Miracle-dz/UniFAR-FTUs huggingface dataset:
Single-Step Purification / Solubilization of Recombinant Proteins : Application to Surfactant Protein B

telling the program where the tubing should go next (vial number or B for buffer) and how long it should stay there. These robot control programs can be saved on disk and loaded into memory to be executed when required. Figure 1 shows that two oocyte rigs can be simultaneously perfused by the robot. The Hamilton HV3-3 valve located just above the platform allows for either or both to be perfused with buffer. The robot cannot, however, perform different experiments on each rig simultaneously. The sample tracings obtained using hand vs. robotic transfer of perfusion tubing are shown in Figure 2. In this experiment, Xenopus oocyte nuclei were injected with 0.3 ng/30 nL human glycine α1 receptor subunit cDNA, and the oocytes were treated as described in Mihic et al. (1). Figure 2 shows two sets of tracings using 50 μM, 75 μM and 100 μM glycine, one obtained after transferring the perfusion tubing by hand, and the second using the robot. The peak heights observed were virtually identical. The use of robotic techniques as well as multiple oocyte rigs allows for more rapid data acquisition, subject of course to the nature of the experiment and the quality of oocytes. It may be especially useful for the automated testing of large numbers of compounds on defined receptors. Furthermore, this inexpensive robotic technique can be used not only for Xenopus oocyte perfusion, but in any assay system involving the pumping of various buffers. A schematic of the rotary table Lucite disk drill holes and the executable code of our robot control software may be freely obtained upon request. The QuickBasic 4.0 source code will also be provided, except for the Arrick Robotics core subroutines, which are provided by the manufacturer upon the purchase of an MD-2 dual-stepper motor system.
Behavior of greedy sparse representation algorithms on nested supports

In this work, we study the links between the recovery properties of sparse signals for Orthogonal Matching Pursuit (OMP) and the whole General MP class over nested supports. We show that the optimality of those algorithms is not locally nested: there is a dictionary and supports I and J with J included in I such that OMP will recover all signals of support I, but not all signals of support J. We also show that the optimality of OMP is globally nested: if OMP can recover all s-sparse signals, then it can recover all s'-sparse signals with s' smaller than s. We also provide a tighter version of Donoho and Elad's spark theorem, which allows us to complete Tropp's proof that sparse representation algorithms can only be optimal for all s-sparse signals if s is strictly lower than half the spark of the dictionary.
Pharmacologic Inhibition of the Menin–MLL Interaction Leads to Transcriptional Repression of PEG10 and Blocks Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) accounts for approximately 85% of malignant liver tumors and results in 600,000 deaths each year, emphasizing the need for new therapies. Upregulation of menin was reported in HCC patients and high levels of menin correlate with poor patient prognosis. The protein–protein interaction between menin and histone methyltransferase mixed lineage leukemia 1 (MLL1) plays an important role in the development of HCC, implying that pharmacologic inhibition of this interaction could lead to new therapeutic strategy for the HCC patients. Here, we demonstrate that the menin–MLL inhibitor MI-503 shows antitumor activity in in vitro and in vivo models of HCC and reveals the potential mechanism of menin contribution to HCC. Treatment with MI-503 selectively kills various HCC cell lines and this effect is significantly enhanced by a combination of MI-503 with sorafenib, the standard-of-care therapy for HCC. Furthermore, MI-503 reduces sphere formation and cell migration in in vitro HCC models. When applied in vivo, MI-503 gives a strong antitumor effect both as a single agent and in combination with sorafenib in mice xenograft models of HCC. Mechanistically, treatment with MI-503 downregulates expression of several genes known to play a critical role in proliferation and migration of HCC cells, including PEG10, and displaces the menin–MLL1 complex from the PEG10 promoter, resulting in reduced H3K4 methylation and transcriptional repression. Overall, our studies reveal a mechanistic link between menin and genes involved in HCC and demonstrate that pharmacologic inhibition of the menin–MLL interaction might represent a promising therapeutic approach for HCC. Mol Cancer Ther; 17(1); 26–38. ©2017 AACR.
SmartUnit: Empirical Evaluations for Automated Unit Testing of Embedded Software in Industry

