WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14517/18

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Transverse Vibrations and Stability of Viscoelastic Axially Moving Rayleigh Beams Under Thermal Fields: an Analytical Approach
(Elsevier, 2025) Sichani, Farzam Fatehi; Mokhtarian, Ali; Babadoust, Shahram; Salahshour, Soheil
In this work, the flexural vibrations and stability of viscoelastic beams under axial motion and thermal fields are investigated using Rayleigh beam theory. The viscoelastic behavior is modeled through the Kelvin-Voigt and Maxwell models, and the governing differential equation is derivative utilizing Hamilton's principle. To create a more realistic model, thermal stresses in the beam are simulated using both linear and non-linear models. An innovative analytical solution method for these equations is presented, employing a power series approach to solve equations. The research provides an explicit mathematical expression for the mixed vibration modes of the beam under axial motion. Various parameters, such as rotational inertia, linear and non-linear thermal stresses, structural damping, and axial movement speed, are analyzed for their effects on the dynamic characteristics and instability of viscoelastic Rayleigh beams under axial motion. The findings indicate that incorporating rotational inertia and Rayleigh beam theory reduces the natural frequencies at low axial speeds but consistently increases the system's critical speed. Furthermore, rotational inertia induces distortions in the vibration mode shapes. Notably, the impact of rotational inertia on the second mode shape is significant, resulting in the loss of the nodal point in the second vibration mode shape of the beam under axial motion.
Relation Between Open Leadership and Techno-Stress in the Industrial Sector of Lebanon
(Emerald Group Publishing Ltd, 2025) Alameddine, Ashraf; Kocer, Canan
PurposeThe aim of this research is to assess whether open leadership can serve as a strategic approach to help in reducing technostress and improving employee well-being in the context of Lebanon's industrial sector.Design/methodology/approachA descriptive, quantitative approach was used, with data collected through a questionnaire distributed to 67 randomly selected white-collar employees from various industrial companies in Lebanon.FindingsThe analysis revealed a strong negative correlation between open leadership and technostress, with a particular emphasis on collaborative leadership. Regression analysis further confirmed that open leadership is a significant predictor of reduced technostress. These findings underscore the value of open leadership in creating a supportive work environment that enhances employee well-being and reduces the negative impacts of technology-related stress.Originality/valueThis research contributes to the limited body of literature on technostress within Lebanon's industrial sector. It offers practical recommendations for leaders seeking to manage digital stressors through open leadership, highlighting its potential as a universally applicable leadership style in technology-driven workplaces.
Recognizing the Unexpected: a Rare Cause of Rice Bodies in Brucellosis
(Wiley, 2025) Kalender, Ayse; Akcin, Ali Izzet; Eyvaz, Nuran; Dundar, Umit; Fazli, Sakhi Ahmad
Brucella is a gram-negative zoonotic agent transmitted by consumption of raw milk and infected meat. Among musculoskeletal manifestations, axial involvement such as spondylodiscitis and sacroiliitis is well documented, while peripheral manifestations like tenosynovitis and rice bodies remain underreported. In this case, flexor tenosynovitis and associated rice body involvement due to Brucella, which developed progressive swelling, pain, and restricted movement in the wrist and third finger of the hand after a minor abrasion, were investigated ultrasonographically. As far as we know, this is the first reported case of primary brucellosis with flexor tenosynovitis and associated rice bodies demonstrated ultrasonographically in the literature.
Effect of Osteotomy Strategy on Primary Stability and Intraosseous Temperature Rise: an Ex-Vivo Study
(BMC, 2025) Gokce Uckun, Gozde; Saygili, Sina; Cakir, Merve; Geckili, Onur
Background Primary stability is a perquisite for achieving successful osseointegration. Additionally thermal effect of implant bed preparation plays an important role in success of a dental implant. This ex vivo study was conducted to compare one step implant specific osteotomy and conventional osteotomy in terms of primary stability and thermal changes during surgery. Methods Forty eight implants were inserted into the sheep iliac crest bones each with a safe distance to each other and divided into six groups. In two of the groups implant specific osteotomy and in the remaining 4 groups conventional osteotomy was performed. In the groups, the primary stability of the trioval implants designed for the implant specific osteotomy were compared with the oval active threaded implants. The two osteotomy methods were also compared. Additionally the thermal changes during the two osteotomy methods were compared using a double-channel temperature monitoring device. Results Statistically significant differences (P <.05) were observed between the stability groups and the thermal evaluation groups (P <.05). Implant specific osteotomy revealed significantly higher stability than the conventional osteotomy (P <.001). Osteotomy without irrigation caused significantly higher thermal changes than the conventional osteotomy wit irrigation (P <.001). Conclusion Although the implant specific osteotomy reveals better primary stability, it causes higher temperature during drilling. However, since this increase is within the limits and doesn't cause a risk in terms of osseointegration, it may be used safely in clinical practice.
