Miracle-dz/UniFAR-FTUs huggingface dataset:
FOR ELUCIDATING THE PHYLOGENY OF THE APICOMPLEXA

The Apicomplexa is traditionally considered to contain four clearly defined groups, but the phylogenetic relationships among these groups, and their subsequent taxonomic arrangement, are currently unclear. Here, I consider five of the important criteria that need to be met before radical taxonomic changes are made, in relation to phylogenetic analyses. Unfortunately, at least four of these criteria indicate that the prospects for elucidating the phylogeny and taxonomy of the Apicomplexa are not good in the short term. A lot more pertinent data need to be collected, both in terms of taxa sampled and genes sequenced, before any concordance among phylogenies is likely to emerge; and someone (e.g. a consortium) needs to co-ordinate the active collection and analysis of these data if any worthwhile progress is to be made.
Problems and Solutions in Applying SWAT in the Upper Midwest USA

We are applying the Soil and Water Assessment Tool (SWAT2000) to the Willow River watershed in western Wisconsin to assess the effects of land use and management changes. The Willow River drains about 735 km, much of which is agricultural land yielding substantial nonpoint-source loads of sediment and nutrients. The upper Midwest USA is a geologically young landscape with many closed drainages, intensive cultivation amid patches of forest, and expanding urban centers. Principal crops include corn, soybeans, and alfalfa typically grown in rotation to support both dairy and cash-crop operations. SWAT had problems with rotations that included alfalfa, wherein alfalfa could not be removed from the landscape once planted. Code changes to the SWAT engine were required to correct this problem. Corn yields were underestimated because of nitrogen stress due to excessive denitrification. Again, code changes allowed parameterization of the nitrification process. About 29% of the landscape drained to closed depressions; the fraction of closed drainage in each subbasin was routed to the Pond routine in SWAT and parameterized to trap all sediment and phosphorus. However, seepage from Ponds was trapped by SWAT in shallow aquifer storage and not included as groundwater recharge, and therefore did not contribute appropriately to stream baseflow. As a surrogate for this missing groundwater discharge, we disallowed Pond seepage and forced slow surficial outflow by increasing the days to reach target storage. Phosphorus loading from subbasins to the channel reaches was complicated by the addition of a subbasin chlorophyll load by SWAT. When the stream water-quality routine was activated, this chlorophyll load was apparently interpreted as algae with significant phosphorus content, and the subsequent release of this phosphorus constituted an additional load unconnected to the land-surface phosphorus budget. To avoid this extraneous phosphorus load, either the stream water-quality routine had to be deactivated, or the phosphorus content of algae had to be reduced to a negligible fraction. Subbasin sediment yields were consistently overpredicted by SWAT with default parameterization. Sediment calibration could be achieved by parameterizing the soil-loss equation to reduce erosion, or by parameterizing the channel to trap excess sediment. Despite these problems encountered during model construction and calibration, the solutions given above have resulted in workable SWAT models for our purposes. We acknowledge other members of the SWAT Midwest America Users Group (SMAUG) in identifying and solving the above problems. Some of these problems have already been addressed in SWAT2005, and we are confident that the code will continue to improve.
Relationship between Helicobacter pylori infection and pre-eclampsia among pregnant women in Ardabil

Background: Studies have shown that certain infections can increase the risk of pre-eclampsia which one of the common infections among pregnant women was H. pylori with prevalence rate of 60-70% in developing countries. The aim of this study was to investigate the association between H. pylori infection and pre-eclampsia among pregnant women. Methods: Blood and stool samples were taken from 108 women with pre-eclampsia and 108 healthy pregnant women. Blood samples analyzed by ELISA for specific antibodies against H. pylori cytotoxin associated gene A (Cag A) antigen and stool samples were studied in terms of the presence of H. pylori Cag A antigen. Collected data were analyzed using statistical methods in SPSS.20. Results: 30 cases (27.8%) of pre-eclampsia women and 34 (31.5%) of healthy women were sero-positive for Cag A antibodies that was not statistically significant difference. Whereas, 67 cases (62.4%) in the case group and 48 cases (44.4%) in the control group had Cag A antigen in stool samples that was statistically significant difference. Conclusions: Results showed that, based on detection of H. pylori antigen in stool samples, frequency of active H. pylori in women with pre-eclampsia was 1.8 times higher than the healthy women.
Beam-Scanning Lens Antenna Based on Corrugated Parallel-Plate Waveguides

