Miracle-dz/UniFAR-FTUs huggingface dataset:
Nucleic acid amplification

Methods and compositions for the amplification of nucleic acids and for the production of concatamers are disclosed. The amplification methods provided herein can be performed under isothermal conditions. The methods and compositions can include reagents such as nucleic acid polymerases and primers. In some embodiments, provided herein is a method for generating a concatamer comprising two or more copies of a double stranded nucleic acid template. In some embodiments, provided herein is a method for generating a concatamer comprising two or more copies of a polynucleotide template or similar sequence thereof.
Simulation of a SEPIC Based Single Switch Buck-Boost DC-DC Converter

This paper presents simulation of a SEPIC based buck-boost DC to DC converter with a single switch. The simulation is performed in MATLAB/Simulink software. Open loop and closed loop simulations are carried out to get a better understanding about the converter. This converter has a better voltage gain in comparison with traditional converters. This is a single switch converter and voltage stress experienced by switch is very less. Also the need of large input filter is eliminated by the continues nature of input current. Along with this the output voltage provided by the converter is non-inverting. All these features are validated with the help of simulation performed.
Soft Sensor Model Based on IBA-LSSVM for Photosynthetic Bacteria Fermentation Process

It is difficult to measure the key biological process variables of photosynthetic bacteria fermentation in real-time, and offline measurement has a large time lag and cannot meet the needs of real-time optimization control. In this paper, a soft sensor model based on least square support vector machine with an improved bat algorithm (IBA-LSSVM) was proposed. The velocity equation of the bat algorithm (BA) was improved and the random variation operation in differential evolution algorithm was introduced into BA algorithm. Thus, the diversity of the population can be increased, and the global and local searching ability of the BA algorithm can be enhanced. Furthermore, the IBA-LSSVM soft sensor model was established for the living cell concentration and compared with BA-LSSVM soft sensor model. Finally, the simulation results show that the improved model was the better learning ability and prediction performance than BA-LSSVM, the measurement error is 0.1358. The improved model could provide accurate guidance for the photosynthetic bacteria fermentation control optimization. This model has certain practical value.
The Use of Soft System Methodology To Build A Conceptual Model for Strengthening Innovation of Entrepreneurs in Coastal Area of Jakarta

Strengthening innovation for entrepreneur is very important because nowadays consumers are smarter and they demand to meet their needs in terms of quality, renewal and price. Small businesses and beginners are often unable to achieve business sustainability. Therefore, innovative capabilities are needed to meet consumer's needs and to achieve business sustainability. By using an entrepreneurial ecosystem approach through elements of actors, factors, enthusiasm and interrelated processes that can strengthen the innovation of entrepreneur. The main purpose of this paper is to analyze the dynamics of entrepreneurial innovation so that factors to strengthen innovation can be identified. This study uses Soft System Methodology (SSM) through the application of SSM steps to obtain a conceptual model to strengthen innovation for entrepreneur. This research was conducted for 6 months, by conducting in-depth interviews with 50 respondents consisting of government, academics, community leaders and business actors. The results showed that a strong will from within the entrepreneur and the use of technology are key factors in strengthening entrepreneurial innovation. Keywords: coastal area, conceptual model, entrepreneur, innovation, soft system methodology
From Traditional Food to Functional Food? Evaluation of Malvaceae Species as Novel Food Crops

Diversification of local food production can streamline supply chains, and ultimately increase food security. Research often focuses on improving existing crops by selection and by agro-technology rather than searching for novel crops. Plants that are traditionally eaten are interesting candidates for adaptation to commercialised agriculture. In this research, two Malvaceae species were explored as potential food crops, as the literature suggests Malvaceae exhibits valuable nutritional merits. This work examined Malva nicaeensis and Lavatera cretica, referred to as “Khubeza” (or “Hubeza”) as a generic term. The plants were experimentally cultivated in two different locations, their leaves were collected, and nutritive values compared. Khubeza leaves exhibited similar or better nutritive value to that of spinach, used here as a reference product. Thus, we conclude that “Khubeza” has potential to enhance food security, expand economic implementation, and to overall diversify agriculture, making it more resilient in the face of projected changes.
BIOACCESSIBILITY OF IRON AND ZINC FROM GRAINS OF DIFFERENT SORGHUM GENOTYPES

