Impact of micro-indentation load/time and Zinc concentration on the thermo-mechanical characteristics of amorphous Se78_{78}Te20_{20}Sn2_2 alloy

We have performed hardness measurement experiments under different loads and loading times by performing micro-indentation marks in the present work. Chalcogenide glasses (ChGs) comprising Se$_{78}$Te$_{20}$Sn$_2$ and Se$_{78-x}$Te$_{20}$Sn$_2$Zn$_x$ (where $x = 0, 2, 4, 6$) alloys are the subject of micro-indentation tests in this work. We have utilized both micro-indentation and optical microscopic methods to determine Vickers hardness. Thermal glass transition phenomena have been identified through DSC techniques. The modulus of elasticity (E), an essential mechanical property, has been evaluated using established empirical equations. Further, we have studied other mechanical parameters [e.g., minimal micro-void formation energy (Eh), glass's fragility index (m), micro-void volume (Vh), etc.] and the covalent character of the glassy system. Additionally, various physical parameters, including density, molar volume, and compactness, have also been determined

Physical Characterization and Crystallization Kinetics of Amorphous BiSe Chalcogenide Glasses

The influence of Bi concentration on the thermal parameters viz temperatures of glass transition (Tgl) and crystallization (Tpc) of binary BixSe100-x glasses were studied experimentally. The activation energy of glass transition (EGl) has been estimated as the averaged value deduced based on Kissenger's relationship and its approximation. On the other hand, Afify and Aly methods help one to estimate the crystallization activation energy (Epc), the frequency factor (k0) and the order of reaction (n) with no approximation. The observed increase in EGl and Epc values resulted from increasing both Tgl and Tpc with increasing of the Bi content. The Lasocka relationship can describe the heating rate dependence of Tgl and Tpc. A good correlation between Tgl and Tpc was investigated. The attained results were discussed according to the distribution of the chemical bonds, the main coordination number (Nr), average heats of atomization (Hs), the mean bond energy (Es), the cohesive energy (CE), and the overall average bond energy (<E>) for BixSe100-x glasses. © 2021 The Author(s).The work of Antoaneta Ene and the APC were financed by Dunarea de Jos University of Galati, Romania, through the internal grant with contract no. RF 3621/2021.The authors express their gratitude to the Deanship of Scientific Research, Majmaah University, Saudi Arabia, for funding this research work under Grant (R-2021-303)

Synthesis and theoretical characterization of ternary Cux(Ge30Se70)100−x glasses

The Cux(Ge30Se70)100−x (0 ≤ x ≤ 12 at.%) chalcogenide alloys have been synthesized by the conventional melt quenching technique. The physical properties such as the mean coordination number, density, molar volume, compactness, overall bond energy, and cohesive energy were estimated for the Cu doped Ge-Se glassy alloys. The chemical bond approach (CBA) was used to predict the type and proportion of the formed bonds in the studied glasses. Subsequently, several structural and physical properties have been estimated. The results show that the studied glasses are rigidly connected, having an average coordination number increase from 2.6 to 2.77. The density and glass compactness show an increase with the Cu content, whereas the main atomic volume decreases. The cohesive energy and the heat of atomization show a similar behavior trend with the enhancement of Cu % in the Ge-Se binary glasses. The optical band gap was estimated theoretically compared with the previously published experimental values for the Cux(Ge30Se70)100−x (0 ≤ x ≤ 12 at.%) thin films. The covalency parameter >91% for the studied glasses so that the compositions may be used as a stable glass former. Furthermore, the mechanical properties as the elastic bulk modulus, Poisson's ratio, Young's modulus, micro-hardness, and Debye temperature were investigated as a function of the Cu content. © 2021The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University , Saudi Arabia, for funding this work through the General Research Project Under Grant Number ( GRP/146/42 )

EPIDEMIOLOGY OF MALARIA IN THE STATE OF QATAR, 2008-2015

Background and Objectives Imported malaria poses a serious public health problem in Qatar because its population is “naïve” to such infection; where local transmission might lead to serious life-threatening infection and might even trigger epidemics. Methods This study is a retrospective review of the imported malaria cases in Qatar reported by the malaria surveillance program at the Ministry of Public Health (MoPH), during the period between January 2008 and December 2015. All cases were imported and underwent parasitological confirmation through microscopy. Results A total of 4092 malaria cases were reported during 2008-2015 in Qatar. The demographic features of the imported cases show that the majority of cases were males (93%), non-Qatari(99.6%), and aged 15 to 44 years(82.1%). Moreover, P. vivax was found to be the main etiologic agent accounting for more than three-quarters (78.7%) of the imported cases. In addition, almost a third (33.1%) of the cases were reported during the months of July, August, and September. Conclusions Imported malaria in Qatar has witnessed an increase during the past 7 years, despite a long period of constant reduction; where the people most affected were adult male migrants from endemic countries. Many challenges need to be overcome to prevent the reintroduction of malaria into the country

Empowering Qualitative Research Methods in Education with Artificial Intelligence

Artificial Intelligence is one of the fastest growing disciplines, disrupting many sectors. Originally mainly for computer scientists and engineers, it has been expanding its horizons and empowering many other disciplines contributing to the development of many novel applications in many sectors. These include medicine and health care, business and finance, psychology and neuroscience, physics and biology to mention a few. However, one of the disciplines in which artificial intelligence has not been fully explored and exploited yet is education. In this discipline, many research methods are employed by scholars, lecturers and practitioners to investigate the impact of different instructional approaches on learning and to understand the ways skills and knowledge are acquired by learners. One of these is qualitative research, a scientific method grounded in observations that manipulates and analyses non-numerical data. It focuses on seeking answers to why and how a particular observed phenomenon occurs rather than on its occurrences. This study aims to explore and discuss the impact of artificial intelligence on qualitative research methods. In particular, it focuses on how artificial intelligence have empowered qualitative research methods so far, and how it can be used in education for enhancing teaching and learning

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely