Miracle-dz/UniFAR-FTUs huggingface dataset:
Tomato TILLING Technology: Development of a Reverse Genetics Tool for the Efficient Isolation of Mutants from Micro-Tom Mutant Libraries

To accelerate functional genomic research in tomato, we developed a Micro-Tom TILLING (Targeting Induced Local Lesions In Genomes) platform. DNA pools were constructed from 3,052 ethyl methanesulfonate (EMS) mutant lines treated with 0.5 or 1.0% EMS. The mutation frequency was calculated by screening 10 genes. The 0.5% EMS population had a mild mutation frequency of one mutation per 1,710 kb, whereas the 1.0% EMS population had a frequency of one mutation per 737 kb, a frequency suitable for producing an allelic series of mutations in the target genes. The overall mutation frequency was one mutation per 1,237 kb, which affected an average of three alleles per kilobase screened. To assess whether a Micro-Tom TILLING platform could be used for efficient mutant isolation, six ethylene receptor genes in tomato (SlETR1–SlETR6) were screened. Two allelic mutants of SlETR1 (Sletr1-1 and Sletr1-2) that resulted in reduced ethylene responses were identified, indicating that our Micro-Tom TILLING platform provides a powerful tool for the rapid detection of mutations in an EMS mutant library. This work provides a practical and publicly accessible tool for the study of fruit biology and for obtaining novel genetic material that can be used to improve important agronomic traits in tomato.
Yangians and Classical Lie Algebras

Contents §0. Introduction §1. The Yangian §2. The quantum determinant and the centre of §3. The twisted Yangian §4. The Sklyanin determinant and the centre of §5. The quantum contraction and the quantum Liouville formula for the Yangian §6. The quantum contraction and the quantum Liouville formula for the twisted Yangian §7. The quantum determinant and the Sklyanin determinant of block matrices Bibliography
The Dual Role of an ESCRT-0 Component HGS in HBV Transcription and Naked Capsid Secretion

The Endosomal Sorting Complex Required for Transport (ESCRT) is an important cellular machinery for the sorting and trafficking of ubiquitinated cargos. It is also known that ESCRT is required for the egress of a number of viruses. To investigate the relationship between ESCRT and hepatitis B virus (HBV), we conducted an siRNA screening of ESCRT components for their potential effect on HBV replication and virion release. We identified a number of ESCRT factors required for HBV replication, and focused our study here on HGS (HRS, hepatocyte growth factor-regulated tyrosine kinase substrate) in the ESCRT-0 complex. Aberrant levels of HGS suppressed HBV transcription, replication and virion secretion. Hydrodynamic delivery of HGS in a mouse model significantly suppressed viral replication in the liver and virion secretion in the serum. Surprisingly, overexpression of HGS stimulated the release of HBV naked capsids, irrespective of their viral RNA, DNA, or empty contents. Mutant core protein (HBc 1–147) containing no arginine-rich domain (ARD) failed to secrete empty virions with or without HGS. In contrast, empty naked capsids of HBc 1–147 could still be promoted for secretion by HGS. HGS exerted a strong positive effect on the secretion of naked capsids, at the expense of a reduced level of virions. The association between HGS and HBc appears to be ubiquitin-independent. Furthermore, HBc is preferentially co-localized with HGS near the cell periphery, instead of near the punctate endosomes in the cytoplasm. In summary, our work demonstrated the importance of an optimum level of HGS in HBV propagation. In addition to an effect on HBV transcription, HGS can diminish the pool size of intracellular nucleocapsids with ongoing genome maturation, probably in part by promoting the secretion of naked capsids. The secretion routes of HBV virions and naked capsids can be clearly distinguished based on the pleiotropic effect of HGS involved in the ESCRT-0 complex.
Essays in Behavioral and Experimental Economics

