Miracle-dz/UniFAR-FTUs huggingface dataset:
Cardenolide Increase in Foxglove During Stresses Corresponds to Cholesterol and Phytosterol Biosynthesis

Cardenolides are a group of steroidal metabolites found in Digitalis lanata with potent cardioactive effects on animals. In plants, cardenolides are involved in various stress responses. However, the molecular mechanism of cardenolide increase during stresses is mostly unknown. Here we show that cardenolides were increased upon methyl jasmonate (MJ), sorbitol, potassium (KCl) chloride, and salicylic acid analog (BTH: 2,1,3-benzothiadiazole) treatments. However, the expression of three known genes for cardenolide biosynthesis did not correlate well with these increases. Specifically, the expression of progesterone-5β-reductases (P5βR and P5βR2) did not correlate with cardenolide increase. The expression of 3β-hydroxysteroid dehydrogenase (3βHSD) correlated with cardenolide levels only during the BTH treatment. Mining the D. lanata transcriptome identified genes involved in cholesterol and phytosterol biosynthesis: SSR1 (sterol sidechain reductase), SMO1, and SMO3 (sterol methyl oxidase). Surprisingly, the expression of all three genes correlated well with the cardenolide increase after BTH treatment. Phylogenetic analysis showed that SSR1 is likely involved in both cholesterol and phytosterol biosynthesis. In addition, SMO1 is likely specific to phytosterol biosynthesis, and SMO3 is specific to cholesterol biosynthesis. These results suggest that both cholesterol and phytosterol are involved in cardenolide biosynthesis. In summary, this work shows that cardenolides are important for stress responses in D. lanata and revealed a novel relationship between phytosterol and cardenolide biosynthesis.
Avian haemosporidians (Plasmodium and Haemoproteus) status in selected bird groups (Old world Flycatchers, Warblers, Babblers, and Thrushes) of India and their phylogenetic relationships with other lineages of the world

The avian haemosporidians (Plasmodium and Haemoproteus) are widely distributed and may affect the host populations from body damage at individual level to the extinction of a population. The knowledge about their status may help in future avifauna conservation plans. Hence, we examined the avian haemosporidians status, in selected bird groups (Old world Flycatchers, Warblers, Babblers, and Thrushes) of India, and their phylogenetic relationships with other known lineages of the world. We used the common genetic marker (Cytochrome b gene fragment of 479 bp) with information on the geographic distribution of parasite and host species available at MalAvi database. The prevalence of avian haemosporidians, from northern, eastern, and southern parts of India and phylogenetic genetic analysis of lineages was carried out to know the genetic relatedness among them at local and world level. The MCC tree revealed six Haemosporidian lineages in which one was common (H_MSP01) and five were unique (H_CYOPOL01, H_CHD01, H_CYORUB01, H_EUMTHA01, and P_GEOCIT01). The avian host richness Index was 2.0852. 9.9%, prevalence of Haemosporidian infection was found in 111 DNA samples belonging to 6 host species. The Haemoproteus prevalence was found to be 9.0 % across five host species (Phylloscopus trochiloides, Cyornis poliogenys, C. hainanus dialilaemus, C. rubeculoides, Eumiyas thalassinus) and Plasmodium prevalence was 0.9% in Geokichla citrina. Spatial phylogeny at global level showed H_MSP01 lineage, found in different host species in India, was genetically related to H. pallidus lineages (COLL2 and PFC1) in parts of Africa, Europe, North America, Malaysia, and Philippines. The Plasmodium lineage (P_GEOCIT01) was related to PADOM16 in Egypt with poor sequence similarity (93.89%). The statistical analysis suggested that the haemosporidian’s host species distribution range was directly and significantly associated with the altitude, minimum temperature, and relative humidity. H_MSP01 distribution was in accordance with H. pallidus having a wide geographic and host range.
The interplay of supercoiling and thymine dimers in DNA

