Miracle-dz/UniFAR-FTUs huggingface dataset:
The Art of Deep Connection - Towards Natural and Pragmatic Conversational Agent Interactions

As research in Artificial Intelligence (AI) advances, it is crucial to focus on having seamless communication between humans and machines in order to effectively accomplish tasks. Smooth human-machine communication requires the machine to be sensible and human-like while interacting with humans, while simultaneously being capable of extracting the maximum information it needs to accomplish the desired task. Since a lot of the tasks required to be solved by machines today involve the understanding of images, training machines to have human-like and effective image-grounded conversations with humans is one important step towards achieving this goal. Although we now have agents that can answer questions asked for images, they are prone to failure from confusing input, and cannot ask clarification questions, in turn, to extract the desired information from humans. Hence, as a first step, we direct our efforts towards making Visual Question Answering agents human-like by making them resilient to confusing inputs that otherwise do not confuse humans. Not only is it crucial for a machine to answer questions reasonably, it should also know how to ask questions sequentially to extract the desired information it needs from a human. Hence, we introduce a novel game called the Visual 20 Questions Game, where a machine tries to figure out a secret image a human has picked by having a natural language conversation with the human. Using deep learning techniques like sequence-to-sequence learning (using recurrent neural networks) and reinforcement learning, we demonstrate promise towards scalable and reasonable performances on both the tasks.
The Impact of CCN Concentrations on the Thermodynamic and Turbulent State of Arctic Mixed-Phase Clouds

Abstract. Impacts of aerosol on mixed-phase cloud evolution play a potentially important role in Arctic climate, but remain poorly understood. The way in which aerosol, clouds and turbulence interact, is speculated to significantly modify the cloud evolution. There has been an increasing number of field observations of the ice clouds in Arctic, however it has proven hard to gain insight into these complex interactions using measurements alone. This model study aims to help filling this gap in the current understanding of low-level Arctic clouds, by combining high resolution simulations with new field campaign data. The main focus is on the impact of the cloud condensation nuclei concentration (CCN) on the properties of cloud and mixed-layer turbulence in an~evolving boundary layer. We configure semi-idealised model scenarios based on the weather situation observed over open ocean during two research flights of the ACLOUD campaign, which took place over Fram Strait northwest of Svalbard. A demi-Lagrangian frame of reference is adopted, with the model domain following low level air masses and the large-scale forcings derived from weather model analyses and short-range forecasts. Adjustments in the initial state are made based on comparison to dropsonde data. The simulations reproduce the observed general structure of the cloud-bearing Arctic mixed layer. Results further show that while the ice phase forms just a fraction of the mass of cloud water, it is responsible for most of the precipitation, in line with previous observational and LES studies. A lower initial CCN concentration generally results into a faster glaciation of the cloud, leading to a faster removal of the cloud water, and also affects the vertical structure of turbulence. Implications for radiative studies of clouds for the purpose of Arctic Amplification are discussed.
The Influence of DMAc Ratio in Sheath Fluid on the Diameters of Medicated Cellulose Acetate Nanofibers

Accurate manipulation of electrospun nanofibers’ diameter is highly sought after for realizing their functional performances. Different with traditional methods in reducing nanofiers’ size, the present job demonstrated that the compositions of sheath mixed solvent were able to exert a significant influence on the modified coaxial processes and correspondingly the final solid medicated nanofibers’ diameter. Scanning electron microscopic images showed that all the prepared ibuprofen-loaded cellulose acetate nanofibers had a linear morphology with few beads or spindles on them although they were prepared under a variable volume ratio of N, N-dimethylacetamide (DMAc) in the sheath mixture with acetone. The linear relationship between the medicated CA nanofibers’ diameter (D) and the volume ratio of DMAc in the sheath fluid (r) was D= 1013-685r, with a correlated coefficient of R=0.9835. The strategy reported should also be useful for other electrohydrodynamic atomization methods for generating high quality micro-/nano-products in a controllable manner.
Improvement of bacterial cellulose nonwoven fabrics by physical entrapment of lauryl gallate oligomers

