50 research outputs found
Asleep at the wheel: the real interest rate experience in Australia
A re-thinking and clear understanding of the factors underlying a country's balance of trade position is needed as the global trade regime becomes more liberalized. The relationship between the overall trade balance and its determinants as propounded in the standard models may not necessarily be the same with the bilateral trade balances. This study has developed a model of bilateral trade balance that captures the effects of all factors influencing trade balance as suggested by elasticity, absorption, and monetary approaches and the popular Gravity Model with some extensions. Specifically, the present paper postulates that the relative factors determine the trading pattern, and hence the trade balance of a country in bilateral trade with partners while in the earlier models absolute factors determine the trade balance,. Using standard panel data techniques the model is empirically tested and the results show significant effects of all the relative factors on the bilateral trade balance of Bangladesh in trading with her partners. The robustness check of the model ensures the validity of the specification.Trade Balance, Panel Data
Trade openness and inflation: A test of Romer hypothesis for Bangladesh
An important prediction found in international trade is that Trade openness can affect inflation. The trade openness or trade liberalization is associated with declining prices, that is, there is negative relation between inflation and trade openness. In line with this view, Romer (1993) postulates the hypothesis that inflation is lower in small and open economies. The objective of this paper is to explore the relationship between trade openness and inflation for the small economy Bangladesh using data over 1976 -2010 period. For this purpose, Cointegration Approach and a Vector Error Correction Model (VECM) have been used. Empirical results show that there is a significant negative long-run relationship between inflation and trade openness, which confirms the existence of Romerâs hypothesis in Bangladesh
Trade openness and inflation: A test of Romer hypothesis for Bangladesh
An important prediction found in international trade is that Trade openness can affect inflation. The trade openness or trade liberalization is associated with declining prices, that is, there is negative relation between inflation and trade openness. In line with this view, Romer (1993) postulates the hypothesis that inflation is lower in small and open economies. The objective of this paper is to explore the relationship between trade openness and inflation for the small economy Bangladesh using data over 1976 -2010 period. For this purpose, Cointegration Approach and a Vector Error Correction Model (VECM) have been used. Empirical results show that there is a significant negative long-run relationship between inflation and trade openness, which confirms the existence of Romerâs hypothesis in Bangladesh
Antidiabetic activity of aqueous extract of Sigesbeckia orientalis (St. Paulâs Wort) in alloxan-induced diabetes model
The current study evaluated antidiabetic and antihyperlipidemic activities of aqueous extract of Sigesbeckia orientalis L. (St. Paulâs Wort) (AESO) in an alloxan-induced diabetic rat model. Following OECD guidelines safe doses of AESO were assessed in rats for the main study. Serum/bood glucose, α-amylase, and lipids levels and histopathological evaluations were conducted to assess antidiabetic and associated antihyperlipidemic efficacies of AESO. AESO was found to be safe up to the dose of 2000 mg/kg. Significant (p < 0.05) reduction in glucose and lipids (total cholesterol, triglycerides, lowâdensity lipoproteins) levels was observed in AESO treatment groups. Serum α-amylase, highâdensity lipoproteins, and total body weight was increased significantly (p < 0.05) in diabetic rats treated with AESO. Histopathological data showed improvement in hepatocyte and pancreatic ÎČ-cells islets architecture. HPLC analysis identified quercetin, gallic acid, vanillic acid, p-coumaric acid, m-coumaric acid and cinnamic acid in AESO which are suggested to be responsible for observed antihyperglycemic and antihyperlipidemic attributes. Further studies to standardise the extract and evaluation of safety profile in long-term toxicity studies are recommended for safe and effective antidiabetic nutraceuticals development
A Novel ESRRB Deletion Is a Rare Cause of Autosomal Recessive Nonsyndromic Hearing Impairment among Pakistani Families