Thymine dimers are a major mutagenic photoproduct induced by UV radiation. While they have been the subject of extensive theoretical and experimental investigations, questions of how DNA supercoiling affects local defect properties, or, conversely, how the presence of such defects changes global supercoiled structure, are largely unexplored. Here we introduce a model of thymine dimers in the oxDNA forcefield, parametrised by comparison to melting experiments and structural measurements of the thymine dimer induced bend angle. We performed extensive molecular dynamics simulations of double-stranded DNA as a function of external twist and force. Compared to undamaged DNA, the presence of a thymine dimer lowers the supercoiling densities at which plectonemes and bubbles occur. For biologically relevant supercoiling densities and forces, thymine dimers can preferentially segregate to the tips of the plectonemes, where they enhance the probability of a localized tip-bubble. This mechanism increases the probability of highly bent and denatured states at the thymine dimer site, which may facilitate repair enzyme binding. Thymine dimer-induced tip-bubbles also pin plectonemes, which may help repair enzymes to locate damage. We hypothesize that the interplay of supercoiling and local defects plays an important role for a wider set of DNA damage repair systems.
miPEP858/miR858-MYB3-PSK4 module regulates growth and development in Arabidopsis

Small molecules, peptides and miRNAs, are the crucial regulators of plant growth. Here, we show the importance of cross-talk between miPEP858a/miR858a and Phytosulfokine (PSK4) in regulating plant growth and development in Arabidopsis. Genome-wide expression analysis suggested modulated expression of PSK4 in miR858 mutant and overexpression, miR858OX, plants. The silencing of PSK4 in miR858OX plants compromised the growth, whereas over-expression of PSK4 in miR858 mutant rescued the developmental defects. The exogenous application of synthetic PSK4 further complemented the plant development in mutant plants. Exogenous treatment of synthetic miPEP858a in PSK4 mutant led to clathrin-mediated internalization of the peptide however did not enhance growth as in the case of wild-type plants. We also demonstrate that the MYB3 is an important molecular component participating in miPEP858a/miR858a-PSK4 module. Finally, our work highlights the signalling between miR858/miPEP858-MYB3-PSK4 in modulating the expression of key elements involved in auxin responses leading to the regulation of growth. One-sentence summary Signaling network between small molecules, miPEP858a/miR858a and phytosulfokine, regulates plant growth in Arabidopsis.
In-silico analysis: common biomarkers of NDs

Neurodegenerative disorders (NDs) are a class of rapidly rising devastating diseases and the reason behind are might be an improper function of related genes or a mutation in a particular gene or even could be autoimmune also. Parkinson’s disease (PD), Multiple sclerosis (MS), Huntington’s disease (HD) are some of the NDs, and still, incurable fully. Apart from the similarities in symptoms, there are common genes that express somehow a differential manner in patients of PDs, MSs, and HDs. A total of 1197 differentially expressed genes (DEGs) are obtained by analyzing the chosen datasets. The protein interactions by STRING online tool and degree sorted hubs obtained through a plug-in in Cytoscape; Cyto-Hubba. Among the sorted hubs KRAS, CREB1, PIK3CA, JAK2 are the ones that are not only common to all the studied datasets of NDs but also in other neurological disorders like Alzheimer’s. The enriched pathways with biological process, molecular function, cellular component, and KEGG pathway details are obtained and analyzed using Enricher. This paper frames that the obtained hub genes could be potential biomarkers also and a need for further drug design for finding a possible cure.
SIN-Like Pathway Kinases Regulate the End of Mitosis in the Methylotrophic Yeast Ogataea polymorpha

