Small Drugs, Huge Impact: The Extraordinary Impact of Antisense Oligonucleotides in Research and Drug Development

Antisense oligonucleotides (ASOs) are an increasingly represented class of drugs. These small sequences of nucleotides are designed to precisely target other oligonucleotides, usually RNA species, and are modified to protect them from degradation by nucleases. Their specificity is due to their sequence, so it is possible to target any RNA sequence that is already known. These molecules are very versatile and adaptable given that their sequence and chemistry can be custom manufactured. Based on the chemistry being used, their activity may significantly change and their effects on cell function and phenotypes can differ dramatically. While some will cause the target RNA to decay, others will only bind to the target and act as a steric blocker. Their incredible versatility is the key to manipulating several aspects of nucleic acid function as well as their process, and alter the transcriptome profile of a specific cell type or tissue. For example, they can be used to modify splicing or mask specific sites on a target. The entire design rather than just the sequence is essential to ensuring the specificity of the ASO to its target. Thus, it is vitally important to ensure that the complete process of drug design and testing is taken into account. ASOs’ adaptability is a considerable advantage, and over the past decades has allowed multiple new drugs to be approved. This, in turn, has had a significant and positive impact on patient lives. Given current challenges presented by the COVID-19 pandemic, it is necessary to find new therapeutic strategies that would complement the vaccination efforts being used across the globe. ASOs may be a very powerful tool that can be used to target the virus RNA and provide a therapeutic paradigm. The proof of the efficacy of ASOs as an anti-viral agent is long-standing, yet no molecule currently has FDA approval. The emergence and widespread use of RNA vaccines during this health crisis might provide an ideal opportunity to develop the first anti-viral ASOs on the market. In this review, we describe the story of ASOs, the different characteristics of their chemistry, and how their characteristics translate into research and as a clinical tool.

A spatiotemporal analysis of COVID-19 transmission in Jakarta, Indonesia for pandemic decision support

With 25% confirmed cases of the country’s total number of coronavirus disease 2019 (COVID-19) on 31 January 2021, Jakarta has the highest confirmed cases of in Indonesia. The city holds a significant role as the centre of government and national economic activity for which pandemic have had a huge impact. Spatiotemporal analysis was employed to identify the current condition of disease transmission and to provide comprehensive information on the COVID-19 outbreak in Jakarta. We applied space-time analysis to visualise the pattern of COVID-19 hotspots in each time series. We also mapped area capacity of the referral hospitals covering the entire area of Jakarta to understand the hospital service range. This research was conducted in 4 stages: i) disease mapping; ii) spatial autocorrelation analysis; iii) space-time pattern analysis; and iv) areal capacity mapping. The analysis resulted in 144 sub-districts categorised as high vulnerability. Autocorrelation studies by Moran’s I identified cluster patterns and the emerging hotspot results indicated successful interventions as the number of hotspots fell in the first period of social restrictions. The results presented should be beneficial for policy makers.

Geographic Information System Mapping Potential of E-Market in Pandemic Period

Changes in people's mindsets in obtaining accurate information are influenced by the rapid advancement of information technology. Currently, one of the most widespread applications of technology is in the field of mapping. Mapping technology is widely used to simplify important tasks. The most widely used mapping technology today is geographic information systems. Geographic Information System (GIS) is a mapping technology trend in the form of computerized information systems designed to work with spatial references. In the current pandemic period, buying and selling products offered are difficult to carry out due to restrictions on social interaction between communities, making it difficult for SMEs to sell their products. The development of information technology, especially the internet, can certainly be used as a medium to overcome these problems. The existence of a website-based information system is intended to support marketing, especially in providing detailed product and price information to consumers. The presence of the COVID-19 pandemic has changed the world with unprecedented challenges and has had a huge impact on daily human activities, resulting in a worsening of the global economy. The COVID-19 pandemic is currently entering its second year, requiring daily activities to be carried out from home. The emergence of the COVID-19 pandemic has also caused business owners to feel a very real decline. In such conditions, a web-based communicative information system is needed, from which it is hoped that problem solving, especially the provision of information about the superior products of SMEs, is needed.

