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The salinity of seawater is of fundamental importance in climate studies, and the measurement of the variable requires high accuracy and precision in order to be able to resolve its typically small variations in the oceans with depth and over long-time scales. This is currently only possible through the measurement of conductivity, which has led to the definition of a Practical Salinity scale. However, seawater is also composed of a large number of non-conducting substances that constitute salinity anomalies. Differences of the ratios of the constituents of sea salt from the Reference Composition may also change salinity anomalies. The establishment of formulae for calculating the thermodynamic properties of seawater has led to the definition of the concept of Absolute Salinity ( S A ), which includes such anomalies and is similar in approach to the notion of density. Although the routine in situ measurement of S A is still a huge challenge, numerous developments based on acoustic techniques, but above all, refractometry, interferometry or complex fiber optic assemblies, have been tested for this purpose. The development of monolithic components has also been initiated. The measurement of the refractive index by these techniques has the advantage of taking into account all the dissolved substances in seawater. This paper reviews the difficulties encountered in establishing theoretical or empirical relations between S A and the sound velocity, the refractive index or the density, and discusses the latest and most promising developments in S A measurement with a particular focus on in situ applications.

This study investigates the effectiveness of the Firefly Optimizer (FFA), Grey Wolf Optimizer (GWO), and Moth Flame Optimizer (MFO) metaheuristic algorithms in estimating the kinetic parameters of a single-step coal pyrolysis model. By examining the effects of the algorithmic configuration, the initial parameter estimates, and the search space size on the efficacy and efficiency of the optimization run, the research seeks to encourage the qualified engineering application of these algorithms in the field of pyrolysis modeling. Four critical analyses were conducted: convergence efficiency, robustness and repeatability, parameter tuning, and performance on noisy data. MFO and GWO had comparable fitness scores of 1.05×10-4 and 1.04×10-4 respectively in the optimisation run analysis, while FireFly Algorithm (FFA) fell behind with a score of 1.09×10-4. Regarding the calculation time, FFA showed better results than other optimizers with an execution time of 113.75 seconds. MFO showed initial promise in convergence analysis with speedy convergence, whereas GWO progressively enhanced its solutions. Additionally, GWO was shown to be the most dependable algorithm with the lowest values for average fitness score and execution time at 1.07×10-4 and 38.86 seconds. The combined values of standard deviation in fitness value and execution time for GWO were 1.07×10-6 and 0.35 indicating its robustness towards initial parameters. Similar to this, investigations on repeatability emphasized the reliability of the GWO method. Further, the parameter tuning assessments supported the balanced performance of GWO, and the studies of noise handling discovered GWO to be the most robust to noisy data. Overall, GWO is recommended as a one-stop average solution for the general engineered application; however, algorithm choice hinges on the specific requirement.

We provide new estimates on size, composition and distribution of human resource for health in India and compare with the health workers population ratio as recommended by the WHO. We also estimate size of non-health workers engaged in health sector and the size of technically qualified health professionals who are not a part of the health workforce. Nationally representative cross-section household survey and review of published documents by the Central Bureau of Health Intelligence. National. Head of household/key informant in a sample of 101 724 households. Not applicable. The primary outcome was the number and density of health workers,and the secondary outcome was the percentage of health workers who are technically qualified and the percentage of individuals technically qualified and not in workforce. The total size of health workforce estimated from the National Sample Survey (NSS) data is 3.8 million as of January 2016, which is about 1.2 million less than the total number of health professionals registered with different councils and associations. The density of doctors and nurses and midwives per 10 000 population is 20.6 according to the NSS and 26.7 based on the registry data. Health workforce density in rural India and states in eastern India is lower than the WHO minimum threshold of 22.8 per 10 000 population. More than 80% of doctors and 70% of nurses and midwives are employed in the private sector. Approximately 25% of the currently working health professionals do not have the required qualifications as laid down by professional councils, while 20% of adequately qualified doctors are not in the current workforce. Distribution and qualification of health professionals are serious problems in India when compared with the overall size of the health workers. Policy should focus on enhancing the quality of health workers and mainstreaming professionally qualified persons into the health workforce.

Characterizing complex fluvial-deltaic deposits is a challenging task for finding hydrocarbon discoveries. We described a methodology for predicting the hydrocarbon zones from complex well-log and prestack seismic data. In this current study, data analysis involves an integrated framework based on Simultaneous prestack seismic inversion (SPSI), target correlation coefficient analysis (TCCA), Poisson impedance inversion, and non-parametric statistical analysis, and Bayesian classification. First, seismic elastic attributes from prestack seismic data were estimated. They can provide the spatial distribution of petrophysical properties of seismic data. Then target correlation coefficient analysis (TCCA) was estimated roration factor “c” from well-log data. Using the seismic elastic attributes and rotation factor “c”, Poisson impedance inversion was performed to predict the Poisson impedance volume. Finally, Bayesian classification integrated the Poisson impedance volume with non-parametric probabilistic density functions (PDFs) to estimate the spatial distribution of lithofacies. Despite complex characteristics in the elastic properties, the current study successfully delineated the complex fluvial-details deposits. These results were verified with conventional findings through numerical analysis.

18 English-language studies published between January 2003 and April 2013 were retrieved from the MEDLINE database using the key word ‘total wrist arthroplasty’. In most studies, total wrist arthroplasty achieved improvement in pain and function over time. In a meta-analysis, the revision rate was 17% for third-generation implants. The survival rate was 92% for fourth-generation implants at 4 years. Complication rates ranged from 0% to 100% for third-generation implants and from 6% to 47% for fourth-generation implants. Results of total wrist arthroplasty vary greatly; longer-term studies are needed to determine its cost-effectiveness.

