A Novel Spinel Ferrite-Hexagonal Ferrite Composite for Enhanced Magneto-Electric Coupling in a Bilayer with PZT.

The magnetoelectric effect (ME) is an important strain mediated-phenomenon in a ferromagnetic-piezoelectric composite for a variety of sensors and signal processing devices. A bias magnetic field, in general, is essential to realize a strong ME coupling in most composites. Magnetic phases with (i) high magnetostriction for strong piezomagnetic coupling and (ii) large anisotropy field that acts as a built-in bias field are preferred so that miniature, ME composite-based devices can operate without the need for an external magnetic field. We are able to realize such a magnetic phase with a composite of (i) barium hexaferrite (BaM) with high magnetocrystalline anisotropy field and (ii) nickel ferrite (NFO) with high magnetostriction. The BNx composites, with (100 - x) wt.% of BaM and x wt.% NFO, for x = 0-100, were prepared. X-ray diffraction analysis shows that the composites did not contain any impurity phases. Scanning electron microscopy images revealed that, with an increase in NFO content, hexagonal BaM grains become prominent, leading to a large anisotropy field. The room temperature saturation magnetization showed a general increase with increasing BaM content in the composites. NFO rich composites with x ≥ 60 were found to have a large magnetostriction value of around -23 ppm, comparable to pure NFO. The anisotropy field HA of the composites, determined from magnetization and ferromagnetic resonance (FMR) measurements, increased with increasing NFO content and reached a maximum of 7.77 kOe for x = 75. The BNx composite was cut into rectangular platelets and bonded with PZT to form the bilayers. ME voltage coefficient (MEVC) measurements at low frequencies and at mechanical resonance showed strong coupling at zero bias for samples with x ≥ 33. This large in-plane HA acted as a built-in field for strong ME effects under zero external bias in the bilayers. The highest zero-bias MEVC of ~22 mV/cm Oe was obtained for BN75-PZT bilayers wherein BN75 also has the highest HA. The Bilayer of BN95-PZT showed a maximum MEVC ~992 mV/cm Oe at electromechanical resonance at 59 kHz. The use of hexaferrite-spinel ferrite composite to achieve strong zero-bias ME coupling in bilayers with PZT is significant for applications related to energy harvesting, sensors, and high frequency devices.

The paradox prevails: Outcomes are better in critically ill obese patients regardless of the comorbidity burden.

During critical illness, obese patients have better outcomes compared to patients with normal BMI, and this is known as the obesity paradox. The difference in comorbidity burden have been implied to be responsible for the paradox. We performed a retrospective review from 2001 to 2012 of critically ill patients from the Medical Information Mart for Intensive Care database. We included 11,433 patients and classified them according to body mass index (BMI) and comorbidity burden (Elixhauser comorbidity measure). The odds of inpatient mortality were lower in obese patients compared to patients with normal BMI; in group with the least comorbidity score (Elixhauser <0) [OR: 0.47, CI (0.28-0.80), p-value 0.006] and higher comorbidity scores, (Elixhauser 1-5) [(OR: 0.66, CI (0.46-0.95), p-value 0.02)] and (Elixhauser 6-13) [OR: 0.69, CI (0.53-0.92), p-value 0.01]. 30-day mortality was also significantly lower in obese patients, in groups with the lowest (Elixhauser <0) [OR:49, CI (0.31-0.77), p-value 0.002] as well as the highest comorbidity burden (Elixhauser >14) [OR:0.59, CI (0.45-0.77), p-value <.001]. Subgroup analysis in patients with various comorbidities showed better outcomes in obese patients. These findings show that the decreased odds of mortality in critically ill obese patients is independent of the comorbidity burden or type of comorbidity.

What Happened to Me while I Was in the Hospital? Challenges and Opportunities for Generating Patient-Friendly Hospitalization Summaries.

Comprehending medical information is a challenging task, especially for people who have not received formal medical education. When patients are discharged from the hospital, they are provided with lengthy medical documents that contain intricate terminologies. Studies have shown that if people do not understand the content of their health documents, they will neither look for new information regarding their illness nor will they take actions to prevent or recover from their health issue. In this article, we highlight the need for generating personalized hospital-stay summaries and several research challenges associated with this task. The proposed directions are directly informed by our ongoing work in generating concise and comprehensible hospitalization summaries that are tailored to suit the patient's understanding of medical terminologies and level of engagement in improving their own health. Our preliminary evaluation shows that our summaries effectively present required medical concepts.

Physician nurse care: A new use of UMLS to measure professional contribution: Are we talking about the same patient a new graph matching algorithm?

BACKGROUND: Physician and nurses have worked together for generations; however, their language and training are vastly different; comparing and contrasting their work and their joint impact on patient outcomes is difficult in light of this difference. At the same time, the EHR only includes the physician perspective via the physician-authored discharge summary, but not nurse documentation. Prior research in this area has focused on collaboration and the usage of similar terminology. OBJECTIVE: The objective of the study is to gain insight into interprofessional care by developing a computational metric to identify similarities, related concepts and differences in physician and nurse work. METHODS: 58 physician discharge summaries and the corresponding nurse plans of care were transformed into Unified Medical Language System (UMLS) Concept Unique Identifiers (CUIs). MedLEE, a Natural Language Processing (NLP) program, extracted "physician terms" from free-text physician summaries. The nursing plans of care were constructed using the HANDS© nursing documentation software. HANDS© utilizes structured terminologies: nursing diagnosis (NANDA-I), outcomes (NOC), and interventions (NIC) to create "nursing terms". The physician's and nurse's terms were compared using the UMLS network for relatedness, overlaying the physician and nurse terms for comparison. Our overarching goal is to provide insight into the care, by innovatively applying graph algorithms to the UMLS network. We reveal the relationships between the care provided by each professional that is specific to the patient level. RESULTS: We found that only 26% of patients had synonyms (identical UMLS CUIs) between the two professions' documentation. On average, physicians' discharge summaries contain 27 terms and nurses' documentation, 18. Traversing the UMLS network, we found an average of 4 terms related (distance less than 2) between the professions, leaving most concepts as unrelated between nurse and physician care. CONCLUSION: Our hypothesis that physician's and nurse's practice domains are markedly different is supported by the preliminary, quantitative evidence we found. Leveraging the UMLS network and graph traversal algorithms, allows us to compare and contrast nursing and physician care on a single patient, enabling a more complete picture of patient care. We can differentiate professional contributions to patient outcomes and related and divergent concepts by each profession.