A lens antenna based on dispersion characteristics of corrugated waveguide is presented for one-dimensional (1-D) beam scanning at Ka-band. The dispersion characteristics of the corrugated waveguide can be controlled by adjusting the parameters of the corrugations. Thus, the effective index of refraction of the corrugated waveguide can be designed to realize the required phase delay to transform cylindrical waves into plane waves. A five-element linear array of waveguide slot antennas is used to feed the corrugation lens for multiple beam scanning. The measured aperture efficiency of the lens antenna is above 60% for the on-axis beam from 30 to 32 GHz. The resulting –3 dB coverage of the designed lens antenna is ±14.1° at 30 GHz.
Online structure-based screening of purchasable approved drugs and natural compounds: retrospective examples of drug repositioning on cancer targets

Drug discovery is a long and difficult process that benefits from the integration of virtual screening methods in experimental screening campaigns such as to generate testable hypotheses, accelerate and/or reduce the cost of drug development. Current drug attrition rate is still a major issue in all therapeutic areas and especially in the field of cancer. Drug repositioning as well as the screening of natural compounds constitute promising approaches to accelerate and improve the success rate of drug discovery. We developed three compounds libraries of purchasable compounds: Drugs-lib, FOOD-lib and NP-lib that contain approved drugs, food constituents and natural products, respectively, that are optimized for structure-based virtual screening studies. The three compounds libraries are implemented in the MTiOpenScreen web server that allows users to perform structure-based virtual screening computations on their selected protein targets. The server outputs a list of 1,500 molecules with predicted binding scores that can then be processed further by the users and purchased for experimental validation. To illustrate the potential of our service for drug repositioning endeavours, we selected five recently published drugs that have been repositioned in vitro and/or in vivo on cancer targets. For each drug, we used the MTiOpenScreen service to screen the Drugs-lib collection against the corresponding anti-cancer target and we show that our protocol is able to rank these drugs within the top ranked compounds. This web server should assist the discovery of promising molecules that could benefit patients, with faster development times, and reduced costs and risk.
Low Overhead Weighted-Graph-Coloring-Based Two-Layer Precoding for FDD Massive MIMO Systems

A massive multiple-input multiple-output (MIMO) system, operating in Frequency Division Duplexing (FDD) mode of operation, suffers from prohibitively high overhead associated with downlink channel state information (CSI) acquisition and downlink precoding, due to the lack of uplink/downlink channel reciprocity. In this paper, a heuristic edge-weighted vertex-coloring based pattern division (EWVC-PD) scheme is proposed to alleviate the overhead of a two-layer precoding approach, in a practical scenario where the user clusters undergo serious angular-spreading-range (ASR) overlapping. Specifically, under a constraint of limited number of subchannels, an undirected edge-weighted graph (EWG) is firstly constructed, to depict the potential ASR overlapping relationship among clusters. Then, inspired by classical graph coloring algorithms, we develop the EWVC-PD scheme which mitigate the ASR by subchannel orthogonalization between clusters possessing serious ASR overlapping, and multiplexing the ones having slight ASR overlapping. Simulation results reveal that our scheme efficiently outperforms the existing pattern division schemes.
Research on the Detection of Capacity and Capacity Fading of Li-Ion Battery of Electric Vehicles Based on Tomographic Imaging

