Miracle-dz/UniFAR-FTUs huggingface dataset:
Active measurements of a mimo WiMAX‐OFDM based system in reverberation chambers

Electromagnetic reverberation chambers can be used for multiple‐input multiple‐output (MIMO) systems testing.Currently, the tests focus on parameters such as correlation, diversity gain, efficiency, etc., by using a vector network analyzer. In contrast with these passive tests, a novel way of MIMO systems characterization is described in this article. It consists on evaluating bit error rate (BER) levels of a MIMO WiMAX‐OFDM system according to the Signal‐to‐Noise Ratio (SNR) by establishing an active link between the transmitter and the receiver. The measurement process is set up in a reverberation chamber, where multipath frequency selective channels are emulated. The obtained results are compared to a reference case with single‐input single‐output (SISO) to evaluate the real improvements made by the studied system. © 2010 Wiley Periodicals, Inc. Microwave Opt Technol Lett 52:2347–2352, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.25465
BNCPL: Brain-Network-based Convolutional Prototype Learning for Discriminating Depressive Disorders

Deep learning has shown great potential to adaptively learn hidden patterns from high dimensional neuroimaging data, so as to extract subtle group differences. Motivated by the convolutional neural networks and prototype learning, we developed a brain-network-based convolutional prototype learning model (BNCPL), which can learn representations that simultaneously maximize inter-class separation while minimize within-class distance. When applying BNCPL to distinguish 208 depressive disorders from 210 healthy controls using resting-state functional connectivity (FC), we achieved an accuracy of 71.0% in multi-site pooling classification (3 sites), with 2.4-7.2% accuracy increase compared to 3 traditional classifiers and 2 alternative deep neural networks. Saliency map was also used to examine the most discriminative FCs learned by the model; the prefrontal-subcortical circuits were identified, which were also correlated with disease severity and cognitive ability. In summary, by integrating convolutional prototype learning and saliency map, we improved both the model interpretability and classification performance, and found that the dysregulation of the functional prefrontal-subcortical circuit may play a pivotal role in discriminating depressive disorders from healthy controls.
Radial compressor design for industrial compressors

Abstract Industrial centrifugal compressors have a very large field of applications in chemical, petrochemical and gas transport applications with an enormous variety of gases, pressure levels and suction volumes. This paper describes the special design features of this type of compressor and sheds light on a method of standardization to overcome the large diversity of machine types. It reviews the aerodynamic and thermodynamic aspects in the design of impellers and diffusers, discusses the importance of the stage matching and illuminates the effect of stage components on stability.
Gait Planning of Humanoid Robot Based on ZMP and Cubic Spline Interpolation

Teaching programming and manual programming are usually used to realize gait planning of humanoid robot. Many methods are lack of the adjustment of center of gravity and lead to the robot walking instability. The gait planning of humanoid robot is solved based on the Linear Inverted Pendulum Model and Zero Moment Point equation in this paper. Two feet trajectories are also planned to realize the smooth transition and overcome the impact during walking with the cubic spline interpolation method. The validation and feasibility of the method proposed in the paper are proved by the results of simulation and experiments.
Damage Identification Based on Dead Load Redistribution: Methodology

A new method for damage identification in large, massive civil structures is presented, which is based on the idea that dead load is redistributed when damage occurs in the structure. The method uses static strain measurements due to dead load only as input to the identification procedure. An analytical model of a fixed-fixed beam is developed in which the damage is represented by a section of reduced flexural rigidity. The damage state is determined by the location, length, and severity of the stiffness reduction. A forward analysis of the beam response is first presented to illustrate how the dead load is redistributed for different damage scenarios. The inverse problem is defined by a constrained optimization problem and is solved using a genetic algorithm. The proposed method correctly identified damage in the beam for a wide range of locations and damage severities. The identification procedure, in general, has a greater degree of success with increasing damage severity. Results show that damage is difficult to identify when it is close to the inflection point of the undamaged beam, where the dead load strain is zero. The effect of measurement noise on the ability to identify damage is investigated in the companion paper.
Sequential Monitoring of Water Distribution Network

Abstract Monitoring drinking water is a public health problem because water is essential for human life. A typical modern drinking water distribution system includes a water purification plant, water towers, water tanks, pumps and pipes. Many procedures are developed for monitoring water quality in water treatment plants. Monitoring of water distribution systems has received less attention. The goal of this paper is to study the problem of drinking water safety by ensuring the monitoring of the distribution network from water tower to private residences. The proposed approach is based on the observation of residual chlorine concentrations which are provided by sensors network. By using the hydraulic model, it is possible to compute the nominal residuals chlorine concentrations under assumption that quality of the water at the water tower output is known. If a significant reduction of the residual chlorine concentrations is observed then it can be interpreted as presence of a dangerous water contamination. This event should be detected as reliable as possible provided an acceptable detection delay and false alarm rate. The traditional abrupt change detection theory is well developed in the case when the duration of the post-change mode is infinite. Unfortunately, in the discussed case the transient signal duration is short. Hence, the usage of traditional change detection algorithm is compromised. A criterion based on the minimization of the missed detection probability provided that the false alarm rate is upper bounded is used in the paper. A suboptimal detection algorithm is designed. The theoretical analysis and the results of simulation are provided.
Exploring the Potential Role of Ants as Pollinators in a Tallgrass Prairie Following Varied Prescribed Burns

Prescribed burns are used to restore the herbaceous plant communities of tallgrass prairies. Unfortunately, land-use change has driven declines in animal communities that use that habitat, including insect pollinators. Flowering forbs in tallgrass prairies likely depend on insect pollinators for their reproduction, suggesting that restoration efforts may be limited if insect pollinators continue to decline. Further, prescribed burns may lead to the direct mortality of insect pollinators. We thus explore whether Formica ants may be able to compensate for the loss of insect pollinators in tallgrass prairies by monitoring visitation rates of ants and insect pollinators to the milkweed Asclepias tuberosa. Using replicated experimental plots burned at different times (summer, fall, or spring), we found that ants were robust to the timing of prescribed burns and that they averaged 50% of all visits across plots. The distribution of ants and other insect pollinators may be regulated by competitive interactions, as there was a negative relationship between the two potential pollinator communities: the more ant visits, the fewer pollinator visits, and vice versa. The high visitation rates suggest ants may potentially compensate, especially as competitive interactions decrease, but whether that may occur likely depends on their efficiency as pollinators, current plant features, or subsequent plant adaptations to utilize ants.
Wind effects on web structure of grass spiders Agelenopsis actuosa

Abstract Habitat selection can be influenced by abiotic factors such as rain and wind. Spiders build webs that are subjected to wind, thus making habitat selection that much more important for individual spiders. I examined the webs of the grass spider Agelenopsis actuosa (Gertsch & Ivie, 1936), to determine whether they differed in shape, size, and attachment points in short versus tall vegetation in the same general area. I hypothesized that short-grass webs would be larger in diameter, closer to the ground, have more numerous attachments to vegetation, and have specific orientations that accounted for the dominant wind directions. Webs in short grass were significantly shorter in diameter (mean short = 23 ± 6 cm, mean tall = 25 ± 6 cm), lower to the ground (mean short = 7 + 3 cm, mean tall = 17 + 5 cm), and had more numerous attachments (mean short = 24 + 6 attachments, mean tall = 10 + 2 attachments) than webs in tall grass. Short-grass webs were significantly oriented towards north while tall-grass webs showed no significant web orientation. My findings suggest that short-grass webs were smaller because of the wind, and are a predictable circular shape with more attachments. Tall-grass webs were a longer oval in shape, with fewer attachments. Webs are possibly more rigid in short grass with significant orientation perpendicular to the dominant wind direction, possibly for spider thermoregulation.
A theoretical foundation for investigating the spatial economic attributes of airport-centric developments

Abstract Among the various areas of interest on the topic of airports and the geographical distribution of land use, one pertinent theme is the spatial economic analysis of airports and their environs. However, the existing literature predominantly focuses on describing the land-use composition of airport-centric developments, without unpacking the spatial economic forces at play. This gap brings to the fore the need to employ an appropriate theoretical lens to guide the spatial economic analysis of airports and their environs. The aim of this theoretical review paper is thus to identify concepts that are relevant to the analysis of airports and their environs; and to use those concepts to systematically identify the existing theory that is most suitable for investigating the spatial economic forces that drive airport-centric developments. Against the background of globalisation, we scrutinise classical location theories, regional science, growth pole theory and new economic geography against their relational interpretations of the concepts of space, proximity, firm, scale and pattern. Given that it portrays a relational perspective of the aforesaid concepts, the paper concludes that growth pole theory is suitable as the main framework for analysing airport-centric developments. It is therefore recommended that growth pole theory be empirically used to guide the analysis of airports and their environs, and subsequently be used as the basis for developing a theoretical framework tailored for airport-centric developments.
Role of shallow water waves generated by modified Camassa-Holm equation: A comparative analysis for traveling wave solutions

Abstract There is no denying fact that harmonic crystals, cold plasma or liquids and compressible fluids are usually dependent of acoustic-gravity waves, acoustic waves, hydromagnetic waves, surface waves with long wavelength and few others. In this context, the exact solutions of the modified Camassa-Holm equation have been successfully constructed on the basis of comparative analysis of (G′ / G − 1 / G) and (1 / G′)-expansion methods. The (G′ / G − 1 / G) and (1 / G′)-expansion methods have been proved to be powerful and systematic tool for obtaining the analytical solutions of nonlinear partial differential equations so called modified Camassa-Holm equation. The solutions investigated via (G′ / G − 1 / G) and (1 / G′)-expansion methods have remarkably generated trigonometric, hyperbolic, complex hyperbolic and rational traveling wave solutions. For the sake of different traveling wave solutions, we depicted 3-dimensional, 2-dimensional and contour graphs subject to the specific values of the parameters involved in the governing equation. Two methods, which are important instruments in generating traveling wave solutions in mathematics, were compared both qualitatively and quantitatively. In addition, advantages and disadvantages of both methods are discussed and their advantages and disadvantages are revealed.
Effect of flux quantity on Sn-Pb and Pb-free BGA solder shear strength

The global movement to eradicate Pb from electronic assemblies has made it necessary to manufacture Pb-free packages. While the industry has identified potential Pb-free alternatives, much work still needs to be done in the component and board level reliability. Ball Grid Array (BGA) packages are commonly used in the electronics industry today. Flux deposition is a standard step in the BGA sphere-attach process and requires precise since it plays a critical role in the formation of the BGA solder joint. Flux measurement is difficult as it is clear or amber colored, thus making it invisible to standard optics techniques. The patent pending Ultraviolet Fluorescence Intensity Mapping (UV-FIM) technique is used in this research effort for flux measurement. BGA spheres are attached using different quantities of flux. A correlation is made between the solder joint shear strength and the flux quantity for Sn-Pb and Pb-free (96.5Sn-3.5Ag, 95.5Sn-4Ag-0.5Cu) BGA solder joints.
Assessing and enhancing foldability in designed proteins

