecting teacher evaluation) and humanistic knowledge (including the axes of interactive knowledge and emotional knowledge).
Keywords	assessment and evaluation literacy ; curriculum evaluation ; teachers ; meta-combination ; Philosophy. Psychology. Religion ; B ; Science ; Q ; Special aspects of education ; LC8-6691
Subject code	306
Language	Persian
Publishing date	2023-01-01T00:00:00Z
Publisher	University of Sistan and Baluchestan
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Relation between biochemical parameters and bone density in postmenopausal women with osteoporosis

Mohammad Reza Salamat / Shokouh Momeni / Ali Asghar Rastegari

Advanced Biomedical Research, Vol 12, Iss 1, Pp 162-

2023 Volume 162

Abstract	Background: Osteoporosis is the most prevalent metabolic bone disease in postmenopausal women associated with reduced bone mass and increased bone fracture. Measuring bone density in the lumbar spine and hip is a reliable measure of bone mass and can therefore specify the risk of fracture. Dual-energy X-ray absorptiometry (DXA) is an accurate non-invasive system measuring bone density, with a low margin of error and no complications. The present study aimed to investigate the relationship between biochemical parameters with bone density in postmenopausal women. Materials and Methods: This cross-sectional study was conducted on 87 postmenopausal women referred to osteoporosis centers in Isfahan. Bone density was measured in the spine and hip area using the DXA system. Serum levels of calcium, phosphorus, alkaline phosphatase, and magnesium were measured by an autoanalyzer, and serum levels of vitamin D were measured by high-performance liquid chromatography (HPLC). Results: The mean parameters of calcium, phosphorus, alkaline phosphatase, vitamin D, and magnesium did not show a significant difference between the two groups (P-value > 0.05). In the control group, the relationship between alkaline phosphatase and bone mineral content (BMC) and bony area (BA) in the spine was significant with a correlation coefficient of − 0.402 and 0.258, respectively (P-value < 0.05) and BMD and T-score in the femoral neck area showed a direct and significant relationship with phosphorus (correlation = 0.368; P value = 0.038). There was a significant relationship between the Z-score with calcium (correlation = 0.358; P value = 0.044). Conclusion: There was no significant relationship between the values of calcium, phosphorus, alkaline phosphatase, vitamin D, and magnesium parameters and bone density (spine and hip) in postmenopausal women with osteopenia or osteoporosis.
Keywords	alkaline phosphatase ; bone mineral density ; calcium ; magnesium ; menopause ; osteoporosis ; phosphorus ; vitamin d ; Medicine ; R ; Biology (General) ; QH301-705.5
Subject code	616
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	Wolters Kluwer Medknow Publications
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Human Endometrial Regenerative Cells for Neurological Disorders: Hype or Hope?

Momeni, Javad / Naserzadeh, Elnaz / Sepehrinezhad, Ali / Ashayeri Ahmadabad, Rezan / Sahab Negah, Sajad

International journal of stem cells

2024

Abstract: Despite enormous efforts, no effective medication has been found to significantly halt or even slow the progression of neurological diseases, such as acquired (e.g., traumatic brain injury, spinal cord injury, etc.) and chronic (e.g., Parkinson's disease, ...

Abstract	Despite enormous efforts, no effective medication has been found to significantly halt or even slow the progression of neurological diseases, such as acquired (e.g., traumatic brain injury, spinal cord injury, etc.) and chronic (e.g., Parkinson's disease, Alzheimer's disease, etc.) central nervous system disorders. So, researchers are looking for alternative therapeutic modalities to manage the disease's symptoms and stop it from worsening. Concerning disease-modifying capabilities, stem cell therapy has emerged as an expanding domain. Among different types of stem cells, human endometrial regenerative cells have excellent regenerative properties, making them suitable for regenerative medicine. They have the potential for self-renewal and differentiation into three types of stem cells: epithelial stem cells, endothelial side population stem cells, and mesenchymal stem cells (MSCs). ERCs can be isolated from endometrial biopsy and menstrual blood samples. However, there is no comprehensive evidence on the effects of ERCs on neurological disorders. Hence, we initially explore the traits of these specific stem cells in this analysis, followed by an emphasis on their therapeutic potential in treating neurological disorders.
Language	English
Publishing date	2024-01-08
Publishing country	Korea (South)
Document type	Journal Article ; Review
ZDB-ID	2914134-5
ISSN	2005-5447 ; 2005-3606
ISSN (online)	2005-5447
ISSN	2005-3606
DOI	10.15283/ijsc23091
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Estimating the Dose-Response Relationship for Ocular Pain after Radiotherapy of Head and Neck Cancers and Skull Base Tumors based on the LKB Radiobiological Model.

