Miracle-dz/UniFAR-FTUs huggingface dataset:
Productivity and complementarity in grassland microcosms of varying diversity

Several researchers have hypothesized that, through various mechanisms, loss of species and functional group richness from a plant community will affect the magnitude and interannual variability of productivity. To test this hypothesis, I conducted a microcosm study of California grassland communities that differed in species richness. I grew cohorts of microcosms that simulated undisturbed grassland (in one year) and gopher-disturbed grassland (in two consecutive years). As the number of species per functional group decreased from 4 to 1, biomass production remained constant in all three cohorts. As species richness decreased from 16 to 1 (or 8 to 1, in either case including a drop in functional group richness), productivity declined in one of the cohorts. In this cohort, productivity of one polyculture marginally exceeded that of the most productive monoculture. Resource complementarity and a type of selection effect may have each contributed to the observed diversity-productivity relationships. Results suggest the existence of a selection effect that involves species that are highly productive in mixtures, rather than in monoculture. Over two seasons, species and functional group richness did not affect the interannual variability of biomass production. Comparisons of interannual changes in the productivity of monocultures and polycultures suggested that, in some polycultures, increased water availability might have relieved interspecific competition more than intraspecific competition. Based on results from this experiment and other manipulative experiments, I develop a framework to explain the relationship between species richness and productivity in terrestrial plant communities. The framework highlights the importance of environmental variation in shaping the diversity/productivity relationship.
The Impact of Peer Accountability Groups in a Mathematics Classroom

This research study will examine student goal attainment through selfand peer analysis. The participants of this study will be students in an eighth grade mathematics class. Research was conducted through Google forms where students were able to list their goals, ideas for reaching those goals, and respond to weekly prompts. Overall, the peer accountability groups tended to be beneficial for most students. THE IMPACT OF PEER ACCOUNTABILITY GROUPS 3 Introduction The National Council of Teachers of Mathematics (NCTM, 2000) suggests that students learn more and understand better when they control their learning through setting goals and monitoring their progress. Students can do this by analyzing the task they need to accomplish and discussing strategies for accomplishing this task. Afterwards, they should receive assistance in monitoring their progress towards completing the task. This allows students to learn strategies that are effective for them (Pape, 2005). In addition, achievement has also been found to correlate with learning environment (Gherasim, Butnaru, & Iacob, 2011). A positive learning environment is created by establishing a sense of community in the classroom (NCTM, 2009). A positive learning environment leads to students setting and achieving goals. All of these elements; goal setting, goal achievement, and a positive learning environment; allow students to build valuable skills. I will use the results of my action research project to impact my teaching. The phenomenon that I will be researching is students’ goal attainment. I would like to help my future students set and reach their academic goals in my classroom through self and peer analysis. I will do this by creating a positive learning environment with a focus on mastery goals. This study is important because students need to be able to set goals for themselves and work towards meeting these goals. This process helps to provide benchmarks that will help students learn mathematics. Students should also support each other and encourage their peers to reach their goals. I anticipate that the self and peer analysis will support goal achievement because students will receive and give feedback about reaching goals. The reminder and accountability involved in this study will help students stay on track and reach their goals.
HIV and innate immunity – a genomics perspective

Innate immunity is a theme of increasing interest for HIV research. However, the term is overstretched to cover biological barriers, cellular systems, soluble factors, signaling pathways, and effectors and is inconsistently applied. A clearer semantic classification of the components of innate immunity is needed, which will have direct relevance to the interpretation of human genome variation. Here, we discuss genomic approaches that can assist in re-defining the perimeter of innate immunity. We place particular emphasis on the characteristics of effectors of the intracellular defense against HIV and other pathogens.
Key Fundamental Factors and Long-run Price Changes in an Emerging Market-A Case Study of Karachi Stock Exchange (KSE)