The Mitotic exit network (MEN) is a conserved signalling pathway essential for termination of mitosis in the budding yeast Saccharomyces cerevisiae. All MEN components are highly conserved in the methylotrophic budding yeast Ogataea polymorpha, except for Cdc15 kinase. Amongst O. polymorpha protein kinases that have some similarity to ScCdc15, only two had no other obvious homologues in S. cerevisiae and these were named OpHCD1 and OpHCD2 for homologue candidate of ScCdc15. A search in other yeast species revealed that OpHcd2 has an armadillo type fold in the C-terminal region as found in SpCdc7 kinases of the fission yeast Schizosaccharomyces pombe, which are homologues of ScCdc15; while OpHcd1 is homologous to SpSid1 kinase, a component of the Septation Initiation Network (SIN) of S. pombe not present in the MEN. Since the deletion of either OpHCD1 or OpHCD2 resulted in lethality under standard growth conditions, conditional mutants were constructed by introducing an ATP analog sensitive mutation. For OpHCD2, we constructed and used new genetic tools for O. polymorpha that combined the Tet promoter and the improved auxin-degron systems. Conditional mutants for OpHCD1 and OpHCD2 exhibited significant delay in late anaphase and defective cell separation, suggesting that both genes have roles in mitotic exit and cytokinesis. These results suggest a SIN-like signalling pathway regulates termination of mitosis in O. polymorpha and that the loss of Sid1/Hcd1 kinase in the MEN occurred relatively recently during the evolution of budding yeast.
A Low Cost Front-End Converter With Maximum Power per Ampere for Rooftop Wind Turbines

Small Permanent Magnet Synchronous Generators (PMSGs) are widely used in small rooftop wind turbines. In order to inject the electric power generated by the PMSG, into the grid, a back-to-back AC/DC/AC converter is required. In this paper, a low cost with high efficiency converter is proposed for the rectifier stage to obtain the maximum power per ampere of PMSG. This structure based on Discontinuous Conduction Mode Single-Ended Primary Inductor Converter (DCM SEPIC) with a single power electronic switch, proposes a converter which is cost-effective and suitable for the small wind turbine used in residential applications. Furthermore, other advantages of the proposed converter include obtaining maximum power delivered per ampere using a simple control method and reducing the size of converter inductive filter by exploiting the PMSG internal synchronous reactance as part of the filter. Unlike the conventional DCM Boost rectifiers, the proposed converter has a continuous input current, which results in lower PMSG conduction loss. Operation principles and various operating modes of this converter are discussed in detail in this paper and verified by closed-loop simulation and experimental results for a 500W/200V prototype.
Exploring Impact Factors of Risk Contagion in Venture Capital Markets: A Complex Network Approach

Large-scale risk events in the venture capital (VC) market can easily lead to systemic risk in the financial market. This paper collects the comprehensive dataset of Chinese VC market from 1999 to 2020, and constructs the multi-layer networks of VC market. After that, a risk contagion model of venture capital market is designed considering both the capital loss transmission and social relations effect (investor herd behavior). By simulating various situations with different risk origins and scales, the speed of risk contagion and the total impacts on the overall stability of the market (network) are compared. We find that the herd behavior of the market will generally aggravate the consequences of risk contagion. Compared with unicorns, the failure of a leading VC firm can cause a wider range of risk contagion. The contagion consequences caused by the failure of random financing companies are more serious than those caused by random VC firms. Moreover, we identify that telecommunications services and information technology are high-risk industries in VC market. Based on the empirical results, this article provides policy implications for the market regulatory sectors to prevent VC market risks.
Voltage Stability Enhancement of the Uganda Power System Network

The unprecedented growth in demand and drive towards deregulation has brought about a complex and constantly changing grid. More so, with the current environmental and economic pressures, there's a reported growing number of numerous transmission and distribution investment deferrals, especially in developing countries. As such, the power system networks are being operated in stressed conditions. Hence, the networks are more prone to voltage instability, and consequently, collapse. Uganda is no exception to these challenges. Thus, a voltage stability assessment of the network is paramount. This research employs the use of Continuation Power Flow (CPF) for the identification of weak regions. Corresponding PV and QV Curves for these buses are also provided to further buttress candidate buses for reactive power compensation. The impact of Static Synchronous Compensators (STATCOMs) on network voltage stability under contingency and fault conditions is also investigated. The results show that with the intervention of STATCOM, an imminent voltage collapse was avoided both during and after fault with bus voltages all restored to normal after incorporation of STATCOM.
Dynamic Simulation of Distribution Power Systems with Distributed Renewable Generation

