Miracle-dz/UniFAR-FTUs huggingface dataset:
Crystal Structures of Human C4.4A Reveal the Unique Association of Ly6/uPAR/α-neurotoxin Domain

Ly6/uPAR/α-neurotoxin domain (LU-domain) is characterized by the presence of 4-5 disulfide bonds and three flexible loops that extend from a core stacked by several conversed disulfide bonds (thus also named three-fingered protein domain). This highly structurally stable protein domain is typically a protein-binder at extracellular space. Most LU proteins contain only single LU-domain as represented by Ly6 proteins in immunology and α-neurotoxins in snake venom. For Ly6 proteins, many are expressed in specific cell lineages and in differentiation stages, and are used as markers. In this study, we report the crystal structures of the two LU-domains of human C4.4A alone and its complex with a Fab fragment of a monoclonal anti-C4.4A antibody. Interestingly, both structures showed that C4.4A forms a very compact globule with two LU-domain packed face to face. This is in contrast to the flexible nature of most LU-domain-containing proteins in mammals. The Fab combining site of C4.4A involves both LU-domains, and appears to be the binding site for AGR2, a reported ligand of C4.4A. This work reports the first structure that contain two LU-domains and provides insights on how LU-domains fold into a compact protein and interacts with ligands.
Brief Announcement: Self-stabilizing Systems in Spite of High Dynamics

We initiate research on self-stabilization in highly dynamic identified message-passing systems where dynamics is modeled using time-varying graphs (TVGs). More precisely, we address the self-stabilizing leader election problem in three wide classes of TVGs: the class TCB (Δ) of TVGs with temporal diameter bounded by Δ, the class TCB (Δ) of TVGs with temporal diameter quasi-bounded by Δ, and the class TCR of TVGs with recurrent connectivity only, where TCB (Δ) ⊆ TCB (Δ) ⊆ TCR. We first study conditions under which our problem can be solved. Precisely, we introduce the notion of size-ambiguity to show that the assumption on the knowledge of the number n of processes is central. Our results reveal that, despite the existence of unique process identifiers, any deterministic self-stabilizing leader election algorithm working in the TVG class TCB (Δ) or TCR cannot be size-ambiguous, justifying why our solutions for those classes assume the exact knowledge of n. We then present three self-stabilizing leader election algorithms for the TVG classes TCB (Δ), TCB(Δ), and TCR, respectively.
An Investigation of the Imprinting Effect of Home Country Institution on the Adoption of ISO 14001 Standard by MNC Subsidiaries

The paper argues that home country institution matters in the adoption of ISO 14001 standard by MNC subsidiaries. Using ‘Organisational Imprinting’ theory the study tests the hypotheses and carries out a cross-sectional analysis using secondary data sources: ORBIS database, the directory of ISO 14001 certified companies published by the Government of Hong Kong , the World Bank’s World-Wide Governance Indicators (Kaufmann et al., 2009) and the GLOBE database (House et al., 2004). The empirical findings support the hypothesis on the positive relationship between imprinting effects of home country institution and ISO 14001 adoption by subsidiaries. Further, findings also suggest that the imprinting effect is more in the case of firms operating in high polluting industries. In addition, the findings confirm that firms originating in countries with high level of GHG emissions reflect greater level of imprinting effect.
Explain like I am a Scientist: The Linguistic Barriers of Entry to r/science

As an online community for discussing research findings, r/science has the potential to contribute to science outreach and communication with a broad audience. Yet previous work suggests that most of the active contributors on r/science are science-educated people rather than a lay general public. One potential reason is that r/science contributors might use a different, more specialized language than used in other subreddits. To investigate this possibility, we analyzed the language used in more than 68 million posts and comments from 12 subreddits from 2018. We show that r/science uses a specialized language that is distinct from other subreddits. Transient (newer) authors of posts and comments on r/science use less specialized language than more frequent authors, and those that leave the community use less specialized language than those that stay, even when comparing their first comments. These findings suggest that the specialized language used in r/science has a gatekeeping effect, preventing participation by people whose language does not align with that used in r/science. By characterizing r/science's specialized language, we contribute guidelines and tools for increasing the number of contributors in r/science.
An Integrated 3D Geological and Isothermal Modelling to Better Understand Geothermal Reservoir