Recent advances in protein-design methodology have led to a dramatic increase in reliability and scale. With these advances, dozens and even thousands of designed proteins are automatically generated and screened. Nevertheless, the success rate, particularly in design of functional proteins, is low and fundamental goals such as reliable de novo design of efficient enzymes remain beyond reach. Experimental analyses have consistently indicated that a major reason for design failure is inaccuracy and misfolding relative to the design model. To address this challenge, we describe complementary methods to diagnose and ameliorate suboptimal regions in designed proteins: first, we develop a Rosetta atomistic computational mutation scanning approach to detect energetically suboptimal positions in designs (available on a web server https://pSUFER.weizmann.ac.il); second, we demonstrate that AlphaFold2 ab initio structure prediction flags regions that may misfold in designed enzymes and binders; and third, we focus FuncLib design calculations on suboptimal positions in a previously designed low-efficiency enzyme improving its catalytic efficiency by 330 fold. Furthermore, applied to a de novo designed protein that exhibited limited stability, the same approach markedly improved stability and expressibility. Thus, foldability analysis and enhancement may dramatically increase the success rate in design of functional proteins.
Nuclear Receptor Subfamily 4A Signaling as a Key Disease Pathway of CD1c+ Dendritic Cell Dysregulation in Systemic Sclerosis

Objectives To identify key disease pathways driving conventional dendritic cell (cDC) alterations in Systemic Sclerosis (SSc). Methods Transcriptomic profiling was performed on peripheral blood CD1c+ cDCs (cDC2s) isolated from 12 healthy donors and 48 SSc patients with all major disease subtypes. Differential expression analysis comparing the different SSc subtypes and healthy donors was performed to uncover genes dysregulated in SSc. To identify biologically relevant pathways, a gene co-expression network was built using Weighted Gene Correlation Network Analysis. We validated the role of key transcriptional regulators using ChIP-sequencing and in vitro functional assays. Results We identified 17 modules of co-expressed genes in cDC2s that correlated with SSc subtypes and key clinical traits including auto-antibodies, skin score, and occurrence of interstitial lung disease. A module of immune regulatory genes was markedly down regulated in patients with the diffuse SSc subtype characterized by severe fibrosis. Transcriptional regulatory network analysis performed on this module predicted NR4A (nuclear receptor 4A) subfamily (NR4A1, NR4A2, NR4A3) genes as the key transcriptional mediators of inflammation. Indeed, ChIP-sequencing analysis supported that these NR4A members target numerous differentially expressed genes in SSc cDC2s. Inclusion of NR4A receptor agonists in culture-based experiments provided functional proof that dysregulation of NR4As affects cytokine production by cDC2s and modulates downstream T-cell activation. Conclusions NR4A1, NR4A2 and NR4A3 are important regulators of immunosuppressive and fibrosis-associated pathways in SSc cDC2s. Thus, the NR4A family represent novel potential targets to restore cDC homeostasis in SSc. KEY MESSAGES What is already known about this subject? CD1c+ conventional dendritic cells (cDC2s) are implicated as key players in Systemic Sclerosis (SSc), but key molecular mechanisms underlying their dysregulation were unknown. What does this study add? Transcriptomic analysis and network analysis identified modules of coexpressed genes in cDC2s that correlated with SSc subtypes and key clinical traits. The NR4A (nuclear receptor 4A) subfamily (NR4A1, NR4A2, NR4A3) genes act as master regulators of key immune regulatory genes dysregulated in SSc cDC2s, as shown by multi-omics integration analysis using transcriptomics and targeted ChIP-sequencing. Pharmacological activation of NR4As inhibits pro-inflammatory cytokine production and CD4+ T-cell activation by cDC2s. How might this impact on clinical practice or future developments? NR4As are attractive candidates for novel treatment options to attenuate pro-inflammatory and pro-fibrotic responses in SSc patients.
Structure-Activity Relationships in the Design of Mitochondria-Targeted Peptide Therapeutics

