Miracle-dz/UniFAR-FTUs huggingface dataset:
A high power 2-18 GHz T/R switch

A high-power 2-18-GHz T/R (transmit/receive) switch monolithic microwave IC (MMIC) has been developed for use in broadband T/R modules. This switch has a power handling of better than 35 dBm (3.2 W), 8-dB higher than any previously reported broadband switch. A combination of techniques was used to yield higher power handling while preserving low loss and high isolation. These circuit techniques include an asymmetrical design of the transmit and receive arms, the use of dual-gate FETs for handling large voltages, and the use of large FET peripheries for handling large currents. The use of dual-gate FETs in place of a stack of individual FETs reduces the device area, with a resulting reduction in parasitic series inductance through the FET and in shunt capacitance from the FET to ground. Power handling is somewhat lower for the dual-gate FET than for conventional stacked FETs, since RF voltage cannot be distributed as uniformly across the gates. Offstate capacitance is higher for a dual-gate FET than for a stacked FET, since the close proximity of the elements leads to additional parasitic capacitances. <<ETX>>
BAYESIAN EVALUATION OF BIOMARKERS AS SURROGATE ENDPOINTS AND ITS APPLICATION IN LONG-TERM EFFECTS OF SKIN LESIONS DUE TO MUSTARD GAS

The paper aims at undertaking a Bayesian evaluation of surrogate endpoints which has the potential to decrease the exposure of patients while at the same time being cost-effective. As such, the current research, with an individual-level evaluation, intends to introduce a new Bayesian criterion based on some of the previous research works. Taking into account the surrogate and the true endpoint variables, the statistics that derived for the exponential family of distributions particularly is for a binomial one. In due process, the paper shows the relationship between the Bayesian likelihood reduction factor (LRFB) and its frequentist counterpart (LRF). Finally, to show some intuition in the nature of LRFB, it has been applied in a multi-center simulation and a uni-center real example. In real data, LRFB is carried out to evaluate the immunological factor IL-18 BPa Serum in the long-term effect of skin lesions of people who
Can managerialism promote organisational transformation in private universities?

Used as a method of university reform, new public management (NPM) involves an ideology of managerialism that conflicts with collegiality and causes ‘hybridisation’. In management organisations, when organisational goals are not shared at the individual level, this adjustment mechanism shifts to the organisational level. This study aimed to examine whether there are coordination mechanisms at the organisational level in universities by focussing on those in Japan, particularly private universities that require autonomous management. Multi-level analysis results revealed that although there is hybridisation associated with increased managerial pressure, there are no organisational-level mechanisms to reduce conflict. In conclusion, the authors point out the difficulty of organising private universities based on managerialism and suggests that university reform in Japan may be ‘hollowing out’ in the public sector as well. Further, the study emphasises the importance of undertaking a comparative study of governance arrangements in China’s private universities in the future.
Picture‐word order compound protein interaction: Predicting compound‐protein interaction using structural images of compounds

Identifying potential associations between proteins and compounds is significant and challenging in the drug discovery process. Existing deep‐learning‐based methods tend to treat compounds and proteins as sequences or graphs. Inspired by the rapid development of computer vision technology, we argue that more abundant characterizations can be extracted from the images of compounds than from their sequences or graphs. Therefore, we propose an interaction model named picture‐word order compound protein interaction (PWO‐CPI) which learns the representation from structural images of compounds and protein sequences by using convolutional neural network (CNN). The experiments show that PWO‐CPI outperforms state‐of‐the‐art CPI prediction models. We also perform drug–drug interaction (DDI) experiments to validate the strong potential of structural formula images of molecular structures as molecular features. In addition, with the aid of generative adversarial networks, the visualization of image features demonstrates PWO‐CPI can learn compound structural features implicitly and automatically.
Human gut bifidobacteria inhibit the growth of the opportunistic fungal pathogen Candida albicans

The human gut microbiota protects the host from invading pathogens and the overgrowth of indigenous opportunistic species via mechanisms such as competition for nutrients and by production of antimicrobial compounds. Here, we investigated the antagonist activity of human gut bacteria towards Candida albicans, an opportunistic fungal pathogen that can cause severe infections and mortality in susceptible patients. Co-culture batch incubations of C. albicans in the presence of faecal microbiota from six different healthy individuals revealed varying levels of inhibitory activity against C. albicans. 16S rRNA gene sequence profiling of these faecal co-culture bacterial communities showed that the Bifidobacteriaceae family, and Bifidobacterium adolescentis in particular, were most correlated with antagonistic activity against C. albicans. Follow up mechanistic studies confirmed that culture supernatants of Bifidobacterium species, particularly B. adolescentis, inhibited C. albicans in vitro under both aerobic and anaerobic conditions. Production of the fermentation acids acetate and lactate, together with the concomitant decrease in pH, were strong drivers of the inhibitory activity. Bifidobacteria may therefore represent attractive targets for the development of probiotics and prebiotic interventions tailored to enhance inhibitory activity against C. albicans in vivo.
Antibodies to ILT3 abrogate myeloid immunosuppression and enable tumor killing

Tumor myeloid suppressor cells impede response to T cell checkpoint immunotherapy. Immunoglobulin-like transcript 3 (ILT3, gene name, LILRB4) expressed on dendritic cells (DCs) promotes antigen-specific tolerance. Circulating monocytic MDSCs that express ILT3 have been linked to clinical outcomes and a soluble form of ILT3 is elevated in certain cancers. We find that LILRB4 expression is correlated with Gene Expression Profile of T-cell inflamed tumor microenvironment shown to be significantly associated with response to the anti-PD1 antibody pembrolizumab across several tumor types. A potent and selective anti-ILT3 mAb effectively antagonized IL-10 polarization of DCs and enabled T cell priming. In an MLR assay anti-ILT3 combined with pembrolizumab afforded greater CD8+ T cell activation compared to either agent alone. Anti-ILT3 antibodies impaired the acquisition of a suppressive phenotype of monocytes co-cultured with SK-MEL-5 cancer cells, accompanied by a reduction in surface detection of peptidase inhibitor 16, a cis interaction candidate for ILT3. Growth of myeloid cell-abundant SK-MEL-5 tumors was abrogated by ILT3 blockade and remodeling of the immune tumor microenvironment was evident by CyTOF. These data support the testing of anti-ILT3 antibodies for the treatment of a wide range of solid tumors replete with myeloid cells.
Insight into the mechanism of H+-coupled nucleobase transport

Members of the nucleobase/ascorbic acid transporter (NAT) gene family are found in all kingdoms of life. In mammals, the concentrative uptake of ascorbic acid (vitamin C) by members of the NAT family is driven by the Na+ gradient, while the uptake of nucleobases in bacteria is powered by the H+ gradient. Here we report the structure and function PurTCp, a NAT family member from Colwellia psychrerythraea. The structure of PurTCp was determined to 2.80 Å resolution by X-ray crystallography. PurTCp forms a homodimer and each protomer has 14 transmembrane segments folded into a substrate-binding domain (core domain) and an interface domain (gate domain) A purine base is present in the structure and defines the location of the substrate binding site. Functional studies reveal that PurTCp transports purines but not pyrimidines, and that purine binding and transport is dependent on the pH. Mutation of a conserved aspartate residue close to the substrate binding site reveals the critical role of this residue in H+-dependent transport of purines. Comparison of the PurTCp structure with transporters of the same structural fold suggests that rigid-body motions of the substrate-binding domain are central for substrate translocation across the membrane.
Extensive genome introgression between domestic ferret and European polecat during population recovery in Great Britain

