MESOSCALE MICROSTRUCTURE EVOLUTION, RELIABILITY AND FAILURE ANALYSIS OF HIGH TEMPERATURE TRANSIENT LIQUID PHASE SINTERING JOINTS

The continuous increase in application temperature of power electronic devices, due to the growing power density, miniaturization, and functionality in military and commercial applications, requires new packaging technologies with high temperature and reliability capabilities. Currently, the traditional maximum allowable temperature of power electronics (125°C) is a limiting factor for high temperature applications, such as space exploration, drilling, avionics, and electronic vehicles. Substitution of Silicon devices with wide bandgap (e.g., SiC) devices has extended the maximum allowable temperatures to 475 ̊C. However, this created the need for robust high temperature packaging materials, especially interconnects and attachments. High temperature solders are often too expensive, too brittle, or environmentally toxic to be used, leading to increased study of low temperature joining techniques, such as solid phase sintering and Transient Liquid Phase Sintering (TLPS), for producing high temperature stable attachments. TLPS is an emerging electronic interconnect technology enabling the formation of high temperature robust joints between metallic surfaces at low temperatures by the consumption of a transient, low temperature, liquid phase to form high temperature stable intermetallic compounds (IMCs). The performance and durability of these materials strongly depend on their microstructure, which is determined by their processing. The complicated process of IMC formation through eutectic solidification and the extensive number of parameters affecting the final microstructure make it impractical to experimentally study the effect of each factor. In this work, phase field modeling of the microstructure of TLPS materials fabricated by different processing methods will be conducted. Phase-field modeling (PFM) is a powerful thermodynamic consistent method in mesoscale modeling that simulates the evolution of intermetallic compounds during the solidification process, providing insight into the final microstructure. Application of this method facilitates the optimization of influential processing factors. Efforts will also be conducted to identify failure modes and mechanisms experimentally under dynamic, power and thermal cycling loads as a function of critical microstructural features, facilitating the optimization of joining parameters to obtain higher durability TLPS interconnections. The objective of this dissertation is to provide an insight into the processing of a reliable high temperature TLPS and facilitate their application in power electronic industries

Sex Determination Using Human Sphenoid Sinus in a Northeast Iranian Population: A Discriminant Function Analysis.

STATEMENT OF THE PROBLEM Sex determination, using skeletal remains, is of paramount importance in forensic studies. The skull accounts for the most sexual dimorphism after the pelvis. Recent studies have shown that paranasal sinuses are valuable in sex determination and considering the location of the sphenoid sinus, the risk of traumatic injuries to this structure is low. PURPOSE The present study aimed to evaluate the morphology of the sphenoid sinus and determine the validity of sphenoid sinus volume (SSV) in sex determination using cone beam computed tomography (CBCT) images. MATERIALS AND METHOD In this cross-sectional retrospective study, CBCT images of 469 Iranian patients (186 male and 283 female), aged 24-45 years, were selected. The morphology of the sphenoid sinus was recorded. 3D Slicer software (4.10.0) was used to assess SSVs in coronal and axial planes. For data analysis, t-test, chi-square test, and discriminant function analysis (DFA) were performed using predictive analytics software (ver. 18.0). RESULTS The most common morphology of the sphenoid sinus in both genders was the sellar type (50.5%). SSV was significantly larger in males than in females (p< 0.001). DFA showed that the capability of SSV in sex identification was 86.0% and 92.9% in males and females, respectively. CONCLUSION The findings of this study suggest that SSV is a reliable variable in gender discrimination in a northeast Iranian population. However, since the morphology of the sphenoid sinus and sex were independent of each other, the morphology of the sphenoid sinus is not a suitable indicator for sex determination

Mizaj assessment and data analysis methods in Amirkola health and aging project (AHAP cohort)

Background: One of the principles of Persian medicine (PM) is the individualized approach that is presented with the concept of Mizaj. In this viewpoint, Mizaj is determined for every person based on 10 criteria, which is a result of the Mizaj of the main organs, including the brain, liver, and heart. There is no standard diagnostic tool for Mizaj assessment in the elderly. The purpose of this study is to explain the method of Mizaj assessment and data analysis in the elderly in the second phase of the Amirkola health and aging project (AHAP) in Iran. Methods: In this study, a novel Mizaj assessment method in two phases is presented. In the first phase, 1541 elderly were assessed by a PM expert and typical diagnoses were determined. At the second phase, an expert panel including 5 PM experts evaluated the cases. The paraclinical and metric data of the elderly whose Mizaj agreed in the expert panel was used to assess its correlation with Mizaj. Conclusion: In the lack of valid and reliable questionnaires to assess the personalized viewpoint of PM, a new expert-based method has been introduced that can be used in similar studies. The result of the Mizaj assessment in this way will be used to obtain objective values for the Mizaj assessment