An Integrated Approach for Crop Production Analysis from Geographic Information System Data using SqueezeNet

Predictions and estimations are very important for agriculture applications. The estimation results on crop production may have a huge impact in the economy of a country by changing their export and import data. The estimation of crop production was started by collecting information manually from the fields and analyzing it using a computer. However, the accuracy was not up to the mark due to the error caused by manual collection of data. The Geographic Information System (GIS) applications are developed to store the information observed from the satellite images on change detection in town planning, disaster management, business development and vegetation management. The proposed work estimates the crop production of Indian states from a GIS dataset with a SqueezeNet algorithm. The performance of the SqueezeNet algorithm is compared with the traditional Inception and ResNet algorithms.

Risk Analysis of Textile Industry Foreign Investment Based on Deep Learning

With the decline of China’s economic growth rate and the uproar of antiglobalization, the textile industry, one of the business cards of China’s globalization, is facing a huge impact. When the economic model is undergoing transformation, it is more important to prevent enterprises from falling into financial distress. So, the financial risk early warning is one of the important means to prevent enterprises from falling into financial distress. Aiming at the risk analysis of the textile industry’s foreign investment, this paper proposes an analysis method based on deep learning. This method combines residual network (ResNet) and long short-term memory (LSTM) risk prediction model. This method first establishes a risk indicator system for the textile industry and then uses ResNet to complete deep feature extraction, which are further used for LSTM training and testing. The performance of the proposed method is tested based on part of the measured data, and the results show the effectiveness of the proposed method.

Languages Speak Reconciliation: An Interdisciplinary Study on the Impact of National Language in Post War Reconciliation Sri Lanka

The Role of National Language is endorsed in different contexts and it has triggered an inspirited debate within the Sri Lankan political history when its discriminatory nature policies marked a triumph of linguist nationalism. The recognition of the Sinhala language as the only National Language in Sri Lanka and its dominance, drifted both communities apart causing frustration and tension among ethnic groups, which have ultimately culminated in ethnic strife that lasted almost three decades. National Languages, hence wield as a sociopolitical tool that demands a balance among languages, recognition, and policies. Similarly, Sri Lanka, in its path to reconciliation also demands a balance among National Languages, policies, and its recognition among the communities. This study thus explores the Role of National Language in promoting social cohesion and coexistence among ethnic groups to achieve anticipated “Reconciliation” within Sri Lankan social fabric. The paper draws upon a mixed approach employing qualitative methods, including in-depth interviews. Data were gathered from interviewing 20 undergraduates from the Faculty of Social Sciences and Languages at the Sabaragamuwa University of Sri Lanka. Data were coded and analyzed using thematic analysis. Findings revealed that the recognition of National languages in their due status will make a huge impact on fostering reconciliation within Sri Lankan Society. It is further not to be confused with the Link Language as a National Language since its duty in social integration is relatively limited in the cases where the understanding of cultural, traditional, and historical attributes of an ethnic community is more pronounced especially in grappling with attitudinal problems inherited within ethnic communities.

Hysteresis Control in Pump-Controlled Systems—A Way to Reduce Mode-Switch Oscillations in Closed and Open Circuits

There is growing interest in using electric motors as prime movers in mobile hydraulic systems. This increases the interest in so-called pump-controlled systems, where each actuator has its own drive unit. Such architectures are primarily appealing in applications where energy efficiency is important and electric recuperation is relevant. An issue with pump-controlled systems is, however, mode-switch oscillations which can appear when the pressure levels in the system are close to the switching condition. In this paper, the mode-switching behavior of different generalized closed and open circuit configurations is investigated. The results show that the choice of where to sense the pressures has a huge impact on the behavior. They also show that, if the pressure sensing components are properly placed, closed and open circuits can perform very similarly, but that mode-switch oscillations still can occur in all circuits. Active hysteresis control is suggested as a solution and its effectiveness is analyzed. The outcome from the analysis shows that active hysteresis control can reduce the risk for mode-switch oscillations significantly.