The study was conducted on bioaccessibility of iron and zinc from twenty four different sorghum genotypes in the year 2014-2015. Physical characteristics, total inherent iron and zinc content, antinutritional factors and effect of processing and preparations methods on iron and zinc bioaccessibility were studied. The sorghum genotypes comprised of rabi local, advanced and released and kharif were selected for the study. The results showed there was significant variation in physical parameters of grains such as weight, volume, density, colour and size. Similarly, moisture, protein, ash and mineral content like iron (4.21 to 18.37 mg/100g) and zinc (0.44 to 1.70 mg/100g) showed significant variation. Antinutritional factors such as polyphenols (44.03 to 209.03 CE mg/100g), phytate (130.52 to 985.03 mg/100g), tannin (71.63 to 235.6 CE mg/100g), calcium (15.6 to 37.64 mg/100g), total (6.83 to 14 g/100g), insoluble (6.43 to 13.73 g/100g) and soluble (0.23 to 2.0 g/100g) dietary fibre content of different sorghum genotypes showed significant variation. Processing sorghum into sorghum rice increased iron and zinc bioaccessibility from 0.47 to 0.61 mg/100g and 0.13 to 0.48 mg/100g in SPV-2217 and in IS-4698 from 0.53 to 0.56 mg/100g and 0.27 to 0.57 mg/100g respectively. Popping of SPV-2217 genotype, improved iron (0.47 to 0.84 mg/100g) and zinc bioaccessibility (0.13 to 0.25 mg/100g). Mudde from SPV-2217 genotype increased iron bioaccessibility (0.49 to 0.52 mg/100g) and in M 35-1 zinc bioaccessibility increased (0.08 to 0.16 mg/100g). Preparation of roti from SPV-2217 improved iron (0.49 to 0.59 mg/100g) and zinc bioaccessibility (0.15 to 0.27 mg/100g). From the results, among all sorghum genotypes, rabi genotypes showed higher inherent mineral and antinutrients content compared to kharif genotypes. Processing the grains into traditional products like rice, popped grain, mudde and roti improved iron and zinc bioaccessibility.
Enhancing the accuracy of GPS Positioning for vehicle tracking system

Vehicle security refers to securing the vehicle against potential thieves. Vehicle makers have been experimenting with various approaches in order to give improved security systems. The usage of GPS and GSM technology can provide security for the car. The security of a vehicle is ensured in this project by tracking its whereabouts. For the integration of the global positioning system, the EKF is widely utilised (GPS) When the system's non-linearity grows or the measurement co-variance is erroneous, the EKF’s performance deteriorates. An extended state observer is introduced for the first time to improve loosely coupled GPS navigation performance utilizing accurate measurement modeling. The RMS values of positional errors are reduced by 52.57 percent, 48.56 percent, and 34.16 percent in the north, east, and vertical directions, respectively.
POLYPHENOL CONTENT AND ANTIOXIDANT POTENTIAL OF Allophylus edulis (A. St.-Hil. et al.) Hieron. ex Niederl. AND Cupania vernalis Cambess. (SAPINDACEAE)