Share prices are the most important indicator readily available to the investors for their decision to invest or not in a particular share. Theories suggest that share price changes are associated with changes in fundamental variables which are relevant for share valuation like payout ratio, dividend yield, capital structure, earnings size of the firm and its growth, [Wilcox (1984); Rappoport (1986); Downs (1991)]. Linter (1956) linked dividend changes to earnings while Shapiro valuation model (1962) showed dividend streams discounted by the difference in discount rate and growth in dividend should be equal to share price. This predicts direct relation between pay out ratio and the price-earning multiple. Conversely it means that there is an inverse relation between pay out ratio and share price changes. Several eventbased studies established direct relation between share price changes and either earnings or dividend changes [Ball and Brown (1968); Baskin (1989)]. Sharpe (1964) and Hamada (1972) suggested direct relation between share price changes and capital structure. Beaver, Kettler and Sholes (1970) showed that firms appear to pay less of their earnings if they have higher earning volatility. This suggests payout ratio as relevant factor for share price changes. Investigations of share price changes appear to yield evidence that changes in fundamental variable(s) should jointly bring about changes in share prices both in developed and emerging markets. However, the actual fundamental factors found to be relevant may vary from market to market. For example, changes in asset growth of firms are significant in the case of Japanese shares while earnings appear to be universally a relevant factor [Ariff, et al. (1994)]. However, it is widely agreed that a set of fundamental variables as suggested by individual theories is no doubt relevant as possible factors affecting share price changes in the short and the long-run.
Ligament Injury and Healing: A Review of Current Clinical Diagnostics and Therapeutics

Ligament injuries are among the most common causes of musculoskeletal joint pain and disability encountered in primary practice today. Ligament injures create disruptions in the balance between joint mobility and joint stability, causing abnormal force transmission through the joint, which results in damage to other structures in and around the joint. The long-term consequence of nonhealed ligament injury is osteoarthritis, the most common joint disorder in the world today. Ligaments heal through a distinct sequence of cellular events that take place in three consecutive stages: an acute inflammatory phase, a proliferative or regenerative phase, and a tissue remodeling phase. The process can take months to resolve itself, and despite advances in therapeutics, many ligaments do not regain their normal tensile strength. Various diagnostic procedures have been used to determine and assess ligament injury. Traditionally, MRI and X-rays have been the most utilized techniques; however, because ligaments do not show up clearly with these devices, there have been many false positives and negatives reported due to inconclusive or inaccurate readings. Newer technologies, such as ultrasound and digital motion X-ray, are able to provide a more detailed image of a ligament's structure and function. Numerous strategies have been employed over the years attempting to improve ligament healing after injury or surgery. One of the most important of these is based on the understanding that monitoring early resumption of activity can stimulate repair and restoration of function and that prolonging rest may actually delay recovery and adversely affect the tissue's response to repair. Likewise, there is a shift away from the use of steroid injections and nonsteroidal anti- inflammatory medications. Although these compounds have been shown effective in decreasing the inflammation and pain of ligament injuries for up to six to eight weeks, their use has been shown to inhibit the histological, biochemical, and biomechanical properties of ligament healing. For this reason their use is cautioned against in athletes who have ligament injuries. Such products are no longer recommended for chronic soft tissue injuries or for acute ligament injuries, except for the shortest possible time, if at all. Regenerative medicine techniques, such as prolotherapy, have been shown, in both case series and clinical studies, to resolve ligament injuries of the spine and peripheral joints. More research and additional studies are needed to better assess ligament injuries and healing properties.
Self-Interference Cancellation in Full-Duplex Radio Transceivers with Oscillator Phase Noise

This paper addresses the problem of phase-noise estimation and mitigation in full-duplex radio transceivers. It has been shown before that the phase-noise is one of the most critical factors limiting the self-interference suppression performance in full-duplex radio transceivers. In this paper, an algorithm is proposed for the phase-noise estimation and mitigation. The algorithm has high estimation quality and low computational complexity, and it does not require synchronization of the useful and self-interference signals, so it is applicable also in long-range communications. The performance of the algorithm is then evaluated and compared to the performance of the state-of-theart algorithm with extensive computer simulations.
Towards Exploring Fundamental Limits of System-Specific Cryptanalysis Within Limited Attack Classes: Application to ABSG

A new approach on cryptanalysis is proposed where the goal is to explore the fundamental limits of a specific class of attacks against a particular cryptosystem. As a first step, the approach is applied on ABSG, which is an LFSR-based stream cipher where irregular decimation techniques are utilized. Consequently, under some mild assumptions, which are common in cryptanalysis, the tight lower bounds on the algorithmic complexity of successful Query-Based Key-Recovery attacks are derived for two different setups of practical interest. The proofs rely on the concept of ``typicality'' of information theory.
Roles for transcript leaders in translation and mRNA decay revealed by transcript leader sequencing