Deploying a Novel Deep Learning Framework for Segmentation of Specific Anatomical Structures on Cone-Beam CT
(Springer, 2025) Yuce, Fatma; Buyuk, Cansu; Bilgir, Elif; Celik, Ozer; Bayrakdar, Ibrahim Sevki
AimCone-beam computed tomography (CBCT) imaging plays a crucial role in dentistry, with automatic prediction of anatomical structures on CBCT images potentially enhancing diagnostic and planning procedures. This study aims to predict anatomical structures automatically on CBCT images using a deep learning algorithm.Materials and methodsCBCT images from 70 patients were analyzed. Anatomical structures were annotated using a regional segmentation tool within an annotation software by two dentomaxillofacial radiologists. Each volumetric dataset comprised 405 slices, with relevant anatomical structures marked in each slice. Seventy DICOM images were converted to Nifti format, with seven reserved for testing and the remaining sixty-three used for training. The training utilized nnUNetv2 with an initial learning rate of 0.01, decreasing by 0.00001 at each epoch, and was conducted for 1000 epochs. Statistical analysis included accuracy, Dice score, precision, and recall results.ResultsThe segmentation model achieved an accuracy of 0.99 for nasal fossa, maxillary sinus, nasopalatine canal, mandibular canal, foramen mentale, and foramen mandible, with corresponding Dice scores of 0.85, 0.98, 0.79, 0.73, 0.78, and 0.74, respectively. Precision values ranged from 0.73 to 0.98. Maxillary sinus segmentation exhibited the highest performance, while mandibular canal segmentation showed the lowest performance.ConclusionThe results demonstrate high accuracy and precision across most structures, with varying Dice scores indicating the consistency of segmentation. Overall, our segmentation model exhibits robust performance in delineating anatomical features in CBCT images, promising potential applications in dental diagnostics and treatment planning.
Transformation of Turkish Foreign Policy and Its Reflections on Turkey-Russia Relations
(Palgrave Macmillan, 2023) Ozdal, Habibe
Experimental Investigation and Correlation of Viscosity for MgO–MWCNT–CeO2/Water Hybrid Nanofluid
(Elsevier, 2025) Aalikhani, Ramin; Toghraie, Davood; Mehmandoust, Babak; Salahshour, Soheil
This study is focused on the viscosity of mono-nanofluids (MNFs) composed of CeO2/water, MWCNT/water, and MgO/water, as well as hybrid nanofluids (HNFs) namely MgO-MWCNT/water, MgO-CeO2/water, and CeO2- MWCNT/water. Additionally, a ternary hybrid nanofluid (THNF) of MgO-CeO2- MWCNT/water was examined. The study encompassed temperatures ranging from 20 to 60 degrees C and solid volume fractions (SVFs) of 0.1 % and 0.3 % for MNFs and HNFs, while THNF was studied at SVFs of 0.1 %, 0.2 %, 0.3 %, 0.4 %, and 0.5 %. Post-nanofluid preparation, zeta potential and dynamic light scattering (DLS) tests were performed to confirm stability, with tests conducted at the highest SVF (SVF = 0.5 %), indicating favorable nanofluid quality. Brookfield viscometer measurements were employed to assess nanofluid viscosity. The experimental findings revealed that viscosity decreases with rising temperature at a constant SVF, while it increases with rising SVF at a constant temperature. Notably, at SVF = 0.1 % and 0.3 %, the most significant viscosity increase occurred in the water/MWCNT MNF, reaching 2.7 times that of the base fluid (BF) at SVF = 0.3 % and T = 40 degrees C. For THNF, the highest viscosity increase was observed at SVF = 0.5 % and T = 50 degrees C, growing approximately 1.3 times that of BF. Subsequently, a mathematical model was proposed to predict THNF viscosity, demonstrating high consistency with laboratory results.