ABSTRACT Allophylus edulis and Cupania vernalis (Sapindaceae) are Brazilian native trees used as medicinal plants for the treatment of respiratory, digestive, circulatory, and skin diseases. Ubiquitously distributed in the Brazilian territory, these species are indicated for mixed plantations aimed at the recovery of degraded ecosystems. In this study, the total phenolic content (TPC) and total flavonoid content (TFC), and the antioxidant activity of extracts and fractions obtained from A. edulis and C. vernalis leaves were assessed. The TPC and TFC was determined spectrophotometrically. Antioxidant activity was evaluated through radical scavenging activity of 2,2-diphenyl-1-picrylhydrazyl (DPPH). The extracts were obtained by two methods: maceration (method 1) and Soxhlet (method 2). Solvents of increasing polarity (hexane, dichloromethane, ethyl acetate, and n-butanol) were used to obtained the fractions. The results showed that the ethyl acetate fraction from A. edulis, obtained from the maceration method, had the highest TPC (442.0 ± 18.2 mg GAE g-1) and TFC (58.1 ± 0.4 mg RUE g-1), and antioxidant activity (EC50 = 43.6 ± 2.6 µg mL-1). By C. vernalis, superior results were obtained with the n-butanol fraction (TPC = 126.1 ± 5.8 mg GAE g-1, TFC = 37.7 ± 0.6 mg RUE g-1). The highest antioxidant potential was found in the crude hydroalcoholic extract (EC50 = 816.1 ± 50.9 µg mL-1) and butanol fraction (1,156.4 ± 3.8 µg mL-1). The results of this study show that the fractions obtained by maceration and liquid-liquid partition with more polar solvents (ethyl acetate and n-butanol) are the richest in TPC and TFC, and presented the greater antioxidant activity. Comparing the two plants, A. edulis showed the best results, with a high content of TPC, TFC, and antioxidant potential, and therefore may be used to treat diseases related to oxidative stress.
CRIME DATA ANALYSIS WITH ASSOCIATION RULE MINING

Along with the positive developments of the globalizing world, new types of crime such as social media fraud, drug trafficking and vehicle robbery, which have disrupted community welfare and order, have also emerged. With developments in information technology, it is possible to record real-time various data related to subject of crimes, location and time information, type of crime. By analyzing these recorded raw data using various data mining methods, it is possible to extract information that can be used to identify the data or for prediction purposes. In this study, an analysis of the association rules on the NIBRS Crime dataset which includes real crime cases from July 2016 to April 2018 in the state of Maryland in USA was carried out using R program with Apriori algorithm and Rapid Miner with FP-Growth al-gorithm. With these association rules created, the time intervals, the districts, the types of crimes and the frequency of the occurrences are analyzed and the results of the algorithms are presented. With the results of this analysis; for organizations which are responsible for maintaining the peace and social order, such as security forces and law enforcement agencies; it is possible to follow useful information such as which crimes are committed more frequently and in which time period of day the criminals are more active.
GMDH Neural Networks - Based Modeling of Variable Power Inductor

In this paper, the Group Method of Data Handling (GMDH) type of neural networks is used for the inductance calculation of variable inductors. The relation between the inductance of the inductor in the linear and nonlinear regions is investigated, and parameters such as the voltage across the inductor, bias current, and ac current are taken into account. The experimental setup is used for generating the data needed for training the neural network. Over 800 experiments were conducted and were used for training and validation of the neural network results. The results are compared with the reluctance equivalent circuit method, and they show a much better accuracy. The proposed method can be used for the calculation of various magnetic components, and it is not limited to variable inductors.
Visual Analysis of Spatiotemporal Data Predictions with Deep Learning Models

The output of a deep-learning model delivers different predictions depending on the input of the deep learning model. In particular, the input characteristics might affect the output of a deep learning model. When predicting data that are measured with sensors in multiple locations, it is necessary to train a deep learning model with spatiotemporal characteristics of the data. Additionally, since not all of the data measured together result in increasing the accuracy of the deep learning model, we need to utilize the correlation characteristics between the data features. However, it is difficult to interpret the deep learning output, depending on the input characteristics. Therefore, it is necessary to analyze how the input characteristics affect prediction results to interpret deep learning models. In this paper, we propose a visualization system to analyze deep learning models with air pollution data. The proposed system visualizes the predictions according to the input characteristics. The input characteristics include space-time and data features, and we apply temporal prediction networks, including gated recurrent units (GRU), long short term memory (LSTM), and spatiotemporal prediction networks (convolutional LSTM) as deep learning models. We interpret the output according to the characteristics of input to show the effectiveness of the system.
Hierarchical Electrode Switching Device Design for Distributed Single-Channel Electrical Resistivity Tomography System