Chapter I We use a large-scale internet experiment to explore how subjects learn to play against computers that are programmed to follow one of a number of standard learning algorithms. The learning theories are (unbeknown to subjects) a best response process, fictitious play, imitation, reinforcement learning, and a trial & error process. We explore how subjects' performances depend on their opponents' learning algorithm. Furthermore, we test whether subjects try to influence those algorithms to their advantage in a forward-looking way (strategic teaching). We find that strategic teaching occurs frequently and that all learning algorithms are subject to exploitation with the notable exception of imitation. Chapter II In a punishment experiment, we separate the demand for punishment in general from a possible demand to conduct punishment personally. Subjects experience an unfair split of their earnings from a real effort task and have to decide on the punishment of the person who determines the distribution. First, it is established whether the allocator's payoff is reduced and, afterwards, subjects take part in a second price auction for the right to (physically) carry out the act of payoff reduction. This auction only resolves who will punish, not whether punishment takes place, so only subjects with a demand for personal punishment should bid. Chapter III This paper experimentally investigates whether risk-averse individuals punish less if the outcome of punishment is uncertain than when it is certain. We compare subjects’ behavior in two treatments: Certain Punishment in which the prisoner’s dilemma game is followed by a punishment stage allowing subjects to decrease the other player’s payoff by 2 Euros; and Uncertain Punishment in which subjects could decrease the other player’s payoff with a 50% probability by 1 Euro and with a 50% probability by 3 Euros. We observe only several instances of punishment in our setup. Consequently, we find that in both cases risk-averse subjects are equally likely to cooperate in the prisoner’s dilemma and equally likely to punish in the punishment stage. Chapter IV Does a mere availability of punishment increase cooperation in the one-shot prisoner’s dilemma game? In our experiment we observe that the subjects almost never use punishment. Consistently, the data shows no increase in the cooperation rate as the subjects correctly anticipated that they would not be punished for defection. Thus, the availability of punishment is ineffective in inducing cooperation in a one-shot game. Moreover, we do not find any evidence that risk attitude is a factor when making the decision to cooperate.
Chandra Observations of Type Ia Supernovae: Upper Limits to the X-Ray Flux of SN 2002bo, SN 2002ic, SN 2005gj, and SN 2005ke

We set sensitive upper limits to the X-ray emission of four Type Ia supernovae (SNe Ia) using the Chandra X-Ray Observatory. SN 2002bo, a normal, although reddened, nearby SN Ia, was observed 9.3 days after explosion. For an absorbed, high-temperature bremsstrahlung model the flux limits are 3.2 × 10-16 ergs cm-2 s-1 (0.5-2 keV band) and 4.1 × 10-15 ergs cm-2 s-1 (2-10 keV band). Using conservative model assumptions and a 10 km s-1 wind speed, we derive a mass-loss rate of Ṁ ~ 2 × 10-5 M☉ yr-1, which is comparable to limits set by the nondetection of Hα lines from other SNe Ia. Two other objects, SN 2002ic and SN 2005gj, observed 260 and 80 days after explosion, respectively, are the only SNe Ia showing evidence for circumstellar interaction. The SN 2002ic X-ray flux upper limits are ~4 times below predictions of the interaction model currently favored to explain the bright optical emission. To resolve this discrepancy, we invoke the mixing of cool dense ejecta fragments into the forward shock region, which produces increased X-ray absorption. A modest amount of mixing allows us to accommodate the Chandra upper limit. SN 2005gj is less well studied at this time. Assuming the same circumstellar environment as for SN 2002ic, the X-ray flux upper limits for SN 2005gj are ~4 times below the predictions, suggesting that mixing of cool ejecta into the forward shock has also occurred here. Our reanalysis of Swift and Chandra data on SN 2005ke does not confirm a previously reported X-ray detection. The host galaxies NGC 3190 (SN 2002bo) and NGC 1371 (SN 2005ke) each harbor a low-luminosity [LX ~ (3-4) × 1040 ergs s-1] active nucleus in addition to widespread diffuse soft X-ray emission.
An Average-Case Analysis of the Gaussian Algorithm for Lattice Reduction

