Boosting edgeR (Robust) by dealing with missing observations and gene-specific outliers in RNA-Seq profiles and its application to explore biomarker genes for diagnosis and therapies of ovarian cancer.

The edgeR (Robust) is a popular approach for identifying differentially expressed genes (DEGs) from RNA-Seq profiles. However, it shows weak performance against gene-specific outliers and is unable to handle missing observations. To address these issues, we proposed a pre-processing approach of RNA-Seq count data by combining the iLOO-based outlier detection and random forest-based missing imputation approach for boosting the performance of edgeR (Robust). Both simulation and real RNA-Seq count data analysis results showed that the proposed edgeR (Robust) outperformed than the conventional edgeR (Robust). To investigate the effectiveness of identified DEGs for diagnosis, and therapies of ovarian cancer (OC), we selected top-ranked 12 DEGs (IL6, XCL1, CXCL8, C1QC, C1QB, SNAI2, TYROBP, COL1A2, SNAP25, NTS, CXCL2, and AGT) and suggested hub-DEGs guided top-ranked 10 candidate drug-molecules for the treatment against OC. Hence, our proposed procedure might be an effective computational tool for exploring potential DEGs from RNA-Seq profiles for diagnosis and therapies of any disease.

Synthesis and biophysical properties of tetravalent PEG-conjugated antisense oligonucleotide.

This study was aimed at developing a novel platform for tetravalent conjugation of 4-arm polyethylene glycol (PEG) with an antisense oligonucleotide (ASO). The ASO technology has several limitations, such as low cellular uptake, poor nuclease stability, and short half-life. PEG-conjugated ASOs may result in an improvement in the pharmacokinetic behavior of the drug. Moreover, PEGylation can reduce enzymatic degradation and renal excretion of the conjugates, thereby, increasing its blood stability and retention time. In this study, we successfully synthesized PEG-ASO conjugate consisting of 4-arm-PEG and four molecules of ASO (4-arm-PEG-tetra ASO). Its hybridization ability with complementary RNA, enzymatic stability, and in vitro gene silencing ability were evaluated. No significant difference in hybridization ability was observed between 4-arm-PEG-tetra ASO and the parent ASO. In addition, gene silencing activity of the 4-arm-PEG-tetra ASO was observed in vitro. However, the in vitro activity of the 4-arm-PEG-tetra ASO was slightly reduced as that of the parent ASO. Moreover, the 4-arm-PEG-tetra ASO showed appreciable stability in cellular extract, suggesting that it hybridizes with mRNA in its intact form, without being cleaved in the cell, and exhibits ASO activity.

Low-loss and bend-insensitive terahertz fiber using a rhombic-shaped core.

A novel porous-core photonic crystal fiber is presented, and its guiding properties are numerically investigated by using the finite element method. It is demonstrated that by introducing a rhombic-shaped core made of circular air holes inside the conventional hexagonal cladding, it is possible to obtain very low bending loss of 3.04×10-11 cm-1 at the operating frequency of 1.0 THz. In addition to this, low effective material loss of 0.089 cm-1 and very small confinement loss of 1.17×10-3 dB/cm are achieved for optimal design parameters. Other guiding properties, including effective area, dispersion, and higher order mode characteristics are also discussed thoroughly. The design of this porous fiber is relatively simple, since it contains fewer air holes and consists of circular air holes only. Due to promising wave-guiding properties, the proposed fiber would have a great potential for terahertz imaging and flexible communication applications.

Polarization-maintaining low-loss porous-core spiral photonic crystal fiber for terahertz wave guidance.

A polarization-maintaining porous-core spiral photonic crystal fiber is proposed for efficient transmission of polarization-maintaining terahertz (THz) waves. The finite element method with perfectly matched layer boundary conditions is used to characterize the guiding properties. We demonstrate that by creating artificial asymmetry in the porous core, an ultrahigh birefringence of 0.0483 can be obtained at the operating frequency of 1.0 THz. Moreover, a low effective material loss of 0.085 cm-1 and very small confinement loss of 1.91×10-3 dB/cm are achieved for the y-polarization mode with optimal design parameters. This article also focuses on some crucial design parameters such as power fraction, bending loss, and dispersion for usability in the THz regime.

Enhancing agricultural automation through weather invariant soil parameter prediction using machine learning.

Soil parameters are crucial aspects in increasing agricultural production. Even though Bangladesh is heavily dependent on agriculture, little research has been done regarding its automation. And a vital aspect of agricultural automation is predicting soil parameters. Generally, sensors relating to soil parameters are quite expensive and are often done in a controlled environment such as a greenhouse. However, a large scale implementation of such expensive sensors is not very feasible. This work tries to find an inexpensive solution towards predicting soil parameters such as soil moisture and temperature, both of which are crucial to the growth of crops. We focus on finding a robust relation between the above mentioned soil parameters with the nearby weather parameters such as humidity and temperature, irrespective of the weather. We apply different machine learning models like multilayer perceptron (MLP), random forest, etc. to predict the soil parameters, given the humidity and temperature of the surrounding environment. For all the experiments we have used a custom made dataset, which contains around 9000 datapoints of soil moisture & temperature, ambient humidity & temperature. The data has been collected in an uncontrolled agriculture bed via inexpensive sensors. Our results show that XGBoost regressor achieves the best results with an R2 score of 0.93 and 0.99 for soil moisture and soil temperature data respectively. This suggests very high correlation between the weather parameters and soil parameters. The model also portrayed a very low root mean squared error and mean absolute error of 0.037 & 0.015 for soil moisture and 0.001 & 0.0008 for soil temperature. Our results show that it is indeed possible to find the soil parameters from the corresponding weather, which will have great impact on mass agricultural automation. The dataset has been made publicly available at https://github.com/Nadimulhaque0403/Soil_parameter_prediction_dataset.

Synergistic Effect of Allium-like Ni9 S8 & Cu7 S4 Electrodeposited on Nickel Foam for Enhanced Water Splitting Activity.

This study explores a water-splitting activity using a biphasic electrodeposited electrode on nickel foam (NF). The *Ni9 S8 /Cu7 S4 /NF electrode with citric acid reduction exhibits superior OER (oxygen evolution reaction) and HER (hydrogen evolution reaction) performance with reduced overpotential and a steeper Tafel slope. The *Ni9 S8 /Cu7 S4 /NF electrode displays the ultra-low overpotential value of 212 mV for OER and 109 mV for HER at the current density of 10 mA cm-2 . The Tafel slope of 25.4 mV dec-1 for OER and 108 mV dec-1 for HER was found from that electrode. The maximum electrochemical surface area (ECSA), lowest series resistance and lowest charge transfer resistance are found in citric acid reduced electrode, showing increased electrical conductivity and quick charge transfer kinetics. Remarkably, the *Ni9 S8 /Cu7 S4 /NF electrode demonstrated excellent stability for 80 hours in pure water splitting and 20 hours in seawater splitting. The synergistic effect of using bimetallic (Cu&Ni) sulfide and enhanced electrical conductivity of the electrode are caused by reduction of metal sulfide into metallic species resulting in improved water splitting performance.

Metal organic framework derived NiO x nanoparticles for application as a hole transport layer in perovskite solar cells.

NiO x as a hole transport layer (HTL) has gained a lot of research interest in perovskite solar cells (PSCs), owing to its high optical transmittance, high power conversion efficiency, wide band-gap and ease of fabrication. In this work, four different nickel based-metal organic frameworks (MOFs) using 1,3,5-benzenetricarboxylic acid (BTC), terephthalic acid (TPA), 2-aminoterephthalic acid (ATPA), and 2,5-dihydroxyterephthalic acid (DHTPA) ligands respectively, have been employed as precursors to synthesize NiO x NPs. The employment of different ligands was found to result in NiO x NPs with different structural, optical and morphological properties. The impact of calcination temperatures of the MOFs was also studied and according to field emission scanning electron microscopy (FESEM), all MOF-derived NiO x NPs exhibited lower particle size at lower calcination temperature. Upon optimization, Ni-TPA MOF derived NiO x NPs calcined at 600 °C were identified to be the best for hole transport layer application. To explore the photovoltaic performance, these NiO x NPs have been fabricated as a thin film and its structural, optical and electrical characteristics were analyzed. According to the findings, the band energy gap (E g) of the fabricated thin film has been found to be 3.25 eV and the carrier concentration, hole mobility and resistivity were also measured to be 6.8 × 1014 cm-3; 4.7 × 1014 Ω cm and 2.0 cm2 V-1 s-1, respectively. Finally, a numerical simulation was conducted using SCAPS-1D incorporating the optical and electrical parameters from the thin film analysis. FTO/TiO2/CsPbBr3/NiO x /C has been utilized as the device configuration which recorded an efficiency of 13.9% with V oc of 1.89 V, J sc of 11.07 mA cm-2, and FF of 66.6%.