An electrode switching device (ESD) is one of the most important components of electrical resistivity tomography (ERT). It is a ligament and relay between a testing circuit and testing electrodes. Existing ESD uses a plane structure to realize the interconnection between ports and testing electrodes. Taking Wenner testing as an example, each electrode needs four additional switches. In this report, a new hardware saving ESD (HESD) is made with a hierarchical structure for a single-channel distributed ERT. HESD has two-layered switches to realize the conversion process. The first layer of 16 switches can realize four pairs of unrepeated connection between four ports—AMNB and four Lines—L1–L4. The second layer establishes the non-overlapping joints between four lines—L1–L4 and four testing electrodes. Each electrode only needs one switch for an 1D test, which has been wildly used in soil science, ocean probing, and contaminated surveys, and an odd number layer test. With the newly designed HESD, three fourths of the cost of hardware (switch) was saved compared with the conventional ESD. In addition, with two more switches, HESD was able to complete a 2D survey. The new two-layer HESD saves hardware costs and shows advantages in maintenance, system tests, and miniaturization, especially when many electrodes are required in an ERT system, which is very common in practice.
Distinguishing areas of organic, biodynamic and conventional farming by means of multispectral images. A pilot study

Abstract The aim of the present investigation was to develop a basic methodological scheme for distinguishing organic, biodynamic and conventional areas of winter wheat cultivation, based on the satellite images from Sentinel-2. The target areas are located in the experimental field of the Institute of Agriculture in Karnobat, Bulgaria. The plant condition was determined on a three-point rating scale according to the average plant height, percentage of projective cover of the aboveground plant parts and intensity of the green color of leaves during the end of tillering to complete ripeness. To determine the homogeneity of the target polygons, we used a small drone DJI Phantom 4, with 1/2.3 CMOS camera and Dronedeploy to compile flight plans for shooting and photogrammetric processing of the images. ArcGIS was used in GIS procedures and analyses. Microsoft Excel, with Solver ADD-IN was used to clusterize the target polygons in order to distinguish the polygons of organic, biodynamic and conventional farming by the multispectral indices (CRI 1, MSAVI, NDVI, NDWI, PSSRa, PSSRc, WDRVI). All selected indices were calculated in GIS environment. Ground observations showed that there were differences in the condition of plants in different cultivation systems during the selected observation phases. The obtained results reveal that the differences in dynamics and development during the growth and development stages of the wheat in the organic, biodynamic and conventional fields can be traced by spectral characteristics from satellite images and they can be used to distinguish them.
Infection control practices and challenges in Pakistan during the COVID-19 pandemic: a multicentre cross-sectional study

Background: Patient and staff safety at healthcare facilities during outbreaks hinges on a prompt infection prevention and control response. Physicians leading these programmes have encountered numerous obstacles during the pandemic. Aim/objective: The aim of this study was to evaluate infection prevention and control practices and explore the challenges in Pakistan during the coronavirus disease 2019 pandemic. Methods: We conducted a cross-sectional study and administered a survey to physicians leading infection prevention and control programmes at 18 hospitals in Pakistan. Results: All participants implemented universal masking, limited the intake of patients and designated separate triage areas, wards and intensive care units for coronavirus disease 2019 patients at their hospitals. Eleven (61%) physicians reported personal protective equipment shortages. Staff at three (17%) hospitals worked without the appropriate personal protective equipment due to limited supplies. All participants felt overworked and 17 (94%) reported stress. Physicians identified the lack of negative pressure rooms, fear and anxiety among hospital staff, rapidly evolving guidelines, personal protective equipment shortages and opposition from hospital staff regarding the choice of recommended personal protective equipment as major challenges during the pandemic. Discussion: The results of this study highlight the challenges faced by physicians leading infection prevention and control programmes in Pakistan. It is essential to support infection prevention and control personnel and bridge the identified gaps to ensure patient and staff safety at healthcare facilities.
Analysis of ERP Implementation in Perum BULOG with Extended TAM 3 Approach