The increased quantity and installed capacity of renewable energy generation at the distribution power system and their impact in the behavior of such network becomes a very relevant topic for planning and operating the grid. It is expected that the number of these distributed facilities continue to grow. By consequence, it is important to simulate and analyze the dynamic performance of the distribution network with Distributed Generation Units (DGs). This paper presents an example of a MATLAB/SIMULINK and RT-LAB-based dynamic simulation of an unbalanced distribution system and the integration of DGs. The IEEE 37 Node Test Feeder has been modified by connecting three DGs at different buses and by modeling the consumption with dynamic load profiles. The objective is to analyze this benchmark and the convenience of individual models of DGs and of the load to evaluate the dynamic performance of the system.
Android Malware Detection Based on Composition Ratio of Permission Pairs

Detecting Android malware is imperative. Among various detection schemes, permission pair based ones are promising for practical detection. However, conventional schemes cannot simultaneously meet requirements for practical use in terms of efficiency, intelligibility, and stability of detection performance. Although the latest scheme relies on differences of frequent pairs between benign apps and malware, it cannot meet the stability. This is because recent malware tends to require unnecessary permissions to imitate benign apps, which makes using the frequencies ineffective. To meet all the requirements, in this paper, we propose Android malware detection based on a Composition Ratio (CR) of permission pairs. We define the CR as a ratio of a permission pair to all pairs in an app. We focus on the fact that the CR tends to be small in malware because of unnecessary permissions. To obtain features without using the frequencies, we construct databases about the CR. For each app, we calculate similarity scores based on the databases. Finally, eight scores are fed into machine learning (ML) based classifiers as features. By doing this, stable performance can be achieved. Since our features are just eight-dimensional, the proposed scheme takes less training time and is compatible with other ML based schemes. Furthermore, our features can quantitatively offer clear information that helps human to understand detection results. Our scheme is suitable for practical use because all the requirements can be met. By using real datasets, our results show that our scheme can detect malware with up to 97.3% accuracy. Besides, compared with an existing scheme, our scheme can reduce the feature dimensions by about 99% with maintaining comparable accuracy on recent datasets.
Design and Implementation of Compliance Tests and Evaluation for a 37 kW Induction Motor based on South African and International Standards

The induction motor is one of the most important motors used in industrial applications. It is used to convert electrical energy into mechanical energy. The aim of this study is to test and evaluate a 37 kW induction motor that is manufactured and sold in South Africa in terms of its compliance with South African National Standards (SANS 1804-1/2) and international standards (e.g., IEC 60034 series). In this study, the test procedures are first designed and a test set-up built to test and evaluate the test motor. The tests and evaluation are conducted at the explosion prevention technology and rotating machines (EPT&RM) laboratory, SABS, South Africa. The design of test procedures is based on quality, performance, ratings and safety of the test induction motor, which ensures the motor is not only safe for end-users but is in compliance with South African and international standards. The study is aimed at reducing injuries and breakdowns caused by non-complying induction motors especially in mining industries.
Investigation of the Current of P3HT: PCBM-Based Organic Solar Cell Extracting the Spatial Recombination Coefficient of the Active Layer

The current of P3HT:PCBM-based organic solar cells was analytically investigated in this work. Position-and wavelength-dependent excitons generated by light were evaluated using the optical transfer matrix method. The charge carriers generated by dissociating excitons were estimated using an improved dissociation probability, incorporating a Gaussian distribution. A universal analytical equation was derived by solving the transport equation to calculate the current-producing holes and electrons. Similarly, another universal equation was derived to calculate the hole and electron currents. The total current, calculated using a constant recombination coefficient, is found to be different at different positions (position dependent), which is inconsistent because the total current should be position independent. The use of a constant recombination coefficient is the reason for this inconsistent result. The spatial recombination coefficients inside the active layer were extracted and used in the calculation, and the total current was found to be position independent; thus, the inconsistency was resolved. The current and its components have been investigated with respect to position, terminal voltage, solar irradiance, active layer thickness and wavelength. This work provides better results because it includes spatial recombination coefficients, space-and wavelength-dependent excitons, and improved dissociation probability in analytical calculations; therefore, it will help improve the prediction and design of organic solar cells.
An Energy Management System for Disaster Resilience in Islanded Microgrid Networks