The European polecat (Mustela putorius) is a mammalian predator which occurs across much of Europe east to the Ural Mountains. In Great Britain, following years of persecution the European polecat has recently undergone a population increase due to legal protection and its range now overlaps that of feral domestic ferrets (Mustela putorius furo). During this range expansion, European polecats hybridised with feral domestic ferrets producing viable offspring. Here we carry out population-level whole genome sequencing on domestic ferrets, British European polecats, and European polecats from the European mainland and find high degrees of genome introgression in British polecats outside their previous stronghold, even in those individuals phenotyped as ‘pure’ polecats. We quantify this introgression and find introgressed genes under selection that may assist in cognitive function and sight.
Landscape genetics across the Andes Mountains: Environmental variation drives genetic divergence in the leaf-cutting ant Atta cephalotes

Disentangling the mechanisms underlying spatial distribution of genetic variation into those due to environment or physical barriers from mere geographic distance is challenging in complex landscapes. The Andean uplift represents one of the most heterogeneous habitats where these questions remain unexplored as multiple mechanisms might interact, confounding their relative roles. We explore this broad question in the leaf-cutting ant Atta cephalotes, a species distributed across the Andes Mountains using nuclear microsatellite markers and mtCOI gene sequences. We investigate spatial genetic divergence across the Western range of Northern Andes in Colombia by testing the relative role of alternative scenarios of population divergence, including geographic distance (IBD), climatic conditions (IBE), and physical barriers due to the Andes Mountains (IBB). Our results reveal substantial genetic differentiation among A. cephalotes populations for both types of markers, but only nuclear divergence followed a hierarchical pattern with multiple models of genetic divergence imposed by the Western range. Model selection showed that IBD, IBE (temperature and precipitation), and IBB (Andes mountains) models, often proposed as individual drivers of genetic divergence, interact, and explain up to 33% of genetic divergence in A. cephalotes. IBE models remained significant after accounting for IBD, suggesting that environmental factors play a more prominent role when compared to IBB. These factors in combination with idiosyncratic dispersal patterns of ants appear to determine hierarchical patterns of gene flow. This study enriches our understanding of the forces shaping population divergence in complex habitat landscapes.
Process Engineering of Biopharmaceutical Production in Moss Bioreactors via Model-Based Description and Evaluation of Phytohormone Impact

The moss Physcomitrella is an interesting production host for recombinant biopharmaceuticals. Here we produced MFHR1, a synthetic complement regulator which has been proposed for the treatment of diseases associated to the complement system as part of human innate immunity. We studied the impact of different operation modes for the production process in 5 L stirred-tank photobioreactors. The total amount of recombinant protein was doubled by using fed-batch or batch compared to semi-continuous operation, although the maximum specific productivity (mg MFHR1/g FW) increased just by 35%. We proposed an unstructured kinetic model which fits accurately with the experimental data in batch and semi-continuous operation under autotrophic conditions with 2% CO2 enrichment. The model is able to predict recombinant protein production, nitrate uptake and biomass growth, which is useful for process control and optimization. We investigated strategies to further increase MFHR1 production. While mixotrophic and heterotrophic conditions decreased the MFHR1-specific productivity compared to autotrophic conditions, addition of the phytohormone auxin (NAA, 10 µM) to the medium enhanced it by 470% in shaken flasks and up to 230% and 260%, in batch and fed-batch bioreactors, respectively. Supporting this finding, the auxin-synthesis inhibitor L-Kynurenine (100 µM) decreased MFHR1 production significantly by 110% and 580% at day 7 and 18, respectively. Expression analysis revealed that the MFHR1 transgene, driven by the Physcomitrella actin5 (PpAct5) promoter, was upregulated 16 hours after NAA addition and remained enhanced over the whole process, whereas the auxin-responsive gene PpIAA1A was upregulated within the first two hours, indicating that the effect of auxin on PpAct5 promoter-driven expression is indirect. Furthermore, the day of NAA supplementation was crucial, leading to an up to 8-fold increase of MFHR1-specific productivity (0.82 mg MFHR1/ g fresh weight, 150 mg accumulated over 7 days) compared to the productivity reported previously. Our findings are likely to be applicable to other plant-based expression systems to increase biopharmaceutical production and yields.
Negative autoregulation mitigates collateral RNase activity of repeat-targeting CRISPR-Cas13d in mammalian cells