In this paper, we aim at the automated unit coverage-based testing for embedded software. To achieve the goal, by analyzing the industrial requirements and our previous work on automated unit testing tool CAUT, we rebuild a new tool, SmartUnit, to solve the engineering requirements that take place in our partner companies. SmartUnit is a dynamic symbolic execution implementation, which supports statement, branch, boundary value and MC/DC coverage. SmartUnit has been used to test more than one million lines of code in real projects. For confidentiality motives, we select three in-house real projects for the empirical evaluations. We also carry out our evaluations on two open source database projects, SQLite and PostgreSQL, to test the scalability of our tool since the scale of the embedded software project is mostly not large, 5K-50K lines of code on average. From our experimental results, in general, more than 90% of functions in commercial embedded software achieve 100% statement, branch, MC/DC coverage, more than 80% of functions in SQLite achieve 100% MC/DC coverage, and more than 60% of functions in PostgreSQL achieve 100% MC/DC coverage. Moreover, SmartUnit is able to find the runtime exceptions at the unit testing level. We also have reported exceptions like array index out of bounds and divided-by-zero in SQLite. Furthermore, we analyze the reasons of low coverage in automated unit testing in our setting and give a survey on the situation of manual unit testing with respect to automated unit testing in industry. SmartUnit is a dynamic symbolic execution implementation, which supports statement, branch, boundary value and MC/DC coverage. SmartUnit has been used to test more than one million lines of code in real projects. For confidentiality motives, we select three in-house real projects for the empirical evaluations. We also carry out our evaluations on two open source database projects, SQLite and PostgreSQL, to test the scalability of our tool since the scale of the embedded software project is mostly not large, 5K-50K lines of code on average. From our experimental results, in general, more than 90% of functions in commercial embedded software achieve 100% statement, branch, MC/DC coverage, more than 80% of functions in SQLite achieve 100% MC/DC coverage, and more than 60% of functions in PostgreSQL achieve 100% MC/DC coverage. Moreover, SmartUnit is able to find the runtime exceptions at the unit testing level. We also have reported exceptions like array index out of bounds and divided-by-zero in SQLite. Furthermore, we analyze the reasons of low coverage in automated unit testing in our setting and give a survey on the situation of manual unit testing with respect to automated unit testing in industry.
MRLR: Multi-level Representation Learning for Personalized Ranking in Recommendation

Representation learning (RL) has recently proven to be effective in capturing local item relationships by modeling item co-occurrence in individual user's interaction record. However, the value of RL for recommendation has not reached the full potential due to two major drawbacks: 1) recommendation is modeled as a rating prediction problem but should essentially be a personalized ranking one; 2) multi-level organizations of items are neglected for fine-grained item relationships. We design a unified Bayesian framework MRLR to learn user and item embeddings from a multi-level item organization, thus benefiting from RL as well as achieving the goal of personalized ranking. Extensive validation on real-world datasets shows that MRLR consistently outperforms state-of-the-art algorithms.
Theories of scanning probe microscopes at the atomic scale

Significant progress has been made both in experimentation and in theoretical modeling of scanning probe microscopy. The theoretical models used to analyze and interpret experimental scanning probe microscope (SPM) images and spectroscopic data now provide information not only about the surface, but also the probe tip and physical changes occurring during the scanning process. The aim of this review is to discuss and compare the present status of computational modeling of two of the most popular SPM methods-scanning tunneling microscopy and scanning force microscopy-in conjunction with their applications to studies of surface structure and properties with atomic resolution. In the context of these atomic-scale applications, for the scanning force microscope (SFM), this review focuses primarily on recent noncontact SFM (NC-SFM) results. After a brief introduction to the experimental techniques and the main factors determining image formation, the authors consider the theoretical models developed for the scanning tunneling microscope (STM) and the SFM. Both techniques are treated from the same general perspective of a sharp tip interacting with the surface-the only difference being that the control parameter in the STM is the tunneling current and in the SFM it is the force. The existing methods for calculating STM and SFM images are described and illustrated using numerous examples, primarily from the authors' own simulations, but also from the literature. Theoretical and practical aspects of the techniques applied in STM and SFM modeling are compared. Finally, the authors discuss modeling as it relates to SPM applications in studying surface properties, such as adsorption, point defects, spin manipulation, and phonon excitation.
Better Safe than Sorry? Ex Ante and Ex Post Moral Hazard in Dynamic Insurance Data