Transcript leaders (TLs) can have profound effects on mRNA translation and stability. To map TL boundaries genome-wide, we developed TL-sequencing (TL-seq), a technique combining enzymatic capture of m7G-capped mRNA 5′ ends with high-throughput sequencing. TL-seq identified mRNA start sites for the majority of yeast genes and revealed many examples of intragenic TL heterogeneity. Surprisingly, TL-seq identified transcription initiation sites within 6% of protein-coding regions, and these sites were concentrated near the 5′ ends of ORFs. Furthermore, ribosome density analysis showed these truncated mRNAs are translated. Translation-associated TL-seq (TATL-seq), which combines TL-seq with polysome fractionation, enabled annotation of TLs, and simultaneously assayed their function in translation. Using TATL-seq to address relationships between TL features and translation of the downstream ORF, we observed that upstream AUGs (uAUGs), and no other upstream codons, were associated with poor translation and nonsense-mediated mRNA decay (NMD). We also identified hundreds of genes with very short TLs, and demonstrated that short TLs were associated with poor translation initiation at the annotated start codon and increased initiation at downstream AUGs. This frequently resulted in out-of-frame translation and subsequent termination at premature termination codons, culminating in NMD of the transcript. Unlike previous approaches, our technique enabled observation of alternative TL variants for hundreds of genes and revealed significant differences in translation in genes with distinct TL isoforms. TL-seq and TATL-seq are useful tools for annotation and functional characterization of TLs, and can be applied to any eukaryotic system to investigate TL-mediated regulation of gene expression.
Towards Good Practices for Very Deep Two-Stream ConvNets

Deep convolutional networks have achieved great success for object recognition in still images. However, for action recognition in videos, the improvement of deep convolutional networks is not so evident. We argue that there are two reasons that could probably explain this result. First the current network architectures (e.g. Two-stream ConvNets) are relatively shallow compared with those very deep models in image domain (e.g. VGGNet, GoogLeNet), and therefore their modeling capacity is constrained by their depth. Second, probably more importantly, the training dataset of action recognition is extremely small compared with the ImageNet dataset, and thus it will be easy to over-fit on the training dataset. To address these issues, this report presents very deep two-stream ConvNets for action recognition, by adapting recent very deep architectures into video domain. However, this extension is not easy as the size of action recognition is quite small. We design several good practices for the training of very deep two-stream ConvNets, namely (i) pre-training for both spatial and temporal nets, (ii) smaller learning rates, (iii) more data augmentation techniques, (iv) high drop out ratio. Meanwhile, we extend the Caffe toolbox into Multi-GPU implementation with high computational efficiency and low memory consumption. We verify the performance of very deep two-stream ConvNets on the dataset of UCF101 and it achieves the recognition accuracy of $91.4\%$.
Tourist: Self-Adaptive Structured Overlay

Structured overlays provide a basic substrate for many peer-to-peer systems. Existing structured overlays can be classified into two categories, O(logN)-hop ones and O(l)-hop ones. The former are suitable for large and dynamic systems, while the latter are suitable for small or stable ones. However, for the lack of adaptivity, it is difficult for a peer-to-peer system designer to choose from these two kinds of overlays because the eventual size and churn rate are not easy to predict in the design phase. To address this problem, we propose a self-adaptive structured overlay Tourist, which can adapt itself to the changing environment dynamically. Tourist nodes determine their routing table size autonomously: nodes with different capacities hold routing tables with different sizes. This makes Tourist sufficiently utilize all the nodes' allowable bandwidth to achieve as high routing efficiency as possible. Tourist also allows each node to adjust its routing table size dynamically, which is the essential reason for the self adaptivity. Simulation results show that in a common 1,000,000-node system, Tourist can route all the messages within two hops and each node only pays no more than 1% bandwidth for its routing table maintenance.
Modeling interaction features for debate side clustering

Online discussion forums are popular social media platforms for users to express their opinions and discuss controversial issues with each other. To automatically identify the sides/stances of posts or users from textual content in forums is an important task to help mine online opinions. To tackle the task, it is important to exploit user posts that implicitly contain support and dispute (interaction) information. The challenge we face is how to mine such interaction information from the content of posts and how to use them to help identify stances. This paper proposes a two-stage solution based on latent variable models: an interaction feature identification stage to mine interaction features from structured debate posts with known sides and reply intentions; and a clustering stage to incorporate interaction features and model the interplay between interactions and sides for debate side clustering. Empirical evaluation shows that the learned interaction features provide good insights into user interactions and that with these features our debate side model shows significant improvement over other baseline methods.
A Single Polar Residue and Distinct Membrane Topologies Impact the Function of the Infectious Bronchitis Coronavirus E Protein