Cas13 is a unique family of CRISPR endonucleases exhibiting programmable binding and cleavage of RNAs and is a strong candidate for eukaryotic RNA knockdown in the laboratory and the clinic. However, sequence-specific binding of Cas13 to the target RNA unleashes non-specific bystander RNA cleavage, or collateral activity, which may confound knockdown experiments and raises concerns for therapeutic applications. Although conserved across orthologs and robust in cell-free and bacterial environments, the extent of collateral activity in mammalian cells remains disputed. Here, we investigate Cas13d collateral activity in the context of an RNA-targeting therapy for myotonic dystrophy type 1, a disease caused by a transcribed long CTG repeat expansion. We find that when targeting CUGn RNA in HeLa and other cell lines, Cas13d depletes endogenous and transgenic RNAs, interferes with critical cellular processes, and activates stress response and apoptosis pathways. We also observe collateral effects when targeting other repetitive and unique transgenic sequences, and we provide evidence for collateral activity when targeting highly expressed endogenous transcripts. To minimize collateral activity for repeat-targeting Cas13d therapeutics, we introduce gRNA excision for negative-autoregulatory optimization (GENO), a simple strategy that leverages crRNA processing to control Cas13d expression and is easily integrated into an AAV gene therapy. We argue that thorough assessment of collateral activity is necessary when applying Cas13d in mammalian cells and that implementation of GENO illustrates the advantages of compact and universally robust regulatory systems for Cas-based gene therapies.
Design and Development of an Emoji Sentiment Lexicon

Emojis represent an essential means of expressing sentiments such as opinions and attitudes in computer - mediated communication, especially in chats and social media. To effectively capture these sentiments, the sentiments associated with the emojis used must be known. Previous approaches to determining the sentiments expressed with emojis require a large amount of manual annotation. For many emojis, especially less frequently used platform - specific emojis, studies on expressed sentiments do not yet exist. Therefore, these emojis cannot be considered in sentiment analyses so far. In this work, a method for effective and efficient determination of emojis’ sentiments and their compilation in a sentiment lexicon was developed. The determined sentiments are compiled as a sentiment lexicon. For this purpose, software was created in Python to process collections of texts into a corpus. The software derives the emojis’ sentiments as valence values based on the sentiments of the texts in which the emojis appear. The lexicons produced by the method can be used in lexicon - based sentiment analysis approaches. The method also derives other information on the emojis and their usage that can be used to assess the sentiment lexicon produced and the usage of the emojis. Using the developed method, two analyses were conducted with corpora of different text sources. The results and subsequent comparisons with existing sentiment lexicons have shown that the developed method is able to efficiently produce similar results as sentiment lexicons produced with manual annotation.
A new bio-inspired decision chain for UAV sense-and-avoid applications

This work, after a preliminary feasibility study using a Matlab environment simulation, defines the design and the real hardware testing of a new bio-inspired decision chain for UAV sense-and-avoid applications. Relying on a single and cheap visible camera sensor, computer vision, bio-inspired and automatic decision algorithms have been adopted and implemented on a specific ARM embedded platform through C++/OpenCV coding. A first data set processing, really captured on flight, has been presented.
Flux Estimation Techniques for Inrush Current Mitigation of Line-Interactive UPS Systems