It is difficult for us to use the conventional detecting method to obtain the capacity and fading of electric vehicle Li-ion battery in real-time, nondestructively and quickly. To solve the problem, the lithium iron phosphate (LFP) batteries are regarded as the research objects to study the relationship between their electrochemical performance and the structural parameters of theirs active materials based on Faraday's law, which reflects the relationship between capacity of a battery and the mass of its active materials. A capacity and fading detecting method of Li-ion battery based on tomographic imaging is proposed. A capacity and fading detecting system of Li-ion battery is established to carry out experiments with a batch of LFP batteries. The experimental results show that the actual capacity of a Li-ion battery is related to the total number of pixels of the active materials in its cross-sectional image, and the loss of its negative active materials is more than that of its positive active materials, when its capacity loses. Compared with the conventional methods, this method is superior in terms of being real-time, nondestructive and quick.
A Circularly Polarized Frequency Beam-Scanning Antenna Fed by a Microstrip Spoof SPP Transmission Line

In this letter, a planar frequency beam-scanning antenna with a circularly polarized (CP) radiation property is proposed. The beam scans along the narrow side and in lateral plane of the antenna. The antenna consists of two layers: Eight periodic symmetrical patches are presented on the top layer as radiation elements to generate CP beam, while microstrip spoof surface plasmon polariton transmission line is used as the feeding line, which improves the beam scanning range. The antenna has been fabricated and measured to verify the theory analysis. Measured results indicate that the main beam scans from –5° to +37° in a lateral plane within the operating frequency band from 12 to 16.5 GHz, of which an excellent CP characteristic is also realized. The peak gain of the antenna is about 9.5 dBi over the whole band.
Diversity and abundance of epibiota on invasive and native estuarine gastropods depend on substratum and salinity

Our understanding of variation in epibiota communities remains incomplete. This study relates such variability to multiple concurrent environmental factors. Specifically we determined the relative importance of salinity, depth, wave exposure, habitat and ‘shell type’ (shell type combined species, size, morphology and mobility traits) for community structure of sessile epibiota on gastropods in the Swan River Estuary, Australia. We quantified distribution, biofouling patterns, and detailed epibiota community structures on gastropod species in the estuary – the native Nassarius pauperatus and Bedeva paiva and the invasive Batillaria australis. The invasive Batillaria was much more abundant, and more biofouled, than any of the native species, thereby supporting orders of magnitude more epibiota in the estuary. Generalised linear models were used to partition variation in richness and abundance of epibiota among the above listed factors. Of the five factors were only shell type and salinity significant in 9 of 14 models. These results highlight (1) that a single invasive species can alter epibiota communities on a large system-wide scale, (2) an overwhelming importance of shell type and salinity in explaining estuarine epibiota communities, and (3) that additional environmental factors need to be included in future studies to improve predictive models of distribution for epibiota communities.
An assessment of global net irrigation water requirements from various water supply sources to sustain irrigation: rivers and reservoirs (1960–2050)

Water supply sources for irrigation (e.g. rivers and reservoirs) are critically important for agricultural productivity. The current rapid increase in irrigation water use is considered unsustainable and threatens food production. In this study, we estimated the time-varying dependence of irrigation water requirements from water supply sources, with a particular focus on variations in irrigation area during past (1960–2001) and future (2002–2050) periods using the global water resources model, H08. The H08 model can simulate water requirements on a daily basis at a resolution of 1.0° × 1.0° latitude and longitude. The sources of irrigation water requirements in the past simulations were specified using four categories: rivers (RIV), large reservoirs (LR) with a storage capacity greater than 1.0 × 10 9 m 3 , medium-size reservoirs (MSR) with storage capacities ranging from 1.0 × 10 9 m 3 to 3.0 × 10 6 m 3 , and non-local non-renewable blue water (NNBW). The simulated results from 1960 to 2001 showed that RIV, MSR and NNBW increased significantly from the 1960s to the early 1990s globally, but LR increased at a relatively low rate. After the early 1990s, the increase in RIV declined as it approached a critical limit, due to the continued expansion of irrigation area. MSR and NNBW increased significantly, during the same time period, following the expansion of the irrigation area and the increased storage capacity of the medium-size reservoirs. We also estimated future irrigation water requirements from the above four water supply sources and an additional water supply source (ADD) in three future simulation designs; irrigation area change, climate change, and changes in both irrigation area and climate. ADD was defined as a future increase in NNBW. After the 2020s, MSR was predicted to approach the critical limit, and ADD would account for 11–23% of the total requirements in the 2040s.
Impact of Load Balancing on Rate Coverage Performance in Millimeter Wave Cellular Heterogeneous Networks