Heat Transfer and Entropy Investigation of Non-Newtonian Nanofluid Mixed Convection in a Cubic Cavity With a Wavy Bottom Wall Under the Influence of a Magnetic Field
(Elsevier, 2025) Younis, Obai; Abderrahmane, Aissa; Ali, Ali B. M.; Rashad, Ahmed; Ahmed, Sameh E.; Mourad, Abed; Guedri, Kamel
1)Background: This article reports 3D simulations of nanofluid motion within a three-dimensional cubic cavity occupied with a permeable medium. It was supposed that the motion region holds a hot spinning cylinder and has a wavy bottom plane with various undulation values. Also, the domain was separated into two levels., namely, the permeable layer and the power-law nanofluid layer. 2)Methods: The worked mixture is a non-Newtonian liquid, and the magnetic impacts are analyzed. The (FEM) with a triangle-shaped part form was used to resolve the governing formulas. The results were demonstrated for a variety of motion factors, including the cylinder's angular velocity (Omega = 0 to 2000), Hartmann number (Ha= 0-10), power-law index (n= 0.8, 1 and 1.4), and undulation numbers (N= 1 to 4). The effects of the different factors on motion, heat transmission, and entropy formation are illustrated in stream function, isotherms, and isentropic contours. Increased amounts of Omega, Da, N, phi, besides decreased values of Ha, enhance the heat transmission. 3)Significant Findings: The majority of entropy production is caused by heat transmission.; though liquid resistance and magneto impact also influence it.
Thermal and Mechanical Attributes and Swelling Percentage of Hydrogels by Changing in Magnetic Field Frequency Using Computer Simulation
(Pergamon-elsevier Science Ltd, 2025) Wang, Haoyu; Basem, Ali; Alhamdi, Sabah F. H.; Singh, Narinderjit Singh Sawaran; Al-Bahrani, Mohammed; Abdullaeva, Barno; Esmaeili, Sh.
The thermodynamic, mechanical, and expansion properties of synthetic hydrogels derived from polyacrylamide (PAM) are investigated in this study to the impact of magnetic field frequency (MFF) as an external stimulus. The impact of various MFFs on essential parameters, such as swelling percentage (SP), ultimate strength (US), Young's modulus (YM), heat flux (HF), and thermal conductivity (TC), is assessed using Molecular Dynamics (MD) simulation with LAMMPS software, ranging from 0.01 to 0.05 1/fs. It is important to note that our results indicate that the structural volume decreased from 356,985 to 349,982 & Aring; at 0.05 1/fs as the MFF increased. The alignment of polymer chains in the hydrogel was improved by increasing the MFF, resulting in a more compact structure. Through this compaction, the total structural volume diminished as the chains were drawn closer together, thereby reducing the spaces among them. US experienced a decrease from 0.0325 to 0.0331 MPa, while YM converged to 0.0008 MPa. The alignment and packaging of polymer chains improved, resulting in an increase in the US of hydrogels as the MFF increased. This enhanced alignment resulted in a material that can withstand a larger amount of stress before failing, as a result of the stronger intermolecular interactions. Additionally, the temperature coefficient (TC) increased to 0.56 W/m & sdot;K as the MFFs increased. An increase in molecular alignment and a decrease in free volume within the hydrogel can be attributed to the higher MFF. This enhanced alignment enabled the molecules to transfer heat more efficiently, resulting in improved TC and increased HF. These findings illustrate the substantial influence of MFF on hydrogel properties, offering valuable insights for the development of drug delivery systems and responsive materials.
Visualization of the Impact of Noise of the Closed-Form Solitary Wave Solutions for the Stochastic Zhiber-Shabat Model
(World Scientific Publ Co Pte Ltd, 2025) Yasin, Muhammad Waqas; Baber, Muhammad Zafarullah; Butt, Aleesha; Saeed, Iqra; Sulaiman, Tukur Abdulkadir; Yusuf, Abdullahi; Salahshour, Soheil
This paper investigates the stochastic Zhiber-Shabat problem under the multiplicative time noise analytically. The Sardar subequation approach is used to explored the solitons and solitary wave solutions under noise. Different families of solutions are gained in the form of dark soliton, singular soliton, bright soliton, complex dark-bright soliton and mixed form solitons along with mixed trigonometric functions. In mathematical physics, the solutions describe a wide range of physical phenomena including chemical kinetics, nonlinear optics, plasma physics, and quantum field theory. The composition of the results would also be displayed in 3D for a variety of parameters using the most modern scientific tools. Graphical representation of the solution's physical behavior demonstrates that the obtained solutions are generated as periodic soliton wave structures with noise term effects that are singular, dark, bright and complex bright dark. Using 3D, 2D, and contour plots with different noise strengths, we illustrate the characteristics of the nonlinear model. It has been shown that choosing a suitable set of parameters optimizes the visual representation of the physical structures.