Several previous studies explained that the implementation of an integrated information system needed to be realized at Perum BULOG because the old system has not been integrated. This was also realized by the management of Perum BULOG by carrying out one of its long-term plans, namely carrying out the implementation of ERP system in 2020. On the other hand, ERP is a complex system because ERP systems often adds more difficulties to the implementation process. Therefore, it is necessary to conduct research on the analysis of ERP implementation at Perum BULOG to see how ERP users will accept this technology using the extended TAM 3 approach. Outer Model and Inner Model are used to test and analyze data from research instruments using the SMART PLS 3.0. Based on the research findings, it can be seen from 12 research hypotheses, 9 research hypotheses were accepted and 3 were rejected. It is known that perceived usefulness is found only factor in system- technology ERP and perceived ease of use which have a positive and significant correlation. Meanwhile, the perceived ease of use factor was found only the organization process characteristic and system-technology ERP factor that had a positive and significant correlation. Furthermore, the attitude factor of ERP user is influenced by the perceived usefulness and perceived ease of use. Where the ERP user attitude factor is able to encourage behavioral intention and have implication for use and user satisfaction.
Examining Catherine of Siena’s controversial discernments about papal politics

Catherine of Siena (1347–1380) contributed important wisdom to Christian spirituality on discernment, yet her own discernment regarding her engagement in papal politics has not been studied. From the perspective of Christian spirituality studies, this article examines the critical text of her letters in relationship with historical events to offer a description of the instances where Catherine’s discernment differed from that of others committed to a spiritual journey and to seeking the good of the church. Catherine’s view of God’s will regarding the papal interdict of Florence controverted that of several ecclesial leaders more likely to be right. Catherine’s advocacy for the crusade differed from the advice Birgitta of Sweden gave Gregory XI, advice corroborated by history. Two of Catherine’s spiritual mentors made decisions they discerned to be right regarding missions on which they were sent by the pope, whereas Catherine reproached them for these choices. Furthermore, Catherine was certain that the election of Urban VI had been blessed by God, whereas another saint considered Clement VII to be the true pope. The above analysis is followed by an examination of influences on Catherine’s experience of seeking and implementing God’s will, seeking to account for the divergence between her discernment and that of others. In conclusion, while Catherine was confident in her union with God and, therefore, God’s guidance, she was also influenced by her unbending beliefs about truth and by the manner these beliefs were conditioned by her personality and sociocultural context. Contribution: This article contributes to scholarship in Christian spirituality on the spirituality of Catherine of Siena and on discernment, studying Catherine of Siena’s discernment regarding papal politics where she differed from others whose discernment can be interpreted as more likely to be congruent with God’s will. The reasons for her controversial discernment are explored.
The antimicrobial effect of thyme and rosemary essential oils against Listeria monocytogenes in sous vide turkey meat during storage

The research was aimed to study the impact of sous vide thermal treatment on the microbiological quality of fresh turkey breast meat after treatment with thyme and rosemary EOs and the survival of Listeria monocytogenes on the turkey meat samples. The samples were vacuum-packed and cooked at 55 °C, 60 °C, and 65 °C for 5, 15, 30 and, 60 min. There was an amount of 5 g (5 ±0.2 g) of the sample placed in PA/PE film bags and inoculated with 100 μL of L. monocytogenes inoculum. The sample was incubated at 37 °C for 18 h after bag sealing. The samples were tested on the 1st and 3rd days of experiments. The microbiological quality of fresh turkey breast meat was assessed by the detection of total microbial counts and meat microbiota was identified by mass spectrometry using MALDI-TOF MS Biotyper (Bruker Daltonics, Germany). Microbial counts differed significantly depending on temperature and time and the microbial counts ranged from 2.21 log cfu.g-1 to 8.26 log cfu.g-1 on the 1st and 3rd day of the experiment. The study shows that the sous vide method with essential oils combination is an effective method and it can be used to protect the microbiota of turkey meat and L. monocytogens survival, however, the quality of raw material is crucial.