Conceptual models are usually made in 2D during the Exploration stage. The 2D model is generally limited to providing subsurface images, overcoming these limitations it is very important to use a 3D approach to improve understanding of subsurface conditions. This study presents some techniques to construct an integrated 3D model of a geothermal field. The geological setting of the field is defined from surface geological data. Identification of the reservoir area using the first appearance of the epidote and integrated with the static temperature of the well. Visualization of the 3D model in this study was made using Leapfrog Geothermal software. This 3D model can be used to help better understand the evolution of geothermal system, support drilling strategies and management of the resource.
Accelerating Approximations via Slack Recycling

Motivated by limitations in current approximate hardware, we propose to extend the notion of timing slack into approximate computation. We propose Axl: disciplined but increased aggressiveness in timing slack estimates at an operation granularity accounting for slack from PVT, data, as well as approximation tolerance. This results in improved performance/efficiency within application-specific tolerable error rates.
The Characteristics of Ambient Non-Methane Hydrocarbons (NMHCs) in Lanzhou, China

Non-methane hydrocarbons (NMHCs) from four sampling sites in Lanzhou, a petrochemical industrialized city in northwest China, was sampled by stainless steel canisters and measured by gas chromatography–mass selective detection/flame ionization detection (GC–MSD/FID) in May and June of 2017. Based on these results, the contributions of NMHCs to the ozone (O3) and secondary organic aerosols (SOA), differences in tracer ratios, and source apportionment by principal component analysis (PCA) were analyzed. The results showed that the total NMHCs concentration in Lanzhou was 48.4 ± 48.3 ppbv (parts per billion by volume) during the observation and it was higher in May (78.6 ppbv) than in June (37.8 ppbv); the highest NMHCs concentration was observed in industrial areas. Alkanes were the dominant group at all sites in Lanzhou and account for more than 60% of the NMHCs, while isopentane, n-butane n-pentane, propane and ethane were the major compounds. Additionally, the NMHCs in Lanzhou have made great contributions to O3 and SOA generation and the S1 site of the industrial area contributed the most to both of them. Propene, toluene, ethylbenzene and n-pentane were found to be more reactive with relatively high contributions to ozone formation. Aromatics and high carbon alkanes were major contributors to SOA formation potential (SOAp) (i.e., toluene, m,p-xylene, dodecane, undecane, n-tanane, benzene and ethylbenzene) in Lanzhou. Based on the specific volatile organic compounds (VOCs) ratio method and the PCA modem, the observation sites in Lanzhou were greatly affected by the surrounding industrial areas. The sources consisted of petrochemical industry, vehicle emissions, solvent usage and combustion sources, which contributed to 33.9%, 31.6%, 19.2% and 7.9% of the total monitored NMHCs, respectively. From different sites, though the influence of regional transport was not very significant on the whole, it also affected the NMHCs of nonindustrial areas based on the ratio of xylene to ethyl-benzene (X/E), especially the S4 site; vehicle emission was less important compared to sources from petrochemical industries in S1, as characterized by relatively higher toluene to benzene (T/B) ratios. However, vehicle emission has significant influence on NMHCs in S4. Overall, local emissions are the main source of NMHCs in Lanzhou and the petrochemical industry has a great influence on the distribution of NMHCs in the whole region.
Analyzing Student Performance with Personalized Study Path and Learning Trouble Ratio