Lipid Nanoparticles Driving Mrna Vaccine Innovations: From Concept To Clinic
(Elsevier, 2025) Hariri, Amirali; Mirian, Mina; Zarepour, Atefeh; Khosravi, Arezoo; Iravani, Siavash; Zarrabi, Ali
Messenger RNA (mRNA) vaccines have emerged as a transformative approach to immunization, driven by their ability to encode specific proteins that elicit targeted immune responses. However, the inherent instability of mRNA and its vulnerability to enzymatic degradation have necessitated the development of sophisticated delivery systems. This review explores the latest advancements in non-viral nanoparticle platforms-particularly lipid nanoparticles (LNPs), cationic liposomes, and lipid-polymer hybrids-for the efficient and safe delivery of mRNA. We analyze the structural and functional components of these nanoplatforms such as ionizable lipids, phospholipids, and PEGylated lipids, which enhance mRNA stability, circulation, and cellular uptake. Key challenges, including immunogenicity, cytotoxicity, and the "PEG dilemma" are examined alongside emerging solutions such as stimuli-responsive elements and targeted ligand modifications. Special emphasis is placed on microfluidic synthesis as a scalable production technique for generating uniform, clinically viable mRNA-loaded nanoparticles. By integrating insights from nanotechnology, immunology, and clinical medicine, this review highlights the critical innovations and ongoing challenges that shape the future of mRNA vaccine development. The conclusions drawn underscore the pivotal role of nanoparticle-based delivery systems in maximizing mRNA vaccine efficacy and advancing personalized immunization strategies against infectious diseases and cancer.
Exploring the Potential of Solar and Wind-Powered Green Hydrogen: Production, Costs and Environmental Impacts in South Asia
(Pergamon-elsevier Science Ltd, 2025) Chowdhury, Prangon; Das, Prithibi; Yeassin, Rahbaar; Agyekum, Ephraim Bonah; Al-Maaitah, Murad Irshied; Odoi-Yorke, Flavio
The global shift towards sustainability has increased interest in green hydrogen as an alternative to fossil fuels. While hydrogen feasibility studies exist for individual countries, there is a lack of comprehensive assessments for South Asia. This study evaluates green hydrogen production in South Asia, focusing on electricity generation from photovoltaic (PV) and wind turbine systems across eight countries. We analyze the levelized cost of hydrogen (LCOH), hydrogen production density, and carbon dioxide (CO2) mitigation potential using climate data and techno-economic model. The findings reveal significant variation in energy potential, with Afghanistan, Sri Lanka, and Pakistan showing strong wind resources, and Afghanistan, Maldives, and Sri Lanka demonstrating high solar potential. LCOH analysis shows wind-based hydrogen is more cost-effective than PV-based systems, particularly in Afghanistan, Pakistan, and Sri Lanka. CO2 mitigation estimates highlight the greater environmental benefits of wind-based hydrogen in regions with high wind speeds. Sensitivity analysis reveals that degradation and discount rates notably impact LCOH, with Bangladesh and Bhutan seeing the highest cost increases. Increasing electrolyzer efficiency consistently reduces LCOH. Additionally, the impact of variations in capital costs, operation and maintenance costs, and system lifespan on LCOH is also significant, with Bangladesh and Bhutan experiencing the highest cost growth. A comparative analysis with global studies shows that South Asia's costs are competitive or lower than those in other regions. These insights offer valuable guidance for policymakers and investors to accelerate hydrogen adoption in South Asia.
Canary in a Coal Mine: Did Financial Investors See World War I Coming
(Wiley, 2025) Hanedar, Avni Onder; Goktan, Mehmet Gokhan; Ince, Tunc
A series of ongoing geopolitical conflicts characterized the years leading up to 1914. Although some countries, such as the Ottoman Empire, faced severe political and economic challenges, the impact on the global financial system was uneven. Our paper examines whether declining bond prices signaled investors' expectations of coming conflicts. By highlighting the difficulty in foreseeing geopolitical instabilities, our results offer a historical perspective on the wars of the early twentieth century. They suggest that investors began to anticipate the onset of major wars due to the uncertainty arising from regional conflicts in Africa and the Balkans.
