Turbidimeters operate based on the optical phenomena that occur when incident light through water body is scattered by the existence of foreign particles which are suspended within it. This review paper elaborates on the standards and factors that may influence the measurement of turbidity. The discussion also focuses on the optical fiber sensor technologies that have been applied within the lab and field environment and have been implemented in the measurement of water turbidity and concentration of particles. This paper also discusses and compares results from three different turbidimeter designs that use various optical components. Mohd Zubir and Bashah and Daraigan have introduced a design which has simple configurations. Omar and MatJafri, on the other hand, have established a new turbidimeter design that makes use of optical fiber cable as the light transferring medium. The application of fiber optic cable to the turbidimeter will present a flexible measurement technique, allowing measurements to be made online. Scattered light measurement through optical fiber cable requires a highly sensitive detector to interpret the scattered light signal. This has made the optical fiber system have higher sensitivity in measuring turbidity compared to the other two simple turbidimeters presented in this paper. Fiber optic sensors provide the potential for increased sensitivity over large concentration ranges. However, many challenges must be examined to develop sensors that can collect reliable turbidity measurements in situ.

Due to resistance and scarcity of treatment options, nosocomial Acinetobacter baumannii infections are associated with significant fatality rates. We investigated the factors contributing to infection-related deaths to develop tailored stewardship interventions that could reduce these high mortality rates. We reviewed the medical records of adult inpatients with A. baumannii infections over two years. Patient demographics and clinical data were collected and statistically analyzed. The study included 321 patients with positive A. baumannii microbiological cultures, with respiratory infections accounting for 58.6%, soft tissues 29.3%, bacteremia 8.6%, urine 2.1%, and others 1.4%. The study population’s median (IQR) age was 62.6 (38.9–94.9) years, and hospital stay was 20 (9.5–40) days. Statistical analysis revealed that various risk factors contribute significantly to high in-hospital all-cause mortality (44%), as well as 14-day and 28-day mortality rates. Deaths increased by a factor of 1.04 with every additional year of age (p = 0.000), admission to the critical care unit (p = 0.000, OR: 2.86), and patients admitted with an infectious diagnosis had nearly three times the mortality rate as those admitted with other diagnoses (p = 0.000, OR: 3.12). Male gender (p < 0.001, OR: 2.14), any comorbid conditions (p = 0.000, OR: 5.29), prolonged hospitalization (>7 days) (p = 0.023, OR: 1.98), and hospital acquisition of infection (p = 0.027, OR: 1.68) were among the most significant predictors of mortality. All variables were investigated for their impact on all-cause, 14-day, and 28-day mortality rates. Improving multidisciplinary infection control practices, regular disinfection of patient care equipment, and optimal intubation practice that avoids unnecessary intubation are necessary interventions to reduce infection-related mortality rates. Better antibiotic selection and de-escalation, shorter hospital stays whenever possible, prompt medical stabilization of comorbid conditions, and fewer unnecessary admissions to critical care units will all lead to improved outcomes.

Numerous instruments such as ionization chambers, hand-held and pocket dosimeters of various types, film badges, thermoluminescent dosimeters (TLDs) and optically stimulated luminescence dosimeters (OSLDs) are used to measure and monitor radiation in medical applications. Of recent, photonic devices have also been adopted. This article evaluates recent research and advancements in the applications of photonic devices in medical radiation detection primarily focusing on four types; photodiodes – including light-emitting diodes (LEDs), phototransistors—including metal oxide semiconductor field effect transistors (MOSFETs), photovoltaic sensors/solar cells, and charge coupled devices/charge metal oxide semiconductors (CCD/CMOS) cameras. A comprehensive analysis of the operating principles and recent technologies of these devices is performed. Further, critical evaluation and comparison of their benefits and limitations as dosimeters is done based on the available studies. Common factors barring photonic devices from being used as radiation detectors are also discussed; with suggestions on possible solutions to overcome these barriers. Finally, the potentials of these devices and the challenges of realizing their applications as quintessential dosimeters are highlighted for future research and improvements.

The measurement of sugars is one of the important methodologies in determining fruits’ intrinsic quality, which can be collectively measured as soluble solids content (SSC) in the unit of ^oBrix. For fruits, ^oBrix is the summation of the grams of sucrose, glucose, fructose, vitamins, minerals, amino acids, proteins, hormones, and other soluble solids over 100 g of the particular fruit sample. Although lower range of near infrared (NIR) between 700 to 1100 nm is popularly being used in reliably determining soluble solids content of fruits, profiling of optical response of water-sugar concentration at this range of wavelength is not widely available. Thus, the purpose of this work is to optically profile water-sugar solutions and identify peak wavelengths in quantifying sugar concentration. Spectroscopic measurement in this work was conducted on the range of wavelength between 360 and 1100 nm. Wavelengths within 959–961 nm are identified as producing the highest coefficient of determination, R², between absorbance and aqueous sugar concentration (^oBrix). Combination of NIR wavelengths ( , 830, 909–915, 960, and 965 nm) within C-H and O-H bands can reliably quantify individual sugars, namely sucrose (calibration: R² = 0.992, RMSEC = 0.907; prediction: R² = 0.985, RMSEP = 1.221), glucose (calibration: R² = 0.998, RMSEC = 0.426; prediction: R² = 0.997, RMSEP = 0.540), and fructose (calibration: R² = 0.996, RMSEC = 0.617; prediction: R² = 0.995, RMSEP = 0.631).