As disasters continue to become common around the world, the reliability of power systems is increasingly becoming critical. Researchers continue to explore the inclusion of distributed energy resources (DERs), specifically smart microgrids, into traditional power system designs to improve their reliability. Smart microgrids possess characteristic advantages of energy storage, off-grid operation, and control flexibility. In this regard, we explore load shedding of noncritical loads as a solution to extend the uptime of a group of interconnected microgrids that have been islanded after a disaster. Load shedding and Photovoltaic (PV) Curtailment are implemented as an addition to our previously proposed energy management systems (EMS) for each prosumer (PR) in the network. The proposed method shows that the proposed control methods can prolong uptime in the interconnected off-grid network of microgrids
Fault Location Detection in Underground Cables based on Wavelet-ANFIS Approach

Due to the difficulties experienced in identifying the exact location of underground cable faults, it is therefore evident that there is a need to employ optimal methods that will have the capability to swiftly identify the fault location and henceforth reduce the downtime of the system. This paper presents a study that combines both Wavelet Transform and Adaptive Neuro-Fuzzy Inference System (ANFIS) technique for fault location in underground cables. A 9 km, 11 kV, 50 Hz transmission line was developed, and a single line to ground fault was simulated at different line locations. The wavelet transform was used to extract noteworthy features that were subsequently utilised as inputs for training and testing the Adaptive Neuro-Fuzzy Inference System (ANFIS). The results obtained from the ANFIS were compared with the actual simulated test values. From the results obtained, the technique was able to achieve a 99.94% accuracy in fault location.
On Efficient DCT Type-I Based Low Complexity Channel Estimation for Uplink NB-IoT Systems

Channel estimation is a challenging and timely issue for the 3rd Generation Partnership Project (3GPP) standardized low power wide-area network technology named narrowband Internet of Things (NB-IoT). Channel estimation is crucial to achieve extended radio coverage, energy efficiency, coherent detection, and channel equalization for signal repetition dominated NB-IoT uplink transmission. The NB-IoT inherits simplified baseband radio frequency processing, physical channels, reference signal structure, and numerology from existing Long Term Evolution (LTE) systems to save power and costs. Thus, channel estimation methods extensively employed in LTE systems may not be applied to the NB-IoT uplink systems. In this paper, efficient discrete cosine transform type-I (DCT-I)-based transform-domain channel estimation approaches are proposed by modifying the original definition of DCT-I. The proposed methods can mitigate the problems experienced in the discrete Fourier transform (DFT)-based channel estimation, such as signal aliasing error, and border effect. The proposed approaches improve channel estimation precision by reducing signal distortion from the high-frequency region in the time-domain when non-sample-spaced path delays exist in multipath fading channels. Signal aliasing error experienced from the virtual subcarriers is also minimized with the anticipated schemes. The proposed methods are applied on simple least squares (LS) estimates in time-domain to eliminate estimation noise. The viability of the proposed estimators is verified as compared to the conventional LS, DFT-based de-noising LS, and standard DCT-I based methods through extensive numerical simulations. Based on the numerical simulations, the proposed estimators show better mean square error and bit error rate performances than their competitors in extremely low coverage conditions.
Rotation Tolerant Finger Vein Recognition using CNNs

Finger vein recognition deals with the recognition of subjects based on their venous pattern within the fingers. The majority of the available systems acquire the vein pattern using only a single camera. Such systems are susceptible to misplacements of the finger during acquisition, in particular longitudinal finger rotation poses a severe problem. Besides some hardware based approaches that try to avoid the misplacement in the first place, there are several software based solutions to counter fight longitudinal finger rotation. All of them use classical hand-crafted features. This work presents a novel approach to make CNNs robust to longitudinal finger rotation by training CNNs using finger vein images from varying perspectives.