Effect of Using Wire Coils and Aluminum Oxide Nanofluid on Heat Transfer in a Double-Pipe Heat Exchanger and Predicting Data With Artificial Neural Networks
(Elsevier, 2025) Karimpooremam, Roohallah; Poursaied, Fatemeh; Keyvani, Bahram; Razmi, Milad; Aghayari, Reza; Toghraie, Davood; Salahshour, Soheil
The present study aims to experimentally investigate the Nusselt number and friction factor in a double-pipe heat exchanger equipped with wire coils and aluminum oxide nanofluid, with a particle size of approximately 55 nm, in Reynolds numbers from 4000 to 14000, volume fractions of 0.02, 0.04, and 0.06 %, and pitch ratios of 0, 1, 1.6, and 2.4. Then, a proposed correlation for the Nusselt number is presented, and finally, the experimental data are evaluated using an artificial neural network. The optimum increase of 135.6 % in the Nusselt number with aluminum oxide nanofluid occurs at a volume fraction of 0.06 %, a Reynolds number of 14000, and a pitch ratio of 1. The increase in the friction factor with nanofluid and wire coils, compared to the base fluid (water) without the wire coils, is approximately 7.06 %. The correlation coefficient, mean squared error, root mean squared error, and mean absolute error are calculated for the proposed correlation and artificial neural network. Furthermore, the maximum and minimum deviation margins obtained are +3.4211 and -3.2120, respectively. The results indicated that perceptron neural network of a 3-22-1 topology with Levenberg-Marquardt algorithm has successfully predicted the experimental data.
Molecular Dynamics Simulation of Thermal Behavior of Paraffin/Cu Nanoparticle PCM in a Non-Connected Rotating Ribbed Tube
(Pergamon-elsevier Science Ltd, 2025) Liu, Yaoyang; Basem, Ali; Al-zahy, Younis Mohamed Atiah; Singh, Narinderjit Singh Sawaran; Al-Bahrani, Mohammed; Abduvalieva, Dilsora; Esmaeili, Sh.
Applying molecular dynamics simulations, this study investigates the influence of different atomic ratios of Cu nanoparticles on the atomic and thermal behavior of a paraffin/Cu composite within a non-connected rotating ribbed tube. A simulation box measuring 50 x 150 x 50 & Aring;3 is employed, with periodic boundary conditions in y and z-coordinates. LAMMPS simulation is running for a total of 20 ns. The simulation model is validated through an equilibration phase for 10 ns, achieving a temperature of 300 K and a total energy of 1.450 kcal/mol. The results indicate that the maximum density decreases to 0.0852 atom/& Aring;3 as the atomic ratio of Cu nanoparticles increases from 1 to 7 %. Additionally, the velocity and temperature increased to 0.00493 & Aring;/fs and 766 K. Furthermore, the thermal conductivity increased from 0.63 to 0.68 W/m & sdot;K, and the heat transfer increased from 5.25 to 5.36 W/m2. The charging and discharging times decrease to 6.24 and 7.11 ns. These trends are reversed at an atomic ratio of 10 %: the maximum density increased, the velocity and temperature decreased, the heat flux and thermal conductivity decreased to 5.33 W/m2 and 0.67 W/m & sdot;K, and the charging/discharging times increased to 6.26 ns and 7.18 ns, respectively. These results indicate that an optimal concentration of 7 % Cu nanoparticles improved thermal conductivity. The paper examined the influence of nanoparticle saturation on thermal stability, demonstrating that excessive agglomeration adversely impacts heat conduction. This study offered for the development of superior nanoparticle-enhanced phase change materials in confined systems with unconnected rotating ribs, to improve heat dissipation and stability.
A Radial Basis Bayesian Regularization Neural Network Process for the Malaria Disease Model
(Elsevier, 2025) Sabir, Zulqurnain; Ismail, Tala; Sleem, Hussein; Umar, Muhammad; Salahshour, Soheil
Purpose: Malaria is one of the dangerous infectious disease produced through Plasmodium parasites, which is transmitted by the bite of a diseased Anopheles mosquito. The aim of this study is to solve the malaria disease model by using one of the stochastic computing neural network structures. The nonlinear system is presented into the populations of the host and vector using the insecticides and treatment. Method: A radial basis neural network uses the radial basis in the hidden layer. The performance of optimization is judged via Bayesian regularization for presenting the solutions of the model. The construction of the data is performed through the explicit Runge-Kutta that decreases the mean square error by adjusting the data for authentication 0.12, testing 0.15, and training 0.73. Results: The accurateness of designed stochastic technique is observed based on the matching of the obtained and the published solutions. Moreover, the negligible absolute error performances 10_ 05 to 10_ 07, and best training values 10_09 to 10_12 also support the exactness of the solver. In addition, the capability of the designed scheme is validated through different values based state transition, regression, and error histogram. Novelty: The designed stochastic computational radial basis neural network procedure along with the optimization of Bayesian regularization has never been applied before to solve the malaria disease system.