This paper empirically analyzes moral hazard in car insurance using a dynamic theory of an insuree's dynamic risk (ex ante moral hazard) and claim (ex post moral hazard) choices and Dutch longitudinal micro data. We use the theory to characterize the heterogeneous dynamic changes in incentives to avoid claims that are generated by the Dutch experience-rating scheme, and their effects on claim times and sizes under moral hazard. We develop tests that exploit these structural implications of moral hazard and experience rating. Unlike much of the earlier literature, we find evidence of moral hazard.
An Adaptive Feature Learning Model for Sequential Radar High Resolution Range Profile Recognition

This paper proposes a new feature learning method for the recognition of radar high resolution range profile (HRRP) sequences. HRRPs from a period of continuous changing aspect angles are jointly modeled and discriminated by a single model named the discriminative infinite restricted Boltzmann machine (Dis-iRBM). Compared with the commonly used hidden Markov model (HMM)-based recognition method for HRRP sequences, which requires efficient preprocessing of the HRRP signal, the proposed method is an end-to-end method of which the input is the raw HRRP sequence, and the output is the label of the target. The proposed model can efficiently capture the global pattern in a sequence, while the HMM can only model local dynamics, which suffers from information loss. Last but not least, the proposed model learns the features of HRRP sequences adaptively according to the complexity of a single HRRP and the length of a HRRP sequence. Experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) database indicate that the proposed method is efficient and robust under various conditions.
Continuous-time group consensus using distributed event-triggered control

Group consensus has both positive and negative communication weights, which is an extension to traditional consensus problem. Additionally, distributed event-triggered control has advantages over periodic control considering energy consumption and communication constraints. Thus, it is important to study group consensus using event-triggered control. Moreover, by calculating the maximum and minimum of the corresponding parameters, we can simplify the event-triggered function. The implementation will validate the effectiveness of our distributed control protocol.
Structural Insights into c-Myc-interacting Zinc Finger Protein-1 (Miz-1) Delineate Domains Required for DNA Scanning and Sequence-specific Binding*

c-Myc-interacting zinc finger protein-1 (Miz-1) is a poly-Cys2His2 zinc finger (ZF) transcriptional regulator of many cell cycle genes. A Miz-1 DNA sequence consensus has recently been identified and has also unveiled Miz-1 functions in other cellular processes, underscoring its importance in the cell. Miz-1 contains 13 ZFs, but it is unknown why Miz-1 has so many ZFs and whether they recognize and bind DNA sequences in a typical fashion. Here, we used NMR to deduce the role of Miz-1 ZFs 1–4 in detecting the Miz-1 consensus sequence and preventing nonspecific DNA binding. In the construct containing the first 4 ZFs, we observed that ZFs 3 and 4 form an unusual compact and stable structure that restricts their motions. Disruption of this compact structure by an electrostatically mismatched A86K mutation profoundly affected the DNA binding properties of the WT construct. On the one hand, Miz1–4WT was found to bind the Miz-1 DNA consensus sequence weakly and through ZFs 1–3 only. On the other hand, the four ZFs in the structurally destabilized Miz1–4A86K mutant bound to the DNA consensus with a 30-fold increase in affinity (100 nm). The formation of such a thermodynamically stable but nonspecific complex is expected to slow down the rate of DNA scanning by Miz-1 during the search for its consensus sequence. Interestingly, we found that the motif stabilizing the compact structure between ZFs 3 and 4 is conserved and enriched in other long poly-ZF proteins. As discussed in detail, our findings support a general role of compact inter-ZF structures in minimizing the formation of off-target DNA complexes.
Research on Flow Rule and Thermal Dissipation Between the Rotor Poles of a Fully Air-Cooled Hydrogenerator

