Scalable production of large quantities of defect-free few-layer graphene by shear exfoliation in liquids

To progress from the laboratory to commercial applications, it will be necessary to develop industrially scalable methods to produce large quantities of defect-free graphene. Here we show that high-shear mixing of graphite in suitable stabilizing liquids results in large-scale exfoliation to give dispersions of graphene nanosheets. X-ray photoelectron spectroscopy and Raman spectroscopy show the exfoliated flakes to be unoxidized and free of basal-plane defects. We have developed a simple model that shows exfoliation to occur once the local shear rate exceeds 10(4) s(-1). By fully characterizing the scaling behaviour of the graphene production rate, we show that exfoliation can be achieved in liquid volumes from hundreds of millilitres up to hundreds of litres and beyond. The graphene produced by this method performs well in applications from composites to conductive coatings. This method can be applied to exfoliate BN, MoS2 and a range of other layered crystals

Cues disseminated by professional associations that represent 5 health care professions across 5 nations : lexical analysis of tweets

Background: Collaboration across health care professions is critical in efficiently and effectively managing complex and chronic health conditions, yet interprofessional care does not happen automatically. Professional associations have a key role in setting a profession’s agenda, maintaining professional identity, and establishing priorities. The associations’ external communication is commonly undertaken through social media platforms, such as Twitter. Despite the valuable insights potentially available into professional associations through such communication, to date, their messaging has not been examined. Objective: This study aimed to identify the cues disseminated by professional associations that represent 5 health care professions spanning 5 nations. Methods: Using a back-iterative application programming interface methodology, public tweets were sourced from professional associations that represent 5 health care professions that have key roles in community-based health care: general practice, nursing, pharmacy, physiotherapy, and social work. Furthermore, the professional associations spanned Australia, Canada, New Zealand, the United Kingdom, and the United States. A lexical analysis was conducted of the tweets using Leximancer (Leximancer Pty Ltd) to clarify relationships within the discourse. Results: After completing a lexical analysis of 50,638 tweets, 7 key findings were identified. First, the discourse was largely devoid of references to interprofessional care. Second, there was no explicit discourse pertaining to physiotherapists. Third, although all the professions represented in this study support patients, discourse pertaining to general practitioners was most likely to be connected with that pertaining to patients. Fourth, tweets pertaining to pharmacists were most likely to be connected with discourse pertaining to latest and research. Fifth, tweets about social workers were unlikely to be connected with discourse pertaining to health or care. Sixth, notwithstanding a few exceptions, the findings across the different nations were generally similar, suggesting their generality. Seventh and last, tweets pertaining to physiotherapists were most likely to refer to discourse pertaining to profession. Conclusions: The findings indicate that health care professional associations do not use Twitter to disseminate cues that reinforce the importance of interprofessional care. Instead, they largely use this platform to emphasize what they individually deem to be important and advance the interests of their respective professions. Therefore, there is considerable opportunity for professional associations to assert how the profession they represent complements other health care professions and how the professionals they represent can enact interprofessional care for the benefit of patients and carers

The value of routine measurement of serum calcitonin on insufficient, indeterminate, and suspicious thyroid nodule cytology

Routine calcitonin measurement in patients with nodular thyroid disease is rather controversial. The aim of this study was to evaluate the contribution of serum calcitonin measurement in the diagnostic evaluation of thyroid nodules with insufficient, indeterminate, or suspicious cytology. Out of 1668 patients who underwent thyroidectomy with the diagnosis of nodular thyroid disease and were screened, 873 patients with insufficient, indeterminate, or suspicious fine needle aspiration biopsy results were included in the study. From the total number of patients in this study, 10 (1.1%) were diagnosed as medullary thyroid cancer (MTC) using histopathology. The calcitonin level was detected to be above the assay-specific cut-off in 23 (2.6%) patients ranging between 6.5 - 4450 pg/mL. While hypercalcitoninemia was detected in all 10 MTC patients, a false positive elevation of serum calcitonin was detected in 13 patients (1.5%). Of the MTC group, 7 patients had cytology results that were suspicious for malignancy (Bethesda V), one patient’s cytology showed atypia of undetermined significance (Bethesda III) and two patient’s cytology results were suspicious for follicular neoplasm (Bethesda IV). Among the cases with non-diagnostic cytology (Bethesda I), none of the patients were diagnosed with MTC. In conclusion, routine serum calcitonin measurement can be performed in selected cases rather than in all nodular thyroid patients. While it is reasonable to perform routine calcitonin measurement in patients with Bethesda IV and Bethesda V, this measurement was not useful in Bethesda I patients. In Bethesda III patients, patient-based decisions can be made according to their calcitonin measurement.