The Gaussian algorithm for lattice reduction in dimension 2 is analysed under its standard version. It is found that, when applied to random inputs in a continuous model, the complexity is constant on average, its probability distribution decays geometrically, and the dynamics are characterized by a conditional invariant measure. The proofs make use of connections between lattice reduction, continued fractions, continuants, and functional operators. Analysis in the discrete model and detailed numerical data are also presented.
Bullies and blackouts: Examining the participatory culture of online book reviewing

This article examines online book reviewing practices through Henry Jenkins’s notion of ‘participatory culture’ and illustrates the power dynamics and market pressures that shape this participation. While the individuals featured in this article participate in shared affinity spaces around a passion for reading and writing books, they also participate in a publishing industry increasingly reliant on reviews and ratings. I argue that the sabotaging and bullying of authors and reviewers, and the power dynamics reinforced through these tactics, risk being occluded by scholarship that emphasizes the literacy practices fostered through participatory culture over the content and social actions reproduced through them. My analysis of book reviewing practices demonstrates the need to critique the positive imagery evoked by terms like ‘participatory’, ‘affinity’, ‘online community’, ‘shared goals’, and ‘collective knowledge’ and to examine these terms within their specific discursive and economic conditions.
Integrability in SFT and new representation of KP tau-function

We are investigating the properties of vacuum and boundary states in the CFT of free bosons under the conformal transformation. We show that transformed vacuum (boundary state) is given in terms of tau-functions of dispersionless KP (Toda) hierarchies. Applications of this approach to string field theory is considered. We recognize in Neumann coefficients the matrix of second derivatives of tau-function of dispersionless KP and identify surface states with the conformally transformed vacuum of free field theory. boyarsky@alf.nbi. dk On leave of absence from Bogolyubov ITP, Kiev, Ukraine ruchay@flash.uchicago. edu
Multi-modal analysis of dance performances for music-driven choreography synthesis

We propose a framework for modeling, analysis, annotation and synthesis of multi-modal dance performances. We analyze correlations between music features and dance figure labels on training dance videos in order to construct a mapping from music measures (segments) to dance figures towards generating music-driven dance choreographies. We assume that dance figure segment boundaries coincide with music measures (audio boundaries). For each training video, figure segments are manually labeled by an expert to indicate the type of dance motion. Chroma features of each measure are used for music analysis. We model temporal statistics of such chroma features corresponding to each dance figure label to identify different rhythmic patterns for that dance motion. The correlations between dance figures and music measures, as well as, correlations between consecutive dance figures are used to construct a mapping for music-driven dance choreography synthesis. Experimental results demonstrate the success of proposed music-driven choreography synthesis framework.
HIV Type-1 Drug Resistance in Treatment-Naive Patients Monitored Using Minority Species Assays: A Systematic Review and Meta-Analysis

Background The detection of mutations associated with drug resistance in HIV type-1 might be increased by applying minority species assays capable of identifying low frequency mutations in comparison with the use of population sequencing alone. Because minority species assays are mutation-specific, the benefit of this approach differs depending on the mutation being detected. Methods We performed a systematic review of published data reporting detection of genotypic drug resistance using allele-specific (AS)-PCR minority assays and by standard DNA sequencing in drug-naive populations. We calculated the fold increase of mutation detection for each study and pooled these via meta-analysis, displaying results using Forest plots. Results Our studies revealed an increase in detection of 1.9-fold (95% confidence interval [CI] 1.3–2.7; P<0.0005) for K103N, 4.4-fold (95% CI 1.2–16.6; P=0.026) for Y181C, 4.8-fold (95% CI 1.5–15.1; P=0.008) for L90M and 8.7-fold (95% CI 4.0–18.6; P<0.0005) for M184V. We found no relationship between AS-PCR assay sensitivity and frequency of additional mutation detection. Conclusions Additional detection of drug resistance mutations using AS-PCR minority mutation assays vary significantly depending on the mutation examined; however, the most marked increase in detection of resistance mutations was observed for M184V, a mutation seldom detected by standard techniques in drug-naive patients. We suggest that the presence of drug resistance mutations can be more accurately estimated using a combination of AS-PCR and standard genotyping.
ESSE: an early software size estimation method based on auto-extracted requirements features