Mitochondria play a central role in metabolic homeostasis; hence, dysfunction of this organelle underpins the etiology of many heritable and aging-related diseases. Mitochondria-targeted tetrapeptides with alternating cationic and aromatic residues, such as SS-31 (Elamipretide), show promise as therapeutic compounds. In this study, we conducted a quantitative structure-activity analysis of three alternative tetrapeptide analogs that differed with respect to aromatic side chain composition and sequence register, benchmarked against SS-31. Using NMR and molecular dynamics approaches, we obtained the first structural models for this class of compounds, showing that all analogs except for SS-31 form compact reverse turn conformations in the membrane-bound state. All peptide analogs bound cardiolipin-containing membranes, yet they had significant differences in equilibrium binding behavior and membrane interactions. Notably, the analogs had markedly different effects on membrane surface charge, supporting a mechanism in which modulation of membrane electrostatics is a key feature of their mechanism of action. All peptide analogs preserved survival and energy metabolism more effectively than SS-31 in cell stress models. Within our peptide set, the analog containing tryptophan side chains, SPN10, had the strongest impact on most membrane properties and showed greatest efficacy in cell culture studies. Taken together, these results show that side chain composition and register strongly influence the activity of these mitochondria-targeted peptides. Furthermore, this work helps provide a framework for the rational design of next-generation therapeutics with enhanced potency.
Evidence for a long-range RNA-RNA interaction between ORF8 and the downstream region of the Spike polybasic insertion of SARS-CoV-2

SARS-CoV-2 has affected people all over the world as the causative agent of COVID-19. The virus is related to the highly lethal SARS-CoV responsible for the 2002-2003 SARS outbreak in Asia. Intense research is ongoing to understand why both viruses have different spreading capacities and mortality rates. Similar to other betacoronaviruses, long-range RNA-RNA interactions occur between different parts of the viral genomic RNA, resulting in discontinuous transcription and production of various sub-genomic RNAs. These sub-genomic RNAs are then translated into different viral proteins. An important difference between both viruses is a polybasic insertion in the Spike region of SARS-CoV-2, absent in SARS-CoV. Here we show that a 26-base-pair long-range RNA-RNA interaction occurs between the genomic region downstream of the Spike insertion and ORF8 in SARS-CoV-2. Predictions suggest that the corresponding ORF8 region forms the most energetically favorable interaction with that of Spike region from amongst all possible candidate regions within SARS-CoV-2 genomic RNA. We also found signs of sequence covariation in the predicted interaction using a large dataset with 27,592 full-length SARS-CoV-2 genomes. In particular, a synonymous mutation in ORF8 accommodated for base pairing with Spike [G23675 C28045U], and a non-synonymous mutation in Spike accommodated for base pairing with ORF8 [C23679U G28042] both of which were in close proximity of one another. The predicted interactions can potentially be related to regulation of sub-genomic RNA production rates.
Water column stability as an important factor controlling nitrite-dependent anaerobic methane oxidation in stratified lake basins

Anaerobic oxidation of methane (AOM) with nitrate/nitrite as the terminal electron acceptor may play an important role in mitigating methane emissions from lacustrine environments to the atmosphere. We investigated AOM in the water column of two connected but hydrodynamically contrasting basins of a south-alpine lake in Switzerland (Lake Lugano). The North Basin is permanently stratified with year-round anoxic conditions below 120 m water depth, while the South Basin undergoes seasonal stratification with the development of bottom water anoxia during summer. We show that below the redoxcline of the North Basin a substantial fraction of methane was oxidized coupled to nitrite reduction by Candidatus Methylomirabilis. Incubation experiments with 14CH4 and concentrated biomass from showed at least 43-52%-enhanced AOM rates with added nitrate/nitrite as electron acceptor. Multiannual time series data on the population dynamics of Candidatus Methylomirabilis in the North Basin following an exceptional mixing event in 2005/2006 revealed their requirement for lasting stable low redox-conditions to establish. In the South Basin, on the other hand, we did not find molecular evidence for nitrite-dependent methane oxidizing bacteria. Our data suggest that here the dynamic mixing regime with fluctuating redox conditions is not conducive to the development of a stable population of relatively slow-growing Candidatus Methylomirabilis, despite a hydrochemical framework that seems more favorable for nitrite-dependent AOM than in the North Basin. We predict that the importance of N-dependent AOM in freshwater lakes will likely increase in future because of longer thermal stratification periods and reduced mixing caused by global warming.