We conduct novel analysis to assess the impact of load balancing on the rate coverage performance in a millimeter wave (mmWave) cellular heterogeneous network (HetNet) with a macro-tier and a micro- tier. To ensure the generality of our analysis, we adopt the Poisson point process for the location of base stations (BSs) and user equipments, the line- of-sight ball model for mmWave links, the sectored antenna model for key antenna array characteristics, and Nakagami-m fading for wireless channels. We first analyze the loads of macro- and micro-tier BSs, based on which we derive a new expression for the rate coverage probability of the network. Through numerical results, we demonstrate the correctness of our analysis. In addition, we thoroughly examine the impact of load balancing and various network parameters on the rate coverage probability in various scenarios, offering valuable guidelines into the design of practical mmWave HetNets.
Power Allocation for Channel Estimation and Energy Beamforming in Wirelessly Powered Sensor Networks

Wirelessly powered sensor networks (WPSNs) are becoming increasingly important to monitor many internet-of-things systems. In these WPSNs, dedicated base stations (BSs) with multiple antennas charge the sensor nodes without the need of replacing their batteries thanks to two essential procedures: i) getting of the channel state information of the nodes by sending pilots, and based on this, ii) performing energy beamforming to transmit energy to the nodes. However, the BSs have limited power budget and thus these two procedures are not independent, contrarily to what is assumed in some previous studies. In this paper, we investigate the novel problem of how to optimally allocate the power for channel estimation and energy transmission. Although the problem is non-convex, we provide a new solution approach and a performance analysis in terms of optimality and complexity. We also provide a closed form solution for the case where the channels are estimated based on a least square estimation. The simulations show a gain of approximately $10\%$ in allocating the power optimally, and the importance of improving the channel estimation efficiency.
Design of the Filtering Power Divider With a Wide Passband and Stopband

The planar power divider with a wide passband/ stopband and filtering characteristics is proposed in this letter. In order to increase the slope rate around the passband skirt, the modified parallel-coupled bandpass filter is adopted. Moreover, utilizing the stub-loaded resonator within the filter, a wide passband can be achieved. Furthermore, the stopband bandwidth and attenuation can be extended with the stepped-impedance coupled lines. An exemplary design of the filtering power divider operated at 2 GHz is presented. In addition, the measured fractional bandwidth at 3 dB and attenuation in the stopband are 57.1% and 40 dB, respectively.
Relationship Between Rhinitis, Asthma, and Eczema and the Presence of Sensitization in Young Swiss Adults

Background Rhinitis is a very common disease with allergies being the most frequent causative factor. It can co-occur together with asthma and eczema in atopic as well as in nonatopic patients. Objectives To assess the prevalence of allergic sensitization within patient groups with rhinitis in consideration of the co-occurring disorders of asthma and eczema. Methods Students of the third year of medical school completed an anonymous questionnaire on age, gender, and clinical symptoms, such as seasonal rhinitis, perennial rhinitis, asthma, and eczema, and underwent an ImmunoCAP Rapid test. We calculated the prevalence of sensitization within subgroups of patients reporting allergic disorders, such as rhinitis, asthma, and eczema. Results Questionnaires and ImmunoCAP Rapid tests of 1513 medical students were analyzed. The participants’ self-reported presence of seasonal/perennial rhinitis, asthma, and eczema was compared to the presence of sensitization. Data of 1467 subjects could be analyzed. Seasonal rhinitis was the most common symptom, followed by eczema, asthma, and perennial rhinitis. The participants were differentiated into 16 subgroups according to the combined clinical manifestations of the different symptoms and association to sensitization within subgroups. The prevalence of sensitization ranged from 18% in subjects reporting only eczema without any other symptom to 100% in those reporting to have asthma, seasonal/perennial rhinitis, and eczema together. In subjects reporting no sign or symptom at all, the prevalence of sensitization was 19%. Seasonal rhinitis was the strongest single predictor for sensitization with the highest proportion of sensitized participants in all symptom combinations (67%–100%), followed by perennial rhinitis (31%–100%), asthma (30%–100%), and eczema (18%–100%). Conclusion Rhinitis most often is associated with allergen sensitization, and the probability of sensitization is substantially enhanced by co-occurrence of asthma. A careful assessment of clinical signs and symptoms is important and enables the selection of patients in whom targeted diagnostic analysis and therapy is appropriate. Trial registration: retrospectively registered by the Cantonal Ethics Committee Zurich on 22.01. 2016; Nr: 08-2016.
Joint Neural Network Equalizer and Decoder