Massive Online Open Courses (MOOCs) have become very popular nowadays and are attracting a lot of attention from both learners and researchers. Learners beneﬁt from their availability of learning materials such as lecture notes, videos and self-tests. However, most MOOCs are a one-size-ﬁt-all model and does not meet the individual needs of learners. For example, each learner is shown a “pre-deﬁned” order of study for each diﬀerent learning concept in a course. It is observed that diﬀerent learners have diﬀerent learning paces, and how good a learner understands one learning concept is heavily dependent on how good s/he understands the pre-requisite of this learning concept (which is also a learning concept). Motivated by this, some researchers would like to propose some personalized suggestions for each learner so that they could learn certain concepts in diﬀerent order. In this paper, we introduce a method for visualizing an ordering of learning concepts concisely and showing how strongly one learning concept is related to another learning concept.
LEA-SIoT: Hardware Architecture of Lightweight Encryption Algorithm for Secure IoT on FPGA Platform

The Internet of Things (IoT) is one of the emerging technology in today’s world to connect billions of electronic devices and providing the data security to these electronic devices while transmission from the attacks is a big challenging task. These electronic devices are smaller and consume less power. The conventional security algorithms are complex with its computations and not suitable for IoT environments. In this article, the hardware architecture of the new Lightweight encryption algorithm (LEA) for the secured Internet of things (SIoT) is designed, which includes Encryption, decryption along with key generation process. The New LEA-SIoT is a hybrid combination of the Feistel networks and Substitution-permutation Network (SPN). The encryption/decryption architecture is the composition of Logical operations, substitution transformations, and swapping. The encryption/decryption process is designed for 64-bit data input and 64-bit key inputs. The key generation process is designed with the help of KHAZAD block cipher algorithm. The encryption and key generation process are executing in parallel with pipelined architecture with five rounds to improve the hardware and computational complexity in IoT systems. TheLEA-SIoT is designed on the Xilinx platform and implemented on Artix-7 FPGA. The hardware constraints like area, power, and timing utilization are summarized. The Comparison of the LEA-SIoT with similar security algorithms is tabulated with improvements.
On the Complexity of Proper Distribution-Free Learning of Linear Classifiers

For proper distribution-free learning of linear classiﬁers in d dimensions from m examples, we prove a lower bound on the optimal expected error of d − o (1) m , improving on the best previous lower bound of d/ √ e − o (1) m , and nearly matching a d +1 m +1 upper bound achieved by the linear support vector machine.
Scalability Performance for Low Power Wide Area Network Technology using Multiple Gateways

Low Power Wide Area Network is one of the leading technologies for the Internet of Things. The capability to scale is one of the advantage criteria for a technology to compare to each other. The technology uses a star network topology for communication between the end-node and gateway. The star network topology enables the network to support a large number of end-nodes and with multiple of gateways deployed in the network, it can increase the number of end nodes even more. This paper aims to investigate the performance of the Low Power Wide Area Network Technology, focusing on the capability of the network to scale using multiple gateways as receivers. We model the network system based on the communication behaviours between the end-node and gateways. We also included the communication limit range for the data signal from the end-node to successfully be received by the gateways. The performance of the scalability for the Low Power Wide Area Network Technology is shown by the successfully received packet data at the gateways. The simulation to study the scalability was done based on several parameters, such as the number of end-nodes, gateways, channels and also application time. The results show that the amount of successfully received data signal at gateway increased as the gateways, application time and channel used increased.
Optimization Tool for Allocation of Watershed Management Practices for Sediment and Nutrient Control

Implementation of conservation programs are perceived as being crucial for restoring and protecting waters and watersheds from nonpoint source pollution. Success of these programs depends to a great extent on planning tools that can assist the watershed management process. Herein, a novel optimization methodology is presented for deriving watershed-scale sediment and nutrient control plans that incorporate multiple, and often conflicting, objectives. The method combines the use of a watershed model (SWAT), representation of best management practices, an economic component, and a genetic algorithm-based spatial search procedure. For a small watershed in Indiana located in the Midwestern portion of the United States, selection and placement of best management practices by optimization was found to be nearly three times more cost-effective than targeting strategies for the same level of protection specified in terms of maximum monthly sediment, phosphorus, and nitrogen loads. Conversely, for the same cost, the optimization plan reduced the maximum monthly loads by a factor of two when compared to the targeting plan. The optimization methodology developed in this paper can facilitate attaining water quality goals at significantly lower costs than commonly used cost-share and targeting strategies.
Large‐ and small‐seeded species have contrasting functional neighborhoods in a subtropical forest

Forest community composition is the outcome of multiple forces, including those that increase taxonomic and functional divergence and those that promote convergence in traits. The mechanisms underlying these forces may not operate homogenously within communities; individuals of different species are never perfectly mixed, and thus, species tend to be surrounded and interact with different subsets of species. In fact, taxonomic and functional composition of neighborhoods of different focal species can be highly variable. Here, we examine whether mechanisms driving species-level neighborhoods relate to intrinsic characteristics of focal species such as differences in life-history and resource-uptake strategies and in turn relate to species survival. We focus on two key characteristics: (1) seed mass, which de ﬁ nes a dominant axis of life-history strategies related to stress tolerance, and (2) understory light preferences that sort species from light-demanding pioneers to shade-tolerant. We monitored seedling communities over 10 yr in Puerto Rico and calculated neighborhood trait dispersion in species-level neighborhoods using seven functional traits. We examined whether species-level characteristics, seed mass and preferred light conditions, in ﬂ uence patterns of functional dispersion in seedling neighborhoods using linear models. Then, we examined how species-level functional neighborhoods impact seedling survival. We found that small- and large-seeded species diverge in the type of functional neighborhoods they associate with. Large-seeded species associate with neighbors that are more similar than expected in leaf economic traits, but more different than expected in seed mass and leaf area traits, while the opposite was found for small-seeded species. This variation in species functional neighborhood was important in determining seedling survival. In sum, our results suggest that divergent and convergent forces do not operate homogenously over entire communities. Their relative role changes in space, and on a species-by-species basis, probably with a deterministic foundation linked to traits such as seed mass.
The Impact of Functional Integration and Spatial Proximity on the Post-entry Performance of Knowledge Intensive Business Service Firms

Knowledge intensive business service firms (KIBS) are an important element of modern economies and thus attracting increasing interest in scientific research. In the existing literature it is argued that due to the important role of knowledge, innovation and userproducer interaction in the KIBS sector, functional integration and spatial proximity are particularly decisive for a firm’s development. Nevertheless, due to the absence of suitable micro data there is a lack of studies empirically analysing the impact of functional integration and regional proximity using micro firm data. Based upon newlyconducted firm micro data in three German metropolitan regions, this paper supplements the literature by giving a multivariate empirical analysis of the determinants of post-entry performance of KIBS. The results of the estimation of firm growth equations show that functional linkages to knowledge providers, customers and co-operation partners indeed matter for the performance of young KIBS. Regarding spatial proximity, however, especially a high diversification of geographical reach is proved to be crucial. JEL-Classification: D21, J23, L80, O30
Bacterial Population Dynamics in a Laboratory Activated Sludge Reactor Monitored by Pyrosequencing of 16S rRNA

The microbial population in a laboratory activated sludge reactor was monitored for 245 d at 75 time points by pyrosequencing of 16S rRNA. Synthetic wastewater was used as the influent, and the reactor was operated under the same conditions throughout the experiment. The behaviors of different bacterial operational taxonomic units (OTUs) were observed. Multiple OTUs showed periodic propagation and recession. One of the OTUs showed sharp recession, which suggests that cells in the OTU were selectively killed. The behaviors of different phylogenetic lineages of Candidatus ‘Accumulibacter phosphatis’ were also visualized. It was clearly demonstrated that pyrosequencing with barcoded primers is a very effective tool to clarify the dynamics of the bacterial population in activated sludge.
Three-dimensional tomographic study of dermal armour from the tail of the Triassic aetosaur Stagonolepis robertsoni