Software size estimation is a crucial step in project management. According to the Standish Chaos Report, 65% of software projects are over budget or deadline; therefore, a good size estimation method is very important. However, existing estimation methods are complicated and human-effort consuming. In many industrial projects, project technical leads (PTLs) do not use these methods but just give a rough estimation based on their experience. To decrease human effort, we propose an early software size estimation (ESSE) method, which can extract semantic features from natural language requirements automatically, and build size estimation models for project. Firstly, ESSE makes a two-level semantic analysis of requirements specification documents by information extraction and activation spreading. Then, complexity-related features are extracted from the results of semantic analysis. Finally, a size estimation model is trained to predict size of new projects by regression algorithms. Experiments in real industrial datasets show that our method is effective and can be applied to real industrial projects.
Analysis on Community Charactristics of Online Social Network

With the rapid development of large-scale online social network applications, understanding the community characteristics of online social networks is benefit to improve application performance. Characteristics of communities are studied based on real measurements of You Tube, a popular online social network. Adapt to the huge scale of online social networks, we modify the original community discovery algorithm, the label propagation algorithm, to reach a balance between goodness of community division and time efficiency. We analyze the distribution of community and group sizes and the relation between community structure and group membership user explicitly claimed. Our experiment show that both the community sizes and group sizes follow a power-law distribution and the dependency of community membership on the group membership is evident, but the latter is neither the only nor the main origin of the community structure. Also, we studied assortative matching, degree distribution of the entire network and the largest scale of community. The results confirm that assortativity matching of the entire network is much higher than inter-communities, both in degree and out degree distributions of the largest scale community and the network satisfy power-law property.
Bu-Shen-Ning-Xin decoction: inhibition of osteoclastogenesis by abrogation of the RANKL-induced NFATc1 and NF-κB signaling pathways via selective estrogen receptor α

Introduction Bu-Shen-Ning-Xin decoction (BSNXD) is a traditional Chinese medicinal composition that has been used as a remedy for postmenopausal osteoporosis, but the mechanisms affecting bone metabolism are not fully understood. Purpose We investigated the molecular mechanism and signaling pathway underlying the effect of BSNXD on osteoclastogenesis. Materials and methods A postmenopausal osteoporosis animal model generated by ovariectomy was administered BSNXD and drug-derived serum was prepared. An enzyme immunoassay was conducted to measure the 17-β-estradiol (E2) concentration in the drug-derived serum. Bone marrow-derived monocyte/macrophage precursor cells were treated with drug-derived serum, and tartrate-resistance acid phosphatase staining was conducted to observe osteoclastogenesis. A bone resorption assay was performed to analyze the effect on osteoclastic resorptive function. Real-time PCR, flow cytometry, Western blotting, transfection, and luciferase assays were conducted to explore the related mechanism. Results E2 was not elevated in BSNXD-derived serum. BSNXD-derived serum suppressed receptor activation of nuclear factor κB ligand (RANKL)-activated osteoclastogenesis in a dose-dependent manner; this effect could be reversed by estrogen receptor α antagonist methyl-piperidino-pyrazole. The serum suppressed RANKL-induced NF-κB transcription and inhibited the accumulation of nuclear factor of activated T-cells, cytoplasmic 1 in osteoclast precursor cells; the inhibitory effect was abolished by methyl-piperidino-pyrazole but not the estrogen receptor β antagonist or androgen receptor antagonist. Conclusion These results collectively suggest that administration of BSNXD presents inhibitory effects on osteoclast differentiation by abrogating the RANKL-induced nuclear factor of activated T-cells, cytoplasmic 1 and NF-κB signaling pathways downstream of estrogen receptor α, thereby contributing to the inhibitory effect on bone resorption.
A CLASSIFICATION SCHEME OF AMINO ACIDS IN THE GENETIC CODE BY GROUP THEORY