Dataset on the nurses’ knowledge, attitude and practice towards palliative care

When a patient enters the end stage of life threatening disease like cancer, treatment of pain and other symptoms must be considered to preserve quality of life (Gielen et al., 2011) [1]. Nurses have an important role in the care of patients who suffered from life threatening diseases. End of life cares is one of the routine activities of nurses (Gott et al., 2012) [2]. We surveyed knowledge, attitude and practice of nurses who worked in the hospitals of Neyshabur University of Medical Sciences towards palliative care from January 2016 to May 2016. A self-administered Persian questionnaire was used for data collection. The attitude scale was adopted from Frommelt Attitude toward Care of the Dying (Frommelt, 1991) and the knowledge questions were adopted from the Palliative Care Quiz for Nursing (Ross et al., 1996). The practice questions were also adopted from different related studies. Data analysis was performed by SPSS Statistics software for windows version 16. Our study showed that majority of nurses had favorable attitude but poor knowledge and practice towards palliative care. The results emphasize the importance and need for developing palliative care services in our hospitals. Keywords: Attitude, Knowledge, Practice, Nurses, Palliative car

Diabetes as one of the long-term COVID-19 complications: from the potential reason of more diabetic patients’ susceptibility to COVID-19 to the possible caution of future global diabetes tsunami

According to recent researches, people with diabetes mellitus (type 1 and 2) have a higher incidence of coronavirus disease 2019 (COVID-19), which is caused by a SARS-CoV-2 infection. In this regard, COVID-19 may make diabetic patients more sensitive to hyperglycemia by modifying the immunological and inflammatory responses and increasing reactive oxygen species (ROS) predisposing the patients to severe COVID-19 and potentially lethal results. Actually, in addition to COVID-19, diabetic patients have been demonstrated to have abnormally high levels of inflammatory cytokines, increased virus entrance, and decreased immune response. On the other hand, during the severe stage of COVID-19, the SARS-CoV-2-infected patients have lymphopenia and inflammatory cytokine storms that cause damage to several body organs such as β cells of the pancreas which may make them as future diabetic candidates. In this line, the nuclear factor kappa B (NF-κB) pathway, which is activated by a number of mediators, plays a substantial part in cytokine storms through various pathways. In this pathway, some polymorphisms also make the individuals more competent to diabetes via infection with SARS-CoV-2. On the other hand, during hospitalization of SARS-CoV-2-infected patients, the use of some drugs may unintentionally lead to diabetes in the future via increasing inflammation and stress oxidative. Thus, in this review, we will first explain why diabetic patients are more susceptible to COVID-19. Second, we will warn about a future global diabetes tsunami via the SARS-CoV-2 as one of its long-term complications

Artificial Intelligence in Cancer Care: From Diagnosis to Prevention and Beyond

&lt;p&gt;Artificial Intelligence (AI) has made significant strides in revolutionizing cancer care, encompassing various aspects from diagnosis to prevention and beyond. With its ability to analyze vast amounts of data, recognize patterns, and make accurate predictions, AI has emerged as a powerful tool in the fight against cancer. This article explores the applications of AI in cancer care, highlighting its role in diagnosis, treatment decision-making, prevention, and ongoing management. In the realm of cancer diagnosis, AI has demonstrated remarkable potential. By processing patient data, including medical imaging, pathology reports, and genetic profiles, AI algorithms can assist in early detection and accurate diagnosis. Image recognition algorithms can analyze radiological images, such as mammograms or CT scans, to detect subtle abnormalities and assist radiologists in identifying potential tumors. AI can also aid pathologists in analyzing tissue samples, leading to more precise and efficient cancer diagnoses. AI's impact extends beyond diagnosis into treatment decision-making. The integration of AI algorithms with clinical data allows for personalized treatment approaches. By analyzing patient characteristics, disease stage, genetic markers, and treatment outcomes, AI can provide valuable insights to oncologists, aiding in treatment planning and predicting response to specific therapies. This can lead to more targeted and effective treatment strategies, improving patient outcomes and reducing unnecessary treatments and side effects. Furthermore, AI plays a crucial role in cancer prevention. By analyzing genetic and environmental risk factors, AI algorithms can identify individuals at higher risk of developing certain cancers. This enables targeted screening programs and early interventions, allowing for timely detection and prevention of cancer. Additionally, AI can analyze population-level data to identify trends and patterns, contributing to the development of public health strategies for cancer prevention and control. AI's involvement in cancer care goes beyond diagnosis and treatment, encompassing ongoing management and survivorship. AI-powered systems can monitor treatment response, track disease progression, and detect recurrence at an early stage. By continuously analyzing patient data, including imaging, laboratory results, and clinical assessments, AI algorithms can provide real-time insights, facilitating timely interventions and adjustments to treatment plans. This proactive approach to disease management improves patient outcomes and enhances quality of life.&lt;/p&gt