Aiming at providing a theoretical basis for the 1000-MW giant fully air-cooled hydrogenerator, which is being studied and developed currently, this paper established a coupling calculation model of 3-D fluid and temperature field based on the actual structure and size of a 250-MW fully air-cooled fanless hydrogenerator. Fluid dynamics control equations, and corresponding boundary conditions in the solved region were given. The additional losses from electromagnetic field calculation were applied to the coupling model as heat sources. Using a computational fluid dynamics approach, the flow distribution of cooling air and the temperature distribution of rotor structures were obtained. It focused on the axial and radial variation rules of the flow condition of cooling air between adjacent poles. Meanwhile, it conducted a detailed research study on the variation rule of the heat-transfer coefficients of pole shoes and damping bars. Temperature calculated value of exciting windings was coincident well with the measured value. The calculated error between the two values meets the engineering requirement, thus verifying both applicability and accuracy of the solution method this paper presents.
Understanding the Success and Failure of Oyster Populations: Periodicities of Perkinsus marinus, and Oyster Recruitment, Mortality, and Size

ABSTRACT Ten-year time series (1992 to 2002) of salinity, Dermo disease, and size-class structure and mortality measured for an eastern oyster (Crassostrea virginica) population at a reef in Bay Tambour, Terrebonne Parish, LA, were analyzed using wavelet techniques to determine dominant frequencies and correlations. Along the Gulf Coast of the United States, Dermo disease (caused by Perkinsus marinus) responds to the El Niño-Southern Oscillation (ENSO) climate signal through its response to salinity. During the La Niña portion of ENSO, decreased rainfall leads to an increase in salinity, which triggers a rise in Dermo disease prevalence and intensity, producing increased oyster mortality. Although disease responds to the 4-y periodicity of ENSO and salinity, the oyster population dynamics do not appear to be controlled by disease at this site. A significant 4-y coherency exists between recruitment and salinity, with recruitment being higher during periods of high salinity. Recruit numbers and submarket numbers also exhibit a strong 4-y periodicity. However, a relationship between the recruit time series and the subsequent change in market-size abundance did not exist. The complexity of postsettlement processes and the extended time over which these processes interact decrease the predictability of the recruit-to-market transition. Even the strong pulse of recruits associated with La Niña and its locally elevated salinities did not result in an exceptional abundance of market oysters. Understanding the environmental and biotic factors that favor the production of large oysters is critical because large oysters not only supply the fishery, but, upon their death, contribute the bulk of the shell required for reef sustainability.
Robust control of piezostage for nanoscale three-dimensional images acquisition

Piezoelectric drivers are widely used in nanoscale image acquisition systems. A source of performance degradation of these drivers is hysteresis, which introduces low rate noise and causes a slow continuous drift, decreasing the quality of scanned images. In this paper a sliding mode control policy, based on an estimator of the perturbation due to hysteresis, is applied to the control of a piezostage in a three dimensional images acquisition system, in order to improve control performances and final scanning results. The presented solution has been experimentally tested and compared with the Proportional-Integrative-Derivative (PID) controllers provided with the piezoelectric acquisition system, showing a noticeable improvement both in the piezostage behavior and in the images quality.
A novel current harmonic compensation based on resonant controllers for a selective active filter