The aetosaur Stagonolepis robertsoni was the first reptile to be named from the Late Triassic Lossiemouth Sandstone Formation of Morayshire. Its characteristic rectangular armour plates have been reported in isolation and in association with skeletal remains. Here we present for the first time a three-dimensional reconstruction of the armour plates around the tail in association with caudal vertebrae and a chevron, to give direct evidence of the body outline. The caudal vertebral column was surrounded by eight bony osteoderms, paired paramedian dorsal and ventral plates, and a pair of lateral osteoderms on right and left. The tail shape was subcircular, broader than high. The osteoderms overlap like roofing tiles, the posterior margin of each overlapping the osteoderm following behind. The success of these scans suggests that computed tomography scanning could reveal excellent detail of all the Elgin reptiles in the future. Supplementary material: Three-dimensional models of the two fossil specimens are available at: https://doi.org/10.6084/m9.figshare. c.4824183
OPTH_A_217932 1579..1586

Department of Ophthalmology, All India Institute of Medical Sciences, Raipur, India Purpose: This study aimed to evaluate whether different anterior chamber depth (ACD) affects the predictive accuracy of intraocular lens formulas in eyes with axial length (AL) less than 22 mm. Methods: Eighty-five eyes of 85 patients with AL less than 22 mm were included in this retrospective study, which were divided into three groups: Group 1, ACD less than 2.4 mm; Group 2, ACD between 2.4 and 2.9 mm; and Group 3, ACD greater than 2.9 mm. Optical biometry with partial coherence interferometry was performed in all cases. The median absolute error (MedAE) was compared by Friedman’s test, using the optimized lens constant, among seven formulas (Barrett Universal II, Haigis, Hill-RBF, Hoffer Q, Holladay 1, Holladay 2, and SRK/T) in each group. Results: Friedman’s test showed no significant difference in MedAE among all formulas in Groups 1 and 3. However, as the Haigis formula had the highest MedAE and lowest percentage of eyes within ±0.25 Diopter, it is least preferred in Group 1. On the contrary, in Group 3 it fared the best, having the least MedAE and highest percentage of eyes within ±0.25 Diopter. In Group 2, Friedman’s test gave significant difference, and post-hoc analysis showed statistical superiority of Haigis over the Holladay 1 (p=0.02), Holladay 2 (p=0.01), Hill-RBF (p=0.04), and SRK/T (p=0.02) formulas. However, there was no statistical difference between the Barrett Universal II, Haigis, and Hoffer Q formulas. Conclusion: Considering the ACD in eyes with AL less than 22 mm, Haigis is the preferred formula while SRK/T proved to be the worst formula in Groups 2 and 3.
Methanol, Ethanol, and Glycerol Oxidation by Graphite-Epoxy Composite Electrodes with Graphene-Anchored Nickel Oxyhydroxide Nanoparticles

In this work, a graphite-epoxy electrode with cyclic voltammetry electrodeposited reduced graphene oxide and nickel oxyhydroxide nanoparticles was prepared by decomposition in NaOH alkaline solution of cyclic voltammetry electrodeposited nickel hexacyanoferrate. FE-SEM studies were performed to confirm the NiOOH nanoparticle; the average size of the NiOOH nanoparticles was 61 ± 16 nm and EDX was applied to analyze chemical composition. To verify the performance of the prepared electrode, it was used in the electrooxidation of alcohols in alkaline medium by cyclic voltammetry. By performing different calibration experiments of methanol, ethanol, and glycerol, it was possible to extract some information about the electrode in the presence of alcohols. The LOD for methanol, ethanol, and glycerol were 2.16 mM, 2.73 mM and 0.09 mM, respectively, with sensitivity values of 1.32 µA mM−1, 1.80 µA mM−1 and 24.60 µA mM−1, respectively. Multivariate inspection of the data using Principal Component Analysis (performed with the ClustVis online tool) demonstrated the potential ability to discriminate between the different alcohols, whereas the explained variance with the first two components was as high as 89.7%.