Recently, deep learning methods have shown significant improvements in communication systems. In this paper, we study the equalization problem over the nonlinear channel using neural networks. The joint equalizer and decoder based on neural networks are proposed to realize blind equalization and decoding process without the knowledge of channel state information (CSI). Different from previous methods, we use two neural networks instead of one. First, convolutional neural network (CNN) is used to adaptively recover the transmitted signal from channel impairment and nonlinear distortions. Then the deep neural network decoder (NND) decodes the detected signal from CNN equalizer. Under various channel conditions, the experiment results demonstrate that the proposed CNN equalizer achieves better performance than other solutions based on machine learning methods. The proposed model reduces about 2/3 of the parameters compared to state-of-the-art counterparts. Besides, our model can be easily applied to long sequence with $\mathcal{O}(n)$ complexity.
Improving Service Availability of Cloud Systems by Predicting Disk Error

High service availability is crucial for cloud systems. A typical cloud system uses a large number of physical hard disk drives. Disk errors are one of the most important reasons that lead to service unavailability. Disk error (such as sector error and latency error) can be seen as a form of gray failure, which are fairly subtle failures that are hard to be detected, even when applications are afflicted by them. In this paper, we propose to predict disk errors proactively before they cause more severe damage to the cloud system. The ability to predict faulty disks enables the live migration of existing virtual machines and allocation of new virtual machines to the healthy disks, therefore improving service availability. To build an accurate online prediction model, we utilize both disk-level sensor (SMART) data as well as system level signals. We develop a cost-sensitive ranking-based machine learning model that can learn the characteristics of faulty disks in the past and rank the disks based on their error-proneness in the near future. We evaluate our approach using real-world data collected from a production cloud system. The results confirm that the proposed approach is effective and outperforms related methods. Furthermore, we have successfully applied the proposed approach to improve service availability of Microsoft Azure.
Cyclic di-GMP integrates functionally divergent transcription factors into a regulation pathway for antioxidant defense

Abstract Cyclic diguanylate monophosphate (c-di-GMP) is a global signaling molecule that modulates diverse cellular processes through its downstream receptors. However, no study has fully clarified the mechanisms by which c-di-GMP organizes functionally divergent regulators to drive the gene expression for coping with environmental stress. Here, we reported that c-di-GMP can integrate two functionally opposite receptor transcription factors, namely, LtmA and HpoR, into a pathway to regulate the antioxidant processes in Mycobacterium smegmatis. In contrast to HpoR, LtmA is an activator that positively regulates the expression of redox gene clusters and the mycobacterial H2O2 resistance. LtmA can physically interact with HpoR. A high level of c-di-GMP stimulates the positive regulation of LtmA and boosts the physical interaction between the two regulators, further enhancing the DNA-binding ability of LtmA and reducing the inhibitory activity of HpoR. Therefore, upon exposure to oxidative stress, c-di-GMP can orchestrate functionally divergent transcription factors to trigger antioxidant defense in mycobacteria. This finding presents a noteworthy example of how a bacterium remodels its transcriptional network via c-di-GMP in response to environmental stress.