This paper addresses a novel control algorithm for a selective active filter compensating specific harmonic currents and the fundamental negative-sequence component of the load current. The proposed control algorithm combines the resonant controller with a PLL circuit to determine the current references in αβ frame. Previous works introduced control algorithms for a selective active filter connected to radial grid, in dq frame, where the load currents were no longer used to determine the current references. However the transient performance of the active filter was compromised, once the current references are indirectly determined and, moreover, due to the presence of low-pass filters. Now, this work proposes an algorithm where the low-pass filters is removed, therefore the overall control algorithm becomes simpler to be implemented with the active filter presenting a faster transient response. Simulation results are presented to evaluate the proposed algorithm with the active filter compensating symmetrical harmonic currents under transient- and steady-state conditions.
Urmia Lake Watershed Restoration in Iran: Short- and Long-Term Perspectives

Urmia Lake (also known as Oroumieh Lake) is a shallow terminal lake located in northwest Iran and one of the largest permanent lakes in the Middle East. Due to its biodiversity it has been designated as a Biosphere Reserve by UNESCO and a National Park under the 1971 Ramsar Convention. At present, the entire lake’s watershed is threatened due to drought and abrupt decline of the lake’s water level and the consequent increase of salinity. The rapidly declining eco-environmental conditions have serious impacts on the socio-economy of the whole region. In this paper we review the environmental state of art and suggest measures to improve the lake’s ecology by short- and long-term restoration possibilities. There are indications that the hydrology of the area could be described by a chaotic climate and a low-dimensional dynamical system. However, also the human impact is strong due to mismanagement of water resources. It is concluded that a multidisciplinary integrated approach is needed to tackle the current critical situation.
Improved Descriptors for the Quantitative Structure-Activity Relationship Modeling of Peptides and Proteins

The ability to model the activity of a protein using quantitative structure-activity relationships (QSAR) requires descriptors for the 20 naturally coded amino acids. In this work we show that by modifying some established descriptors we were able to model the activity data of 140 mutants of the enzyme epoxide hydrolase with improved accuracy. These new descriptors (referred to as physical descriptors) also gave very good results when tested against a series of four dipeptide data sets. The physical descriptors encode the amino acids using only two orthogonal scales: the first is strongly linked to hydrophilicity/hydrophobicity, and the second, to the volume of the amino acid residue. The use of these new amino acid descriptors should result in simpler and more readily interpretable models for the enzyme activity (and potentially other functions of interest, e.g., secondary and tertiary structure) of peptides and proteins.
From morbid obesity to a healthy weight using cognitive-behavioral methods: a woman's three-year process with one and one-half years of weight maintenance.

BACKGROUND Obesity is a national health problem regularly confronting medical professionals. Although reduced-energy (kilocalorie [kcal]) eating and increased exercise will reliably reduce weight, these behaviors have been highly resistant to sustained change. OBJECTIVE To control eating using theory-based cognitive-behavioral methods that leverage the positive psychosocial effects of newly initiated exercise as an alternate to typical approaches of education about appropriate nutrition. METHOD A woman, age 48 years, with morbid obesity initiated exercise through a 6-month exercise support protocol based on social cognitive and self-efficacy theory (The Coach Approach). This program was followed by periodic individual meetings with a wellness professional intended to transfer behavioral skills learned to adapt to regular exercise, to then control eating. There was consistent recording of exercises completed, foods consumed, various psychosocial and lifestyle factors, and weight. RESULTS Over the 4.4 years reported, weight decreased from 117.6 kg to 59.0 kg, and body mass index (BMI) decreased from 43.1 kg/m(2) to 21.6 kg/m(2). Mean energy intake initially decreased to 1792 kcal/day and further dropped to 1453 kcal/day by the end of the weight-loss phase. Consistent with theory, use of self-regulatory skills, self-efficacy, and overall mood significantly predicted both increased exercise and decreased energy intake. Morbid obesity was reduced to a healthy weight within 3.1 years, and weight was maintained in the healthy range through the present (1.3 years later). CONCLUSION This case supports theory-based propositions that exercise-induced changes in self-regulation, self-efficacy, and mood transfer to and reinforce improvements in corresponding psychosocial factors related to controlled eating.