Designing A Calibration Set in Spectral Space for Efficient Development of An NIR Method For Tablet Analysis

Designing a calibration set is the first step in developing a spectroscopic calibration method for quantitative analysis of pharmaceutical tablets. This step is critical because successful model development depends on the suitability of the calibration data. For spectroscopic-based methods, traditional concentration based techniques for designing calibration sets are prone to have redundant information while simultaneously lacking necessary information for a successful calibration model. The traditional method also follows the same design approach for different spectroscopic techniques and different formulations, thereby lacks the optimizing capability to be technique and formulation specific. A method for designing a calibration set in the Near Infrared (NIR) spectral space was developed for quantitative analysis of tablets. The pure component NIR spectra of a tablet formulation were used to define the spectral space of that formulation. This method minimizes sample requirements to provide an efficient means for developing multivariate spectroscopic calibration. Multiple comparative studies were conducted between commonly employed experimental design approaches to calibration development and the newly developed spectral space based technique. The comparisons were conducted on single API (Active Pharmaceutical Ingredient) and multiple API formulation to quantify model drugs using NIR spectroscopy. Partial least squares (PLS) models were developed from respective calibration designs. Model performance was comprehensively assessed based on the ability to predict API concentrations in independent prediction sets. Similar prediction performance was achieved using the smaller calibration set designed in spectral space, compared to the traditionally designed large calibration sets. An improved prediction performance was observed for the spectrally designed calibration sets compared to the traditionally designed calibration sets of equal sizes. Spectral space was also used to incorporate physico-chemical information into the calibration design to provide an efficient means of developing robust calibration model. Robust calibration model is critical to ensure consistent model performance during model lifecycle. A weight coefficient based technique was developed for selecting loading vector in PLS model to aid in building robust calibration model. It was also demonstrated that the optimal structures of calibration sets are different between NIR and Raman spectroscopy for the same tablet formulation. The optimum calibration structures are also different between two APIs for the same spectroscopic technique, indicating the criticality of the calibration design to be formulation and technique specific. This study demonstrates that a calibration set designed in spectral space provides an efficient means of developing spectroscopic multivariate calibration for tablet analysis. This study also provides opportunity to design formulation and technique specific calibration sets to optimize calibration capability

Effects of substituting plant-based protein sources for fish meal in the diet of Nile Tilapia (Oreochromis niloticus)

The purpose of this study was to evaluate the nutritional adequacy and suitability of rice polish and mustard oil cake as protein sources in the diet of Nile Tilapia (Oreochromis niloticus). To assess the growth performance and feed utilization of Nile Tilapia, three diets containing rice polish (0, 8, and 16%) and mustard oil cake (8, 16, and 24%) were formulated and fed to the fish over a period of 60 days. According to the findings, the growth performance tended to decline as the levels of rice polish and mustard oil cake increased. The control diet (30% Fish meal) resulted in the highest weight gain (373.79±49.78%), whereas the diet (20% Fish meal) resulted in the least weight gain (341.24±27.23%). The specific growth rate (SGR) followed the same pattern, and there were no statistically significant differences in SGR between diets (p>0.05). At the end of this trial, the feed intake (FI) of the various diets ranged between 32.37 g and 37.78 g per fish. Although feed conversion ratio (FCR) and protein efficiency ratio (PER) were not significantly different among diets (p>0.05), feed intake decreased as the incorporation of rice polish increased

Alternative protein sources as a replacement of fish meal in the diet of Oreochromis niloticus: A review

The farming of Tilapia (Oreochromis niloticus) has conquered the significant popularity in tropical and subtropical regions, primarily due to its remarkable faster growth rate. The growth performance of the species makes it an attractive choice for many fish farmers. Additionally, Tilapia exhibits a commendable resilience to disease, further enhancing its appeal as a farming option. Furthermore, the low trophic feeding levels of Tilapia contribute to its desirability, making it an efficient and sustainable choice for nutrition-conscious individuals. Due to the increasing prevalence of aquaculture production, there has been a significant surge in the demand for fishmeal. This particular protein source has relished the widespread popularity for many years and its demand has now more than doubled. The current growth rate of the aquaculture industry is outpacing the available fishmeal supplies, which are insufficient to meet the demand. According to scientific studies, it has been found that fishmeal can be effectively replaced with alternative sources without compromising the overall performance of the fish. This article presents a compelling case for the practicality of replacing fishmeal with alternative protein sources in the diet of Tilapia. These alternatives include terrestrial animal by-products, oilseed plants, single-cell proteins, and protein-rich plant derivatives. In order to mitigate the environmental impact of the fishmeal industry, it is crucial to implement measures that can effectively address this concern. Moreover, it is crucial to highlight the significance of these sources from a nutritional perspective. The blood meal, meat and bone meal are highly beneficial options for incorporating essential amino acids and protein into the diet of Tilapia. These alternatives offer a rich source of nutrients that can effectively replace fishmeal. The minerals instead of amino acids could improve plant protein performance. Due to inconsistent findings, aquatic plants and single-cell proteins in Tilapia meals should be carefully considered. Fishmeal replacers need biological and economic analyses. Long-term evaluations should be done in practical culture systems rather than labs. In conclusion, it is imperative for Tilapia producers to contemplate the utilization of alternative dietary sources, as extensive research has demonstrated the scientific feasibility of substituting the fishmeal in the diet of Tilapia

Different stocking densities and species combinations effects the growth and production in carp polyculture

A comparative experiment was undertaken to assess the effectiveness of different carp species i.e., Rohu (Labeo rohita), Catla (Catla catla), Mrigal (Cirrhinus cirrhosus), and Silver Carp (Hypophthalmicthys molitrix) with variable stocking densities. Three treatments each with three replicates were maintained and the stocking densities of carps were 40, 80, and 120 fish/decimal in T1, T2, and T3, respectively. The stocking ratio of Rohu, Catla, Mrigal, and Silver Carp was 2:1:2:1. The experimental diet included rice bran (25%), wheat bran (25%), fish meal (25%), and mustard oil cake (25%), with a total protein content of 28%. This dietary supplement was administered twice daily. The fish were supplemented with 5% of their body weight for the first month, 4.5% for the next three months, and 2% for the final two months. The water quality parameters i.e., pH, temperature, dissolved oxygen and transparency were measured every 14 days interval. In T1, Silver Carp obtained the highest weight (188.86±17.86g) followed by Mrigal (106.78±14.23g), Catla (74.0±3.80g), and Rohu (67.72±6.03g). In T1, Silver Carp also attained the highest length at 26.33±0.63 cm, followed by Catla at 14.40±2.10 cm, Mrigal at 14.09±0.89 cm, and Rohu at 14.07±0.59 cm, respectively. Nevertheless, both weight gain and length gain were lowest for all species in T3. The highest SGR% was found in T1 for Silver Carp (3.22±0.06), whereas the lowest SGR% was found in T3 for Catla (1.69±0.06). In addition, T2  yielded the highest production (3090.91±119.57 kg/ha), followed by T3 (2949.80±137.67 kg/ha) and T1 (2946.21± 129.00 kg/ha). The experimental findings suggest that, the stocking density of 80 fingerlings/decimal (T2) yielded the highest production in carp polyculture

Non-Performing Loans: A Catastrophic Phenomena in Banking Sector of Bangladesh

Nonperforming loan (NPL) is one of the most cataclysmic phenomena for the entire banking industry in Bangladesh. NPLs in the banking sector have experienced a monstrous escalation of 300% in the last decade and statistically this figure is more than 1000 billion of Bangladeshi Taka (BDT). Even though international standards of loan classification and provisioning system is being adopted, the management of NPL is found unproductive. Fundamentally, deficiency of good governance, weak supervision, corruption, political interference in approving loans, culture of impunity and professional ineptness of bankers to deal with the pressing issue have played an instrumental role for the swift upsurge of NPLs. Pertaining to preventive measures, prominence needs to be placed on credit screening, loan surveillance, stringent law enforcement, centralized loan authorization system, strong monetary policy and strong loan review functionaries. Therefore, this study has emphasized on the challenges of NPL, evocative ways for improving the debt recovery environment and cracking the NPL problems in order to safeguard a sustainable banking sector of the country.Keywords: non-performing loan, loan classifications, provisioning, good governance, sustainable bankingDOI: 10.7176/EJBM/12-27-14Publication date:September 30th 202

Production of He-4 and (4) in Pb-Pb collisions at root(NN)-N-S=2.76 TeV at the LHC

Results on the production of He-4 and (4) nuclei in Pb-Pb collisions at root(NN)-N-S = 2.76 TeV in the rapidity range vertical bar y vertical bar <1, using the ALICE detector, are presented in this paper. The rapidity densities corresponding to 0-10% central events are found to be dN/dy4(He) = (0.8 +/- 0.4 (stat) +/- 0.3 (syst)) x 10(-6) and dN/dy4 = (1.1 +/- 0.4 (stat) +/- 0.2 (syst)) x 10(-6), respectively. This is in agreement with the statistical thermal model expectation assuming the same chemical freeze-out temperature (T-chem = 156 MeV) as for light hadrons. The measured ratio of (4)/He-4 is 1.4 +/- 0.8 (stat) +/- 0.5 (syst). (C) 2018 Published by Elsevier B.V.Peer reviewe

Leveraging Sensor Fusion and Sensor-Body Position for Activity Recognition for Wearable Mobile Technologies

Smart devices like smartphones and smartwatches have made this world smarter. These wearable devices are created through complex research methodologies to make them more usable and interactive with its user. Various interactive mobile applications such as augmented reality (AR), virtual reality (VR) or mixed reality (MR) applications solely depend on the in-built sensors of the smart devices. A lot of facilities can be taken from these devices with sensors such as accelerometer and gyroscope. Different physical activities such as walking, jogging, sitting, etc., can be important for analysis like health state prediction and duration of exercise by using those sensors based on artificial intelligence. In this paper, we have implemented machine learning and deep learning algorithms to detect and recognize eight activities namely, walking, jogging, standing, walking upstairs, walking downstairs, sitting, sitting-in-a-car and cycling; with a maximum of 99.3% accuracy. A few activities are almost similar in action, such as sitting and sitting-in-a-car, but difficult to distinguish; which makes it more challenging to predict tasks. In this paper, we have hypothesized that with more sensors (sensor fusion) and data collection points (sensor-body positions) a wide range of activities can be recognized and the recognition accuracies can be increased. Finally, we showed that the combination of all the sensors data of both pocket/waist and wrist can be used to recognize a wide range of activities accurately. The possibility of using the proposed methodologies for futuristic mobile technologies is quite significant. The adaptation of most recent deep learning algorithms such as convolutional neural network (CNN) and bi-directional Long Short Time Memory (Bi-LSTM) demonstrated high credibility of the methods presented as experimentation

Double burden of malnutrition at household level: A comparative study among Bangladesh, Nepal, Pakistan, and Myanmar.

BackgroundThe coexistence of overweight mother and stunted child at the same household is a type of Double Burden of Malnutrition at Household Level (DBMHL). This particular public health concern is now emerging at an alarming rate among most of the South Asian and its neighboring lower-and-middle income countries which are going through nutritional transition. This study has examined the prevalence rate and the risk factors of DBMHL along with the socio-economic inequality in DBMHL among Bangladesh, Nepal, Pakistan, and Myanmar.MethodsLatest Demographic and Health Survey datasets were used in this study. To identify the significant association of DBMHL with socio-demographic characteristics, a multivariate technique named as logistic regression model, and for measuring socio-economic inequalities in DBMHL prevalence, relative index of inequality (RII) and slope index of inequality (SII) were used.ResultsThe prevalence rates of DBMHL were 4.10% (urban: 5.57%, rural: 3.51%), 1.54% (urban: 1.63%, rural: 1.42%), 3.93% (urban: 5.62%, rural: 3.20%), and 5.54% (urban: 6.16%, rural: 5.33%) respectively in Bangladesh, Nepal, Pakistan, and Myanmar. The risk ratios (RR) obtained from RII for Bangladesh, Nepal, Pakistan and Myanmar were 1.25, 1.25, 1.14, and 1.09, respectively, and β coefficient from SII were 0.01, 0.004, 0.005, and 0.006 unit respectively. In addition to not breastfeeding [Bangladesh (AOR: 1.55; 95% CI: 1.11-2.15), Myanmar (AOR: 1.74; 95% CI: 1.02-2.95)], respondent's older age (in Bangladesh, Nepal, and Myanmar), child's older age (in Pakistan and Myanmar), and middle and rich groups of wealth-index (in Bangladesh and Pakistan) were strong risk factors for DBMHL. On the other hand, female child [Nepal (AOR: 0.50; 95% CI: 0.26-0.95), Pakistan (AOR: 0.58; 95% CI: 0.41-0.84)], higher education [in Pakistan], respondent not participated in decision making [in Bangladesh and Nepal] and media access [Nepal (AOR: 0.44; 95% CI: 0.20-0.98)] had negative association with DBMHL.ConclusionThe DBMHL persists in all selected countries, with a higher prevalence in urban areas than in rural areas. In order to control the higher prevalence of DBMHL in urban areas, respective countries need urgent implementation of multisectoral actions through effective policies and empowering local communities