Gender Equality in Turkey
(Palgrave Macmillan, 2023) Alemdar, Zeynep
Turkish-American Relations: From the Catalyst of the Model Country Image To the Reference Point of Defensive Discourses
(Palgrave Macmillan, 2023) Peksen, Hasan Deniz
A Systematic Review of Nuclear Energy and Public Acceptance-A Detailed Analysis of Evolution, Emerging Trends, and Future Research Potentials
(Sage Publications inc, 2025) Agyekum, Ephraim Bonah; Tarawneh, Bashar; Rashid, Farhan Lafta; Kumar, Pankaj; Odoi-Yorke, Flavio; Togun, Hussein; Velkin, Vladimir Ivanovich
The Fukushima nuclear catastrophe in 2011 had a significant effect on nuclear development worldwide. Despite the numerous studies that assessed nuclear acceptance in recent times, there is currently no study that provides a detailed bibliometric review on the available literature. Therefore, a bibliometric review of public acceptance and nuclear energy has been carried out to better understand their evolution, trends, and future research potentials. In the period under review (2000-2023), 263 documents were published, and a total of 659 researchers produced the literature with an annual growth rate of 7.9%. The factorial analysis revealed key themes; grouped into three clusters: technical operational aspects of nuclear energy (Cluster 1), safety and risk management (Cluster 2), and public policy and social issues (Cluster 3). The word cloud analysis identified common subjects of research such as nuclear safety, risk perception, and public trust, suggesting that further research is needed on societal concerns and effective communication strategies. Collaboration patterns revealed strong research linkages between China and the US, and a number of other internationally collaborative countries such as the UK, Germany, and Japan. Future studies should investigate prediction models for public perceptions of nuclear power and concentrate on comprehending the elements that affect public trust, especially in developing nations. Research on public-private partnerships, psychological aspects influencing attitudes, and the effectiveness of educational initiatives is also crucial. The policy recommendations highlights the need for open governance and broad public participation in decisions concerning nuclear energy to alleviate concerns on safety and environmental risks and therefore nurture public trust in nuclear power.
Is It Possible To Predict Severe Postpartum Hemorrhage and the Need for Massive Transfusion in Placenta Previa Cases
(Via Medica, 2025) Kole, Emre; Akar, Bertan; Doger, Emek; Kole, Merve Cakir; Anik, Yonca; Caliskan, Eray
Objectives: The aim was to construct a reliable working model for patients with placenta previa (PP) that aids in the prediction of postpartum bleeding potential with data from antenatal imaging studies using both ultrasound (US) and magnetic resonance imaging (MRI). Material and methods: Forty-three patients with PP were evaluated initially with the US and then by 3-Tesla MRI. The placenta accreata index (PAI) was used during the US evaluation in order to define the risks. Uterine bulging, heterogeneous signal, dark placental bands, focal interruption of myometrium and tenting of bladder wall were regarded as predictive criteria in MRI evaluation. The correlation between the findings from US and MRI studies and subsequent haemorrhage, < 1000 mL, > 1000 mL and severe haemorrhage (> 2000 mL) and massive transfusion [> 5 units of red blood cells (RBC)] were used to build this predictive model. The findings from the imaging studies were also confirmed histopathologically. Results: In the multivariate analysis of data from patients stratified by bleed size either < 1000 mL or > 1000 mL, none of the MRI and ultrasound findings were found to be predictive. The multivariate analysis was done using the second stratification cut-point of 2000 mL, in patients bleeding > 2000 mL PAI values [OR: 2.3 (1.4-3.8)] and overall MRI reported placenta accreata spectrum [OR: 4.9 (1.8-12.9)] were found to be predictive. While MRI findings were not discriminative between transfusion groups, grade 3 loculation on US examination was found to be predictive for the need of transfusion of > 5 units [OR: 67.5 (8.2-549.4)]. There were no cases needing hysterectomy. Conclusions: Ultrasound and MRI findings in cases of PP can be helpful in predicting postpartum bleeding.

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