Assessment and classification of COVID-19 DNA sequence using pairwise features concatenation from multi-transformer and deep features with machine learning models.

The 2019 novel coronavirus (renamed SARS-CoV-2, and generally referred to as the COVID-19 virus) has spread to 184 countries with over 1.5 million confirmed cases. Such a major viral outbreak demands early elucidation of taxonomic classification and origin of the virus genomic sequence, for strategic planning, containment, and treatment. The emerging global infectious COVID-19 disease by novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) presents critical threats to global public health and the economy since it was identified in late December 2019 in China. The virus has gone through various pathways of evolution. Due to the continued evolution of the SARS-CoV-2 pandemic, researchers worldwide are working to mitigate, suppress its spread, and better understand it by deploying deep learning and machine learning approaches. In a general computational context for biomedical data analysis, DNA sequence classification is a crucial challenge. Several machine and deep learning techniques have been used in recent years to complete this task with some success. The classification of DNA sequences is a key research area in bioinformatics as it enables researchers to conduct genomic analysis and detect possible diseases. In this paper, three state-of-the-art deep learning-based models are proposed using two DNA sequence conversion methods. We also proposed a novel multi-transformer deep learning model and pairwise features fusion technique for DNA sequence classification. Furthermore, deep features are extracted from the last layer of the multi-transformer and used in machine-learning models for DNA sequence classification. The k-mer and one-hot encoding sequence conversion techniques have been presented. The proposed multi-transformer achieved the highest performance in COVID DNA sequence classification. Automatic identification and classification of viruses are essential to avoid an outbreak like COVID-19. It also helps in detecting the effect of viruses and drug design.

Morphological, physiological and molecular assessment of cotton for drought tolerance under field conditions.

Climate change could be an existential threat to many crops. Drought and heat stress are becoming harder for cultivated crops. Cotton in Pakistan is grown under natural high temperature and low moisture, could be used as a source of heat and drought tolerance. Therefore, the study was conducted to morphological, physiological and molecular characterization of cotton genotypes under field conditions. A total of 25 cotton genotypes were selected from the gene pool of Pakistan based on tolerance to heat and drought stress. In field trail, the stress related traits like boll retention percentage, plant height, number of nodes and inter-nodal distance were recorded. In physiological assessment, traits such as photosynthesis rate, stomatal conductance, transpiration rate, leaf temperature, relative water content and excised leaf water loss were observed. At molecular level, a set of 19 important transcription factors, controlling drought/heat stress tolerance (HSPCB, GHSP26, HSFA2, HSP101, HSP3, DREB1A, DREB2A, TPS, GhNAC2, GbMYB5, GhWRKY41, GhMKK3, GhMPK17, GhMKK1, GhMPK2, APX1, HSC70, ANNAT8, and GhPP2A1) were analyzed from all genotypes. Data analyses depicted that boll retention percentage, photosynthesis, stomatal conductance, relative water content under the stress conditions were associated with the presence of important drought & heat TF/genes which depicts high genetic potential of Pakistani cotton varieties against abiotic stress. The variety MNH-886 appeared in medium plant height, high boll retention percentage, high relative water content, photosynthesis rate, stomatal conductance, transpiration rate and with maximum number transcription factors under study. The variety may be used as source material for heat and drought tolerant cotton breeding. The results of this study may be useful for the cotton breeders to develop genotype adoptable to environmental stresses under climate change scenario.

How financial development affects green energy finance? Relationship between environmental regulation and economic performance.

The construction of green finance index is a three-tiered process that involves macroeconomic, ecological, and monetary indicators. Therefore, this research is one of the first thorough assessments of the impacts of green financing regulations in China, examining 30 provinces during the period of 2010 to 2017. Data envelopment analysis models for 30 provinces in China have been tested by using non-radial models and longitudinal datasets. The findings demonstrate that between 2010 and 2017, the efficiency of China's provinces such as Beijing, Fujian, Guangdong, Hainan, Hebei, Jiangsu, Liaoning, Shandong, Shanghai, Tianjin, and Zhejiang and provinces of central regions as well as western provinces of country green economies has increased with distinct geographical disparities becoming more apparent. The geographical distribution of economic efficacy in the green economy is greatest in the eastern parts and poorest in the Chongqing, Gansu, Guangxi, Guizhou, Inner Mongolia, Ningxia, Qinghai, Shaanxi, Sichuan, Tibet, Xinjiang, and Yunnan. The study revealed that sustainable financial growth may be accomplished via the creation of green financing, which can be achieved by employing different solutions across the macroeconomic, institutional, and ecological considerations. The western and central areas, however, have a significant negative association. There are substantial variations in factors at the state and federal level from the viewpoint of dependent variables. Eventually, the research offers some suggestions for future ecological impact of China, along with the creation of new environmental legislation.

Development of Cerium Oxide/Corncob Nanocomposite: A Cost-Effective and Eco-Friendly Adsorbent for the Removal of Heavy Metals.

This research aims to assess the efficiency of the synthesized corncob as a cost-effective and eco-friendly adsorbent for the removal of heavy metals. Therefore, to carry out the intended research project, initially, the corncob was doped with nanoparticles to increase its efficiency or adsorption capacity. The prepared adsorbent was evaluated for the adsorption of cadmium (Cd) and chromium (Cr) from aqueous media with the batch experiment method. Factors that affect the adsorption process are pH, initial concentration, contact time and adsorbent dose. The analysis of Cd and Cr was performed by using atomic absorption spectrometry (AAS), while the characterization of the adsorbent was performed using Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM). The results showed that there is a significant difference before and after corncob activation and doping with CeO2 nanoparticles. The maximum removal for both Cd and Cr was at a basic pH with a contact time of 60 min at 120 rpm, which is 95% for Cd and 88% for Cr, respectively. To analyze the experimental data, a pseudo-first-order kinetic model, pseudo-second-order kinetic model, and intra-particle diffusion model were used. The kinetic adsorption studies confirmed that the experimental data were best fitted with the pseudo-second-order kinetic model (R2 = 0.989) and intra-particle diffusion model (R2 = 0.979). This work demonstrates that the cerium oxide/corncob nanocomposite is an inexpensive and environmentally friendly adsorbent for the removal of Cd and Cr from wastewater.

Role of economic growth and innovative technologies in the outlook of energy and environmental efficiency: a way forward for developing Asian economies.

Energy consumption is widely regarded as the primary driver of economic development and environmental degradation. The current study examines how energy use is related to technological innovation, human resources, energy pricing, economic development, and trade openness. For this context, the data set of OECD economies' indicators as mentioned above has been compiled for the period 1991-2019. Three estimators were used in this study from the family of autoregressive distributed lag (ARDL): the mean group (MG), the dynamic fixed effect (DFE), and the pooled mean group (PMG). According to empirical research, technical advances, human resources, and energy pricing all have a negative impact on OECD countries' long-run energy consumption. In the short term, however, these variables have a negligible or inverse effect on energy consumption. On the other hand, economic growth and trade openness in OECD economies all contribute positively to energy demand in the short and long run. Based on the empirical findings, this study recommends a policy structure for emerging economies.

Cost difference of enhanced recovery after surgery pathway vs. Conventional care In Elective Laparoscopic Cholecystectomy.

BACKGROUND: Enhanced recovery after surgery (ERAS) is a perioperative bundle aimed to reduce surgical stress. Significant reductions in length of hospital stay and associated costs have been reported in multiple studies in all surgical specialties. Purpose of the study was to compare the effect of Enhanced recovery protocols vs. conventional care on perioperative length of hospital stay and cost per patient in a government funded hospital. METHODS: this randomized controlled trial was conducted in the department of General Surgery, unit B, Lady reading hospital, Peshawar from April to December 2018. One hundred and fifty patients were selected based on consecutive sampling. Random allocation into two groups of 75 (ERAS vs Conventional) was done based on computer generated numbers. Length of hospital stay and total direct costs were calculated. Frequency of Surgical site infections, readmissions and mortality was also recorded. Patient reported outcomes were recorded by Surgical Recovery Scale SRS. RESULTS: Patients in the Enhanced recovery group showed a significant reduction in length of hospital stay 28.9 hours in ERAS group vs 40.5 hours in Conventional care group (p<0.001). Total per patient cost was reduced in the ERAS group PKR 6804 in comparison to the conventional care PKR 7682 (p<0.001). Patient reported outcomes measured on Surgical Recovery Scale SRS on discharge, day 3 of discharge and day 10 of discharge showed no significant difference between the two groups. CONCLUSIONS: Enhanced recovery protocols demonstrated a reduction in length of perioperative hospital stay and total cost despite similar post discharge recovery scores on Surgical Recovery Scale SRS and no increase in readmissions.

Assessment of flatulence causing agents in Chickpea (Cicer arietinum L.) and their possible removal

Abstract Flatulence and fullness of stomach is one of the most common problem associated with chickpea primary due to presence of some oligosaccharides and phenols. In this investigation Desi and Kabuli varieties were compared for these oligosaccharides and phenolic compounds. Furthermore, the effect of different processing and cooking methods such as soaking, cooking and germination in the reduction of these antiphysiological factors were are also studies. Maximum tannic acid (0.90 ± 0.20%) was observed in Parbat and C-44 while minimum (0.60 ± 0.04%) in Karak-2. Stachyose contents ranged between 1.10 ± 0.05 (Karak-3) to 1.42 ± 0.02% (Parbat) while raffinose was 0.63 ± 0.05(Karak-3) to 0.81 ± 0.02% (Dasht). The highest tannic acid content was reduced up to 50% in C-44 by cooking of 72 hours germinated seeds. Stachyose and raffinose contents were completely removed after 72 hours germination. Present studies revealed that cooking after germination is the most effective method to reduce the anti-nutritional factors of chickpea. Individually, soaking and cooking also contributed to the loss of the same factors but to a lesser extent.

Capacity development for health research in Pakistan: the effects of doctoral training.

Capacity development for health research has been promoted in developing countries for many years, especially by international aid agencies. In Pakistan the government has been investing substantial funds in the development of a critical mass of scientists in the country. This paper represents the first attempt in Pakistan to assess the impact of capacity development efforts in health research. The study surveyed 54 Pakistani researchers who were sent for doctoral training to institutions out of the country on funded programmes in the past three decades. The 50 male and four female respondents had an average of 5.7 years of job experience prior to being sent for training and the average duration of training per person was 4 years. The average reported expenditure directly given to the trainees was US dollars 35300 (1995 US dollars) per person. These researchers had an average of 15 publications per person, while they have trained an average of nine students per researcher since return to Pakistan. The respondents indicated a lack of academic liberty and incentives to sustain their research efforts, and recommended autonomy in work and provision of facilities to stimulate their contributions. This study reflects the complex issues facing highly trained researchers who have returned to Pakistan and are attempting to pursue their careers. Their contributions in terms of writing papers, teaching students and policy involvement are important for assessing capacity development efforts. Comparative data from other developing nations is severely lacking for cross-country analysis. Such evaluations are critical to develop plans for the reduction of the 10/90 gap in health research investments.