This paper provides a group theoretical model that enables us to calculate polarity and molecular volume of amino acids to a good approximation. Group theory provides insight into problems by helping uncover and exploit underlying symmetries. Our approach to the classification of “building constituents of the biosphere” is motivated by group theory’s success in particle physics and chemistry. We derive the amino acid assignment to one codon representation (typical 64-dimensional irreducible representation) of the basic classical Lie superalgebra osp(5|2) from biochemical arguments. This work is one step in achieving our objectives to complete our comprehension of the genetic language, to make genetic research more accessible to mathematical methods which have proven to be powerful in physics and chemistry, and to make predictions about the synthesis of
CONVERGENCE ANALYSIS OF AN INTERIOR-POINT METHOD FOR NONCONVEX NONLINEAR PROGRAMMING

In this paper, we present global and local convergence results for an interior-point method for nonlinear programming. The algorithm uses an `1 penalty approach to relax all constraints, to provide regularization, and to bound the Lagrange multipliers. The penalty problems are solved using a simplified version of Chen and Goldfarb’s strictly feasible interior-point method [6]. The global convergence of the algorithm is proved under mild assumptions, and local analysis shows that it converges Q-quadratically. The proposed approach improves on existing results in several ways: (1) the convergence analysis does not assume boundedness of dual iterates, (2) local convergence does not require the Linear Independence Constraint Qualification, (3) the solution of the penalty problem is shown to locally converge to optima that may not satisfy the Karush-Kuhn-Tucker conditions, and (4) the algorithm is applicable to mathematical programs with equilibrium constraints.
Genetic Algorithm Approach to Construction of Specialized Multi-Classifier Systems: Application to DNA Analysis

Learning algorithms aim for accuracy of classification but this depends on a choice of heuristic metric to measure performance and also on the proper consideration and addressing of the important requirements of the classification task. This paper introduces a framework, MVGen, to implement different training heuristics capable of inducing the training algorithm that can provide the desired results while negating detrimental aspects of a training set imbalance. Our experiments indicate that successful classifiers can indeed be built to specialize on the minority class within an imbalanced data set.
Subjective Outcomes Assessment in Chronic Rhinosinusitis

The treatment of chronic rhinosinusitis (CRS) requires an increasing use of medical and economic resources. Therefore, the assessment of objective and subjective outcome of different treatment strategies is of considerable interest. Validated quality of life (QOL) instruments are one important means to assess subjective outcome of the patients. Frequently used generic instruments are the Short Form 36 Health Survey (SF-36) for prospective evaluations and the Glasgow Benefit Inventory (GBI) for retrospective evaluations. Normative data and numerous comparative data sets collected from various diseases are available for the SF-36. Disease-specific QOL instruments for CRS have been developed over the last 15 years. In this review 11 disease-specific instruments are discussed. Only four of these instruments cover all four main symptoms of CRS and are completely validated as well. Most frequently used instruments (Sino-Nasal Outcome Test, SNOT-20; Chronic Sinusitis Survey, CSS) do not query all the main symptoms of CRS. Until the nineteen-nineties the evaluation of success was straitened to the reporting of complications, revision surgery rates etc. It was postulated that normal and non- inflammatory endoscopic clinical findings were always a successful result even for the patient. However, frequently strong divergences between clinical findings and subjective patient reports had to be noted (10). Furthermore, computed tomography (CT) which is the most important imaging method in these patients could not establish significant correlations between imaging and symptom severity. Since the nineteen-eighties quality of life (QOL) instruments were systematically developed and validated for use in clinical medicine to achieve the goal of measuring the subjective outcome of the patients. The first instruments for use in patients with CRS were developed in the nineteen- nineties. In the following general and disease-specific QOL instruments which are in use in patients with CRS are presented.