The coronavirus E protein is a small membrane protein with a single predicted hydrophobic domain (HD), and has a poorly defined role in infection. The E protein is thought to promote virion assembly, which occurs in the Golgi region of infected cells. It has also been implicated in the release of infectious particles after budding. The E protein has ion channel activity in vitro, although a role for channel activity in infection has not been established. Furthermore, the membrane topology of the E protein is of considerable debate, and the protein may adopt more than one topology during infection. We previously showed that the HD of the infectious bronchitis virus (IBV) E protein is required for the efficient release of infectious virus, an activity that correlated with disruption of the secretory pathway. Here we report that a single residue within the hydrophobic domain, Thr16, is required for secretory pathway disruption. Substitutions of other residues for Thr16 were not tolerated. Mutations of Thr16 did not impact virus assembly as judged by virus-like particle production, suggesting that alteration of secretory pathway and assembly are independent activities. We also examined how the membrane topology of IBV E affected its function by generating mutant versions that adopted either a transmembrane or membrane hairpin topology. We found that a transmembrane topology was required for disrupting the secretory pathway, but was less efficient for virus-like particle production. The hairpin version of E was unable to disrupt the secretory pathway or produce particles. The findings reported here identify properties of the E protein that are important for its function, and provide insight into how the E protein may perform multiple roles during infection.
The Determinants of State‐Level Caps on Punitive Damages: Theory and Evidence

Under the standard economic model of torts, punitive damages correct for imperfect detection. Incorporating litigation costs into the model provides a justification for punitive damage caps. At the optimum, caps balance deterrence against the cost of litigation. Empirical testing of the model is performed via Cox proportional and parametric hazard analyses, using a panel dataset from 1981 to 2007. The results reveal a positive relationship between judicial and legal expenditures (a proxy for legal costs) and cap enactment, and a negative relationship between state GSP (a proxy for damages) and cap enactment. Cap enactment is also influenced by political ideology.
Corporate sustainability: an IS approach for integrating triple bottom line elements

Purpose - – The purpose of this paper is to investigate the inter-relationships among three triple bottom line (TBL) outcomes of corporate sustainability, namely, corporate environmental performance outcome (CEPO), corporate social performance outcome (CSPO) and corporate financial performance outcome (CFPO), with the aid of an empirical study conducted in Australian businesses. The paper also aims to provide a roadmap for integrating sustainable business practices using information systems (IS) approach of continuous improvement lifecycle. Current business practices try to achieve economic, social and ecological goals independently as silos due to the individual operational challenges posed by each of these TBL principles. Design/methodology/approach - – The research design mainly adopts a quantitative research methodology with data collected by means of a survey questionnaire that included both descriptive and exploratory flavour. The empirical study examines the relationships of TBL elements as perceived by 85 different Australian-based large, medium as well as small business organisations. The data collected were analysed by performing factor analysis on 21 items, resulting in three latent factors that were aligned to TBL outcomes and the correlations among them were analysed to assess their inter-relationships. Findings - – The results of the study report weak and positive relationships existing between the TBL elements, with insights gained through the study leading towards useful implications that are well-supported by the qualitative feedback. The empirical study has also resulted in providing practical recommendations and an implementation framework consisting of a four-step roadmap with the participation of quality circles within an IS approach. Practical implications - – The study focuses on inter-relationships and integration of TBL elements in Australian businesses. This could be extended to other businesses in different countries. The proposed roadmap with a continuous improvement cycle of system implementation steps facilitates any organisation to adopt an incremental integration of the social responsibility and environment protection practices within its core business operations for achieving corporate sustainability. Originality/value - – While most of the TBL studies conducted worldwide focus on predominantly assessing large organisations towards responsible and sustainable business practices, this paper considers large, medium and small businesses. The research methodology adopted in this study as well as the proposed IS approach with quality circles add value to a growing body of literature with a recent increasing focus on integrated approaches for corporate sustainability.
Flaring and self-shadowed disks around Herbig Ae stars: simulations for 10 μm interferometers

We present simulations of the interferometric visibilities of Herbig Ae star disks. We investigate whether interferometric measurements in the 10μm atmospheric window are sensitive to the presence of an increased scale height at the inner disk edge, predicted by recent models. Furthermore, we investigate whether such measurements can discriminate between disks with a flaring geometry and disks with a flat geometry. We show that both these questions can be addressed, using measurements at a small number of appropriately chosen baselines. The classification of Herbig Ae stars in two groups, based on the appearance of the spectral energy distribution (SED), has been attributed to a difference in disk geometry. Sources with a group I SED would have a flaring outer disk geometry, whereas the disk of group II sources is proposed to be flat (or self-shadowed). We show that this hypothesis can be tested using long-baseline interferometric measurements in the 10μm atmospheric window.