The present study aimed to improve the properties of bacterial cellulose nonwoven fabrics by physical entrapment of lauryl gallate oligomers. The lauryl gallate oligomerization process was conducted by laccase-mediated oligomerization. Lauryl gallate was chemically confirmed by matrix-assisted laser desorption/ionization with time-of-flight analyses. The oligomerization conditions were controlled considering the surface properties (water contact angle, surface energy, and water absorption time) of bacterial cellulose nonwoven fabrics. The controlled oligomerization conditions were 160 U/mL of laccase and 20 mM lauryl gallate. After bacterial cellulose was treated by the physical entrapment of lauryl gallate oligomers, X-ray photoelectron spectroscopy analysis showed that the N1 atomic composition (%) of bacterial cellulose increased from 0.78% to 4.32%. This indicates that the lauryl gallate oligomer molecules were introduced into the bacterial cellulose nanofiber structure. In addition, the water contact angle was measured after washing the bacterial cellulose nonwoven fabric treated by the physical entrapment of lauryl gallate oligomers for 180 minutes, and it was found to maintain a water contact angle of 88°. The durability of bacterial cellulose nonwoven fabric treated by the physical entrapment of lauryl gallate oligomers was confirmed by measuring the tensile strength after wetting and dimensional stability. As a result, the tensile strength after wetting was about five times higher and the dimensional stability was three times higher than that of untreated bacterial cellulose nonwoven fabric.
Unterschiede in der biologischen Wirkung des Clostridium difficile Toxin B in proliferierenden und nicht-proliferierenden Zellen

Toxin A (TcdA) and toxin B (TcdB) from Clostridium difficile are the causative agents of the C. difficile-associated diarrhea (CDAD) and its severe form, the pseudomembranous colitis. TcdA and TcdB both glucosylate and thereby inactivate low molecular weight GTP-binding proteins of the Rho, Rac, and Cdc42 subfamilies. In cultured cell lines, TcdB induces actin reorganization and bi-nucleation (“cytopathic effects”) and cell death (“cytotoxic effects”). In this study, the role of cell cycle progression in the cytopathic and the cytotoxic effects of TcdB is evaluated by a differential analysis of these effects in proliferating and non-proliferating cells. Densitysynchronized murine fibroblasts and confluent HT29 colonocytes are exploited as cell culture models for nonproliferating cells. Cell death is analyzed in terms of a loss of cell viability, phosphatidylserine exposure, and DNA fragmentation. In proliferating cells, TcdB blocks cell proliferation and induces apoptotic cell death. In contrast, TcdB induces non-apoptotic cell death in non-proliferating cells. TcdB-induced cell rounding turns out to be independent of cell cycle progression. Cell cycle progression is an important determinant in the biological effects of TcdB. With respect to the pathology of CDAD, this study leads to the new hypothesis that necrotic cell death of terminally differentiated colonocytes and inhibition of epithelial renewal of the colon contribute to the pathogenesis of CDAD.
The role of medium on the assembly of carbon nanotube by dielectrophoresis

Abstract Dielectrophoresis (DEP) is an electrode-medium process used to control the movement of Carbon nanotubes (CNTs) within a solution under nonuniform electric fields. CNTs are typically dispersed into a solvent to form a homogeneous suspension in order to prevent their aggregation and to improve solubility. This paper starts with a short review of the techniques used to improve the compatibility of CNTs with a target medium. Then, direct and indirect variations in CNTs’ velocities as a function of DEP force were investigated, under different dispersion mediums, for a rectangular electrode pair with a 10 μm gap subjected to a 500 kHz AC signal with an amplitude of 10 V. The effects of changes in permittivity, conductivity, viscosity, and density of the medium were presented and discussed. Simulation results from this study were used to further clarify the role of the medium on the motion of CNTs during alignment using a DEP process prior to an actual alignment. Graphical Abstract
The logic design of a digital control computer.

This thesis presents the logic design of a digital control computer presently being constructed at the University of Windsor. The computer incorporates a pluggable program board, a magnetostrictive delay line memory, several working registers, and an arithmetic unit capable of addition, subt­ raction, multiplication, and division. The computer has the ability to modify data locations and to execute program jumps. Input facilities accept data from a keyboard and also from an external rotating shaft position digitizer. Output facilities are a set of lamps which indicate the contents of an accumu­ lator register and also an output order which can be used to control an external system. This thesis includes a complete set of logic diagrams of the computer, which utilizes NAND logic.
Multi-domain Adaptation for Statistical Machine Translation Based on Feature Augmentation

Domain adaptation is a major challenge when applying machine translation to practical tasks. In this paper, we present domain adaptation methods for machine translation that assume multiple domains. The proposed methods combine two model types: a corpus-concatenated model covering multiple domains and single-domain models that are accurate but sparse in specific domains. We combine the advantages of both models using feature augmentation for domain adaptation in machine learning. Our experimental results show that the BLEU scores of the proposed method clearly surpass those of single-domain models for low-resource domains. For high-resource domains, the scores of the proposed method were superior to those of both single-domain and corpusconcatenated models. Even in domains having a million bilingual sentences, the translation quality was at least preserved and even improved in some domains. These results demonstrate that state-of-the-art domain adaptation can be realized with appropriate settings, even when using standard log-linear models.
Solubility and Liquid Density of Ammonia/Athabasca Bitumen Mixtures at Temperatures up to 463 K: Measurements and Modeling

We report the experimental data of ammonia solubility in Athabasca bitumen measured at different temperatures and pressures ranging from 348 to 463 K and 