The transformer inrush current contains a large amount of harmonic components and high current magnitude which could result in reduced line voltages and even trigger the overcurrent protection of an uninterruptible power supply (UPS). To mitigate the inrush current fast and also satisfy the load voltage requirement, the estimation of transformer flux is required in the UPS control design. However, in most of the flux estimation techniques, the transformer flux is calculated by integrating the measured line voltages directly. Therefore, a major problem with the pure integrator is that it lacks a virtual damper for convergence and a large error in the estimated transformer flux. The estimation error of transformer flux could lower the quality of UPS output voltage and affect the performance of inrush current mitigation. To improve the accuracy of flux estimation, this paper develops a flux-observer-based inrush current mitigation technique based on the synchronous reference frame. The flux-observer-based inrush current mitigation technique can make the UPS system track the variation of transformer flux fast and precisely. Therefore, it can improve the voltage quality and reduces the required voltage for the inrush current mitigation.
Particle Swarm Optimization Based Najran University Course Timetable Scheduling

The university course timetable scheduling is a combinatorial optimization problem, which is accepted to be an NP-complete problem. Therefore, obtaining a feasible solution to the problem is a challenging issue. There are multiple types of course timetables under a diverse of hard and soft constraints exist in the universities worldwide. Particle swarm optimization is an exciting population-based stochastic approach for solving such kind of optimization problems due to its fast convergence, fewer parameter settings and ability to fit dynamic environmental characteristics. This paper focuses on the application of particle swarm optimization to solve the problem of the university course timetable scheduling at Najran University. There are three objectives in this work. First, is to provide detailed information about the particle swarm optimization algorithm and the university course timetable scheduling problem in general and at Najran University in specific. Second, is to map the university course timetable to the particle swarm optimization problem. Third, is to evaluate the efficiency of the particle swarm optimization algorithm on building optimum university course timetables. The particle swarm optimization algorithm has been implemented on Java programming language and evaluated using data collected from some course timetables of the college of computer science and information systems at Najran University. The parameters of the algorithm have been compared with different values which resulted on different findings. It is found that the algorithm is very efficient in building optimum timetables.
Reliable Schedule Forecasting in Federal Design-Build Facility Procurement

Research Question: Do initial schedules provide reliable forecasting for project control? Purpose: The purpose of this research is to understand how scheduling works in federal facility procurement and identify how project change underscores schedule uncertainty. Research Method: Comparative analysis of project schedule data from three case studies. Findings: This paper documents how initial project schedules fail to sufficiently forecast and provide a reliable baseline for total cost, final duration, and activity count for three design-build projects. Most schedule variability occurs after the 100% design benchmark. Activity growth highlights scheduling challenges encountered by the construction managers and general contractors (GCs). Limitations: The research considers three military construction projects managed by the United States Army Corps of Engineers (USACE) on Wright-Patterson Air Force Base, Ohio. Implications: The research indicates a need to reexamine federal design-build schedule specifications and management practices in the pursuit of project control. Value for Practitioners: This paper discusses reliability concerns in activity-based scheduling and promotes an application of lean thinking to public sector construction management.
Infinitely Variable Transmission (IVT) of John Deere 7000 TEN Series Tractors

The John Deere 7000 TEN series tractors represent a significant change in the transmission system compared to previous John Deere tractor models in this category. John Deere 7710 and 7810 series tractors are the first of the 7000 TEN series tractors offering an infinitely variable transmission (IVT). These tractors provide infinite vehicle speeds in the forward mode from 50 meters/hr to 40 km/hr or an optional 50 km/hr. Reverse mode provides infinite vehicle speeds from 50 meters/hr to 17 km/hr. The IVT provides performance improvements in several areas for unmatched operator convenience and control. The new IVT uses an electric signal to control the electro-hydraulic hydrostatic system with mechanical power train. The IVT represents a hydro-mechanical transmission system using electronics, hydraulics and mechanical systems’ integration to achieve the required performance. This paper describes the IVT system configuration, components, operation, characteristics and some of the engineering considerations dealt with in the development process. The overall IVT system truly represents a “drive-by-wire” mechatronic design.Copyright © 2002 by ASME