Momeni, Nastaran / Broomand, Mohammad Ali / Roozmand, Zahra / Hamzian, Nima

Journal of biomedical physics & engineering

2023 Volume 13, Issue 5, Page(s) 411–420

Abstract: Background: Radiotherapy is considered a compromise between the amount of killed tumor cells and the damage caused to the healthy tissue. Regarding this, radiobiological modeling is performed to individualize and optimize treatment strategies.: ... ...

Abstract	Background: Radiotherapy is considered a compromise between the amount of killed tumor cells and the damage caused to the healthy tissue. Regarding this, radiobiological modeling is performed to individualize and optimize treatment strategies. Objective: This study aimed to determine the normal tissue complication probability (NTCP) of acute ocular pain following radiotherapy. Material and methods: In this prospective observational study, the clinical data were collected from 45 patients with head and neck cancers and skull-base tumors, and dosimetric data were recorded after contouring the eye globe. Acute ocular pain was prospectively assessed with a three-month follow-up. The Lyman-Kutcher-Berman (LKB) parameters were estimated using the Area Under Curve (AUC) of Receiver Operating Characteristic (ROC) maximization and Maximum Likelihood (MLH) methods, and the NTCP of acute ocular pain was then determined using generalized LKB radiobiological model. The model performance was evaluated with AUC, Brier score, and Hosmer-Lemeshow tests. Results: Six out of 45 (13.33%) patients developed acute ocular pain (grade 1 or more). LKB model showed a weak dose-volume effect (n=0.09), tolerance dose for a 50% complication (TD Conclusion: The LKB model showed a high performance in determining the NTCP of ocular pain so that the probability of ocular pain will be less than 25% if the eye globe mean dose is kept below 12 Gy.
Language	English
Publishing date	2023-10-01
Publishing country	Iran
Document type	Journal Article
ZDB-ID	2673599-4
ISSN	2251-7200
ISSN	2251-7200
DOI	10.31661/jbpe.v0i0.2210-1554
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Article: A new truck-drone routing problem for parcel delivery by considering energy consumption and altitude.

Momeni, Maryam / Mirzapour Al-E-Hashem, S M J / Heidari, Ali

Annals of operations research

2023 , Page(s) 1–47

Abstract: The high population density in metropolitan areas, high-rise buildings, and changes in people's lifestyles have completely changed the way postal packages are delivered. People no longer go to the ground floor to receive a postal package. In the meantime, ...

Abstract	The high population density in metropolitan areas, high-rise buildings, and changes in people's lifestyles have completely changed the way postal packages are delivered. People no longer go to the ground floor to receive a postal package. In the meantime, the delivery of postal packages through the balconies and windows of the units on the upper floors of the buildings will gradually become inevitable. Hence, a new Vehicle Routing Problem with Drone mathematical model has been developed with the objective of minimizing total delivery time and with the ability to deliver postal packages in the path of drones at different heights. In addition, the drone's energy consumption is computed by taking into account wind speed, the weight of the postal parcel, the weight of the drone's body, and other factors in the drone's path. A two-phase algorithm based on the nearest neighborhood and local search is presented to solve the developed mathematical model in different instances. Several small-sized test problems are designed and solved, and the performance of the heuristic approach is evaluated compared to the outputs of the CPLEX solver. Finally, the proposed model is implemented on a real-world scale to demonstrate the efficacy and applicability of the proposed model as well as the heuristic approach. The results show that the model successfully finds the optimal planning of the delivery routes, especially when we deal with delivery points at different heights.
Language	English
Publishing date	2023-05-22
Publishing country	United States
Document type	Journal Article
ISSN	0254-5330
ISSN	0254-5330
DOI	10.1007/s10479-023-05381-8
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