Türkiye’de inme hastalarında atrial fibrilasyonun yönetimi: NöroTek çalışması gerçek hayat verileri

Objective: Atrial fibrillation (AF) is the most common directly preventable cause of ischemic stroke. There is no dependable neurology-based data on the spectrum of stroke caused by AF in Turkiye. Within the scope of NoroTek-Turkiye (TR), hospital-based data on acute stroke patients with AF were collected to contribute to the creation of acute-stroke algorithms.Materials and Methods: On May 10, 2018 (World Stroke Awareness Day), 1,790 patients hospitalized at 87 neurology units in 30 health regions were prospectively evaluated. A total of 929 patients [859 acute ischemic stroke, 70 transient ischemic attack (TIA)] from this study were included in this analysis.Results: The rate of AF in patients hospitalized for ischemic stroke/TIA was 29.8%, of which 65% were known before stroke, 5% were paroxysmal, and 30% were diagnosed after hospital admission. The proportion of patients with AF who received "effective" treatment [international normalization ratio >= 2.0 warfarin or non-vitamin K antagonist oral anticoagulants (NOACs) at a guideline dose] was 25.3%, and, either no medication or only antiplatelet was used in 42.5% of the cases. The low dose rate was 50% in 42 patients who had a stroke while taking NOACs. Anticoagulant was prescribed to the patient at discharge at a rate of 94.6%; low molecular weight or unfractionated heparin was prescribed in 28.1%, warfarin in 32.5%, and NOACs in 31%. The dose was in the low category in 22% of the cases discharged with NOACs, and half of the cases, who received NOACs at admission, were discharged with the same drug.Conclusion: NoroTekTR revealed the high but expected frequency of AF in acute stroke in Turkiye, as well as the aspects that could be improved in the management of secondary prophylaxis. AF is found in approximately one-third of hospitalized acute stroke cases in Turkiye. Effective anticoagulant therapy was not used in three-quarters of acute stroke cases with known AF. In AF, heparin, warfarin, and NOACs are planned at a similar frequency (one-third) within the scope of stroke secondary prophylaxis, and the prescribed NOAC dose is subtherapeutic in a quarter of the cases. Non-medical and medical education appears necessary to prevent stroke caused by AF.Amaç: Atrial fibrilasyon (AF) iskemik inmenin doğrudan önlenebilir en sık nedendir. Ülkemizde AF nedenli inme spektrumuna dair nöroloji kaynaklı geniş ölçekte bir veri bulunmamaktadır. NöroTek-Türkiye (TR) kapsamında akut inme algoritmalarının oluşturulmasına katkı yapması beklenen AF tespit edilen akut inme hastalarına dair hastane verisi toplanmıştır. Gereç ve Yöntem: 10 Mayıs 2018 Dünya İnme Farkındalık Günü’nde 30 sağlık bölgesine yer alan 87 nöroloji biriminde yatmakta olan 1.790 hasta prospektif olarak değerlendirilmiştir. Çalışmada yer alan toplam 929 hasta [859 akut iskemik inme, 70 geçici iskemik atak (GİA)] bu analize dahil edilmiştir. Bulgular: İskemik inme/GİA sebebiyle ile interne edilmiş hastalarda AF oranı %29,8 olup bunların %65’i bilinmekte olan, %5’i paroksismal ve %30’u yeni tanıdır. AF tanısı ile gelen hastalarda “etkin” tedavi [internasyonel normalizasyon oranı ≥2,0 varfarin veya rehber dozunda non-vitamin K antagonist oral antikoagülan (NOAK)] alanların oranı %25,3 olup, %42,5 olguda ya hiç ilaç kullanılmamakta ya da sadece antiplatelet kullanılmaktaydı. Düşük doz kullanım oranı 42 NOAK alırken inme geçirmiş olguda %50 idi. Taburcu edilirken antikoagülan %94,6 (düşük molekül ağırlıklı veya non-fraksiyone heparin %28,1; varfarin %32,5 ve NOAK %31) hastaya reçete edilmişti. NOAK ile taburcu edilen olguların %22’sinde doz düşük kategoride olup gelişte NOAK almakta olan olguların yarısı aynı ilaçla taburcu edilmiştir. Sonuç: NöroTekTR ülkemizde AF’nin akut inmedeki sıklığı yanı sıra sekonder proflaksi perspektifinde yönetiminin geliştirilebilecek yönlerini ortaya koydu. Türkiye’de hastanede yatan akut inme olgularının yaklaşık üçte birinde AF saptanmıştır. AF’si bilinen akut inme olgularının dörtte üçünde etkin antikoagülan tedavi kullanılmamaktaydı. AF’de inme sekonder proflaksisi kapsamında heparin, varfarin ve NOAK planlaması benzer sıklıkta (üçte bir) olup reçete edilen NOAK dozu dörtte bir olguda subterapötiktir. AF’ye bağlı inmenin önlenebilmesi non-medikal ve medikal eğitim gerekli görünmektedir

Artificial Neural Network (ANN) Approach to Prediction of Diffusion Bonding Behavior (Shear Strength) of Ni-Ti Alloys Manufactured by Powder Metalurgy Method

In this study, Artificial Neural Network approach to prediction of diffusion bonding behavior of Ni-Ti alloys, manufactured by powder metallurgy process, were obtained using a back-propagation neural network that uses gradient descent learning algorithm. Ni-Ti composite manufactured with a chemical composition of 51 % Ni – 49 % Ti in weight percent as mixture with a average dimension of 45μm. Diffusion welding process have been made under argon atmosphere, with a constant load of 5 MPa, under the temperature of 850, 875, 900 and 925ºC and, in 20, 40 and 60 minutes experiment time. Microstructure examination at bond interface were investigated by optical microscopy, SEM and EDS analysis. Specimens were tested for shear strength and metallographic evaluations. After the completion of experimental process and relevant test, to prepare the training and test (checking) set of the network, results were recorded in a file on a computer. In neural networks training module, different temperatures and welding periods were used as input, shear strength of bonded specimens at interface were used as outputs. Then, the neural network was trained using the prepared training set (also known as learning set). At the end of the training process, the test data were used to check the system accuracy. As a result the neural network was found successful in the prediction of diffusion bonding shear strength and behavior

Artificial Neural Network (ANN) Approach to Prediction of Diffusion Bonding Behavior (Shear Strength) of Ni-Ti Alloys Manufactured by Powder Metalurgy Method

In this study, Artificial Neural Network approach to prediction of diffusion bonding behavior of Ni-Ti alloys, manufactured by powder metallurgy process, were obtained using a back-propagation neural network that uses gradient descent learning algorithm. Ni-Ti composite manufactured with a chemical composition of 51 % Ni – 49 % Ti in weight percent as mixture with a average dimension of 45μm. Diffusion welding process have been made under argon atmosphere, with a constant load of 5 MPa, under the temperature of 850, 875, 900 and 925ºC and, in 20, 40 and 60 minutes experiment time. Microstructure examination at bond interface were investigated by optical microscopy, SEM and EDS analysis. Specimens were tested for shear strength and metallographic evaluations. After the completion of experimental process and relevant test, to prepare the training and test (checking) set of the network, results were recorded in a file on a computer. In neural networks training module, different temperatures and welding periods were used as input, shear strength of bonded specimens at interface were used as outputs. Then, the neural network was trained using the prepared training set (also known as learning set). At the end of the training process, the test data were used to check the system accuracy. As a result the neural network was found successful in the prediction of diffusion bonding shear strength and behavior