Seroprevalence and Molecular Detection of Bovine Brucellosis

Background: Brucellosis is one of the major zoonotic problems that exist worldwide. Brucellosis is clinically characterized by metritis, mastitis, repeat breeding, abortion in the last trimester of pregnancy, retention of placenta and reduced milk production in the female whereas epididymitis, orchitis and sterility in male. In humans can be highly variable, ranging from nonspecific, flu-like symptoms to undulant fever, arthritis, orchitis and epididymitis. Methods: A total of 567 bovine serum samples was taken from four districts of Brij region of UP. All the samples were processed to detection of prevalence of brucellosis by RBPT, STAT ELISA and confirmation of genes bcsp31, 16SrRNA, omp2 and IS711 by PCR. Result: The prevalence of brucellosis was found to be 07.93% (31/391), 08.69% (34/391) and 10.74% (42/391) shows positive by RBPT, STAT and I- ELISA respectively. In buffalo Out of 176 tested serum sample the seroprevalence was found to be 09.66% (17/176), 10.79% (19/176) and 12.5% (22/176) positive by RBPT, STAT and I- ELISA respectively. Out of 567 samples 18 were positive for Brucella genus specific gene. The higher prevalence of the disease in this region increases the risk of zoonotic transmission and it implies a serious threat to the human population as well as the huge impact on economy due to loss of productivity as well as loss of livestock population.

Pola Pergerakan Orang di Masa Pandemi dengan Pendekatan Eksploratif di Wilayah Kepulauan Bangka Belitung

COVID-19 has spread around the world and has given a huge impact on people's lives. One of the changes in the COVID-19 condition is the travel pattern of people. Travel patterns can be explained in terms of the flow of vehicles, passengers, and people's mobility from the origin and destination zones within a certain area and period. On the other hand, it is known that travel patterns are an essential factor in solving transportation problems. The change of travel pattern data is needed for transportation planners and policymakers in providing safe transportation during the pandemic. In addition, data on travel patterns also play an important role in determining travel restrictions in an area to reduce the spread of COVID-19. This study tries to analyze travel patterns during the COVID-19 pandemic through an exploratory approach by taking a case study in the Bangka Belitung Province. The results of this study show that the mobility was dominated by intra-island trips during the pandemic, both within Bangka Island and Belitung Island. Furthermore, during the COVID-19 pandemic, the majority of people made changes to their routine's mobility. More than 50% of people did not return to their original travel patterns even though the pandemic conditions had entered the New Normal period. The most influential factor which makes people change their mobility is to take precautions from COVID-19.

Experimental Evaluation of Distortion Effect for Grid-Connected PV Systems with Reference to Different Types of Electric Power Quantities

Aware of the fact that the installed PV capacity and its power production rapidly increased in the last decade, with the huge impact that has been done to the power system, the distortion effects for grid-connected PV systems with reference to different types of electric power quantities will be presented in this article. The impact of the frequent fluctuation of solar irradiance on the behavior of the grid-connected PV system, due to cloud movements and resulting shadows and in terms of power quality and the evaluation of power components, is the topic of analysis in this research. Besides the simulation results of certain study cases, an experimental evaluation of electric power quantities on an actual PV system in real weather conditions was also performed. The experimental setup, formed through the combination of a PC and multifunctional I/O board with an appropriate software solution, was established and used for obtaining the target results. The methodology used for the evaluation of electric power quantities relied on the current physical components (CPC) theory for power definition. The experimental results were obtained for three different cases, namely, the low, medium, and high solar irradiance cases. On the basis of these results, the conclusions about distortion effects are given.