It is paramount that solutions to questions of energy security for a developing nation be addressed through its internal resources. India, endowed with 23.8 billion tons of deep un-minable lignite, faces the challenge of economically sustainable extraction. This study presents a comprehensive assessment of lignite's suitability for underground coal gasification (UCG) compared to bituminous coal. Employing a multi-dimensional approach, combining single-step and distributed activation energy model of pyrolysis kinetic modeling with extensive physicochemical analysis (proximate and ultimate analyses, FTIR, SEM–EDX, XRD), revealed that lignite has a lower activation energy making it suitable for UCG. This finding, highlighted by kinetic modeling, is substantiated by the lignite’s structural properties as identified in physicochemical analysis. This study leverages machine learning for higher heating value prediction, finding long short-term memory as the most effective model compared to five other models based on the R 2 score and error values. Additionally, an XGBoost algorithm-based model predicts syngas heating value and yield while showcasing the application of machine learning in enhancing energy prediction accuracy. The economic analysis, applied for a 50 MW power plant framework, determines the unit costs for syngas and electricity production to be 7.49 and 6.71 $/GJ and 53.68 and 59.93 $/MWh for the samples of lignite and bituminous coal, respectively. The sensitivity analysis revealed that the energy content in syngas is the most significant parameter. These comprehensive findings validate lignite's potential for energy production in India, offering insights for similar resource optimization in other developing countries.

The Canadian League Against Epilepsy initiated a virtual epilepsy education program, conducting 29 webinars from March 2021 to September 2023. We report our experience, with the goal to inspire other groups to develop inclusive, equitable, and free educational spaces with a worldwide reach. Monthly sessions drew a median attendance of 118 participants, predominantly Canadian but also international, including physicians (58.9%) and trainees (22.8%). Post-webinar surveys (average 40% response rate) noted high satisfaction, a strong inclination to recommend the sessions, and an interest in clinical case-based topics. We plan to consider integrating a self-assessment section evaluating knowledge gained after each seminar.

B-cell acute lymphoblastic leukemia (ALL) is characterized by accumulation of immature hematopoietic cells in the bone marrow, a well-established sanctuary site for leukemic cell survival during treatment. While standard of care treatment results in remission in most patients, a small population of patients will relapse, due to the presence of minimal residual disease (MRD) consisting of dormant, chemotherapy-resistant tumor cells. To interrogate this clinically relevant population of treatment refractory cells, we developed an in vitro cell model in which human ALL cells are grown in co-culture with human derived bone marrow stromal cells or osteoblasts. Within this co-culture, tumor cells are found in suspension, lightly attached to the top of the adherent cells, or buried under the adherent cells in a population that is phase dim (PD) by light microscopy. PD cells are dormant and chemotherapy-resistant, consistent with the population of cells that underlies MRD. In the current study, we characterized the transcriptional signature of PD cells by RNA-Seq, and these data were compared to a published expression data set derived from human MRD B-cell ALL patients. Our comparative analyses revealed that the PD cell population is markedly similar to the MRD expression patterns from the primary cells isolated from patients. We further identified genes and key signaling pathways that are common between the PD tumor cells from co-culture and patient derived MRD cells as potential therapeutic targets for future studies.

Background Upper tract urothelial carcinoma (UTUC) is a rare urological cancer that is still an important public health concern in many areas around the world. Although UTUC has been linked to a number of risk factors, to our knowledge no systematic review has been published on the overall incidence and prevalence of de-novo UTUC. This review aimed to examine the global epidemiology of UTUC to provide clinicians and public health specialists a better understanding of UTUC. Methods A systematic search was conducted on MEDLINE, Embase, and the Web of Science using a detailed search strategy. Observational epidemiological studies describing the incidence and prevalence of de-novo UTUC in adults were included, and the Joanna Briggs Institute checklist was used for critical appraisal and data extraction of the studies selected. Results The systematic search identified 3506 papers, of which 59 papers were included for qualitative synthesis. The studies selected included data ranging from the years 1943 to 2018. A comprehensive qualitative synthesis of the data was performed. UTUC incidence generally varied according to age (higher with increasing age), sex (unclear), race (unclear), calendar time (increased, stable, or decreased according to region), geographical region (higher in Asian countries), occupation (higher in seamen and printers), and other population characteristics. Prevalence was only reported by one study, which showed UTUC to have the highest incidence of the rare urogenital cancers in Europe. Conclusion This systematic review highlights an increased incidence of UTUC in certain groups, including increasing age and certain occupations such as seamen. The incidence of UTUC also varies between certain geographical regions. The trend of UTUC incidence for sex, race, and calendar time is less clear due to a wide variety of metrics used by the studies identified. More studies are also required on the prevalence of UTUC to understand its disease burden. Trial registration This review was registered on PROSPERO (registration number CRD42019134255).

Olfactory Reference Disorder (ORD) is a known clinical entity for several decades; however, it is only in ICD 11 that it has found its niche. Long considered a delusional disorder, it is currently classified as an obsessive–compulsive (OC) spectrum disorder. ORD is characterised by an erroneous conviction that the body is emitting an unpleasant smell. Patients harbour referential thinking, practise rituals to eliminate or mask the perceived odour, and avoid social interactions. While the conviction can be at a delusional level in some patients, the preoccupation has an obsessive quality in others. The level of insight can be varied. Patients present to mental health settings after traversing a long pathway of care comprising of various specialists. Medical and psychiatric conditions which can present with ORD-like symptoms need to be ruled out. Establishing a therapeutic alliance is the first step in management. There are no randomised controlled trials comparing treatment options in ORD. Antidepressants, antipsychotics, and their combinations have been used with varying degrees of success, in addition to psychotherapy and electroconvulsive therapy. Data on prognosis is limited.