Mutations in the estrogen-related receptor beta (ESRRB) gene is the underlying cause of autosomal recessive nonsyndromic hearing impairment (ARNSHI) due to the DFNB35 locus which maps to 14q24.3. A genome scan of a large consanguineous Pakistani pedigree with ARNSHI established linkage with a maximum multipoint LOD score of 4.2 to the 14q24 region and the region of homozygosity contained the ESRRB gene. Sequencing of the ESRRB gene using DNA samples from hearing-impaired family members uncovered a novel three-nucleotide deletion c.1018_1020delGAG (p.Glu340del). The deletion segregates with hearing impairment in the pedigree and was not observed in 500 control chromosomes. The deletion of glutamic acid residue occurs in the ligand-binding domain of ESRRB protein. It is expected that the deletion affects the ligand-binding activity of the domain in ESRRB, which leads to the ARNSHI
Predicting Breast Cancer Leveraging Supervised Machine Learning Techniques
Breast cancer is one of the leading causes of increasing deaths in women worldwide. The complex nature (microcalcification and masses) of breast cancer cells makes it quite difficult for radiologists to diagnose it properly. Subsequently, various computer-aided diagnosis (CAD) systems have previously been developed and are being used to aid radiologists in the diagnosis of cancer cells. However, due to intrinsic risks associated with the delayed and/or incorrect diagnosis, it is indispensable to improve the developed diagnostic systems. In this regard, machine learning has recently been playing a potential role in the early and precise detection of breast cancer. This paper presents a new machine learning-based framework that utilizes the Random Forest, Gradient Boosting, Support Vector Machine, Artificial Neural Network, and Multilayer Perception approaches to efficiently predict breast cancer from the patient data. For this purpose, the Wisconsin Diagnostic Breast Cancer (WDBC) dataset has been utilized and classified using a hybrid Multilayer Perceptron Model (MLP) and 5-fold cross-validation framework as a working prototype. For the improved classification, a connection-based feature selection technique has been used that also eliminates the recursive features. The proposed framework has been validated on two separate datasets, i.e., the Wisconsin Prognostic dataset (WPBC) and Wisconsin Original Breast Cancer (WOBC) datasets. The results demonstrate improved accuracy of 99.12% due to efficient data preprocessing and feature selection applied to the input data
A pH-responsive bi-MIL-88B MOF coated with folic acid-conjugated chitosan as a promising nanocarrier for targeted drug delivery of 5-Fluorouracil
Cancer has remained one of the leading causes of death worldwide, with a lack of effective treatment. The intrinsic shortcomings of conventional therapeutics regarding tumor specificity and non-specific toxicity prompt us to look for alternative therapeutics to mitigate these limitations. In this regard, we developed multifunctional bimetallic (FeCo) bi-MIL-88B-FC MOFs modified with folic acidâconjugated chitosan (FC) as drug delivery systems (DDS) for targeted delivery of 5-Fluorouracil (5-FU). The bi-MIL-88B nanocarriers were characterized through various techniques, including powder X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray, thermogravimetric analysis, and Fourier transform infrared spectroscopy. Interestingly, 5-FU@bi-MIL-88B-FC showed slower release of 5-FU due to a gated effect phenomenon endowed by FC surface coating compared to un-modified 5-FU@bi-MIL-88B. The pH-responsive drug release was observed, with 58% of the loaded 5-FU released in cancer cells mimicking pH (5.2) compared to only 24.9% released under physiological pH (5.4). The in vitro cytotoxicity and cellular internalization experiments revealed the superiority of 5-FU@bi-MIL-88B-FC as a highly potent targeted DDS against folate receptor (FR) positive SW480 cancer cells. Moreover, due to the presence of Fe and Co in the structure, bi-MIL-88B exhibited peroxidase-like activity for chemodynamic therapy. Based on the results, 5-FU@bi-MIL-88B-FC could serve as promising candidate for smart DDS by sustained drug release and selective targeting
DNA key based visual chaotic image encryption
With the exponential growth of Internet technologies, digital information exchanged over the Internet is also significantly increased. In order to ensure the security of multimedia contents over the open natured Internet, data should be encrypted. In this paper, the quantum chaotic map is utilized for random vectors generation. Initial conditions for the chaos map are computed from a DNA (Deoxyribonucleic acid) sequence along with plaintext image through Secure Hash Algorithm-512 (SHA-512). The first two random vectors break the correlation among pixels of the original plaintext image via row and column permutation, respectively. For the diffusion characteristics, the permuted image is bitwise XORed with a random matrix generated through the third random vectors. The diffused image is divided into Least Significant Bit (LSB) and Most Significant Bits (MSBs) and Discrete Wavelet Transform (DWT) is applied to the carrier image. The HL and HH blocks of the carrier image are replaced with LSBs and MSBs of the diffused image for the generation of a visually encrypted image. The detailed theoretical analysis and experimental simulation of the designed scheme show that the proposed encryption algorithm is highly secured. Efficiency and robustness of the proposed visually image encryption scheme is also verified via a number of attack analyses, i.e., sensitivity attack analysis (> 99%), differential attack analysis (NPCR > 99, UACI > 33), brute force attack (almost 7.9892), statistical attack (correlation coefficient values are almost 0 or less than zero), noise tolerance, and cropping attack. Further security analyses such as encryption quality (ID â
1564, DH = 3.000), homogeneity (0.3798), contrast (10.4820) and energy (0.0144) of the scheme are also evaluated
Biallelic Variants in Seven Different Genes Associated with Clinically Suspected Bardet-Biedl Syndrome
Bardet-Biedl syndrome (BBS) is a rare clinically and genetically heterogeneous autosomal recessive multi-systemic disorder with 22 known genes. The primary clinical and diagnostic features include six different hallmarks, such as rod-cone dystrophy, learning difficulties, renal abnormalities, male hypogonadism, post-axial polydactyly, and obesity. Here, we report nine consanguineous families and a non-consanguineous family with several affected individuals presenting typical clinical features of BBS. In the present study, 10 BBS Pakistani families were subjected to whole exome sequencing (WES), which revealed novel/recurrent gene variants, including a homozygous nonsense mutation (c.94C>T; p.Gln32Ter) in the IFT27 (NM_006860.5) gene in family A, a homozygous nonsense mutation (c.160A>T; p.Lys54Ter) in the BBIP1 (NM_001195306.1) gene in family B, a homozygous nonsense variant (c.720C>A; p.Cys240Ter) in the WDPCP (NM_015910.7) in family C, a homozygous nonsense variant (c.505A>T; p.Lys169Ter) in the LZTFL1 (NM_020347.4) in family D, pathogenic homozygous 1 bp deletion (c.775delA; p.Thr259Leufs*21) in the MKKS/BBS5 (NM_170784.3) gene in family E, a pathogenic homozygous missense variant (c.1339G>A; p.Ala447Thr) in BBS1 (NM_024649.4) in families F and G, a pathogenic homozygous donor splice site variant (c.951+1G>A; p?) in BBS1 (NM_024649.4) in family H, a pathogenic bi-allelic nonsense variant in MKKS (NM_170784.3) (c.119C>G; p.Ser40*) in family I, and homozygous pathogenic frameshift variants (c.196delA; p.Arg66Glufs*12) in BBS5 (NM_152384.3) in family J. Our findings extend the mutation and phenotypic spectrum of four different types of ciliopathies causing BBS and also support the importance of these genes in the development of multi-systemic human genetic disorders
Revamping of Chronic Respiratory Diseases in Low- and Middle-Income Countries
Low- and middle-income countries (LMICs) endure an asymmetrically high burden of worldwide disease and death caused by chronic respiratory diseases (CRDs), i.e., asthma, emphysema, bronchiectasis, and post-tuberculosis lung disease (PTLD). CRDs are firmly related with indigence, infectious diseases, and other non-communicable diseases (NCDs) and add to complex multi-disease with great impact on the lives and livelihood of those affected. The pertinence of CRDs to health and demographic wellbeing is relied upon to increment in the long time ahead, as expectations of life rise and the contending dangers of right on time youth mortality and irresistible infections level. The WHO has distinguished the counteraction and control of NCDs as an earnest improvement issue and crucial for the sustainable development goals (SDSs) by 2030. In this review, we center on CRDs in LMICs. We examine the early life roots of CRDs, challenges in their avoidance, identification and administration in LMICs, and the pathways to resolve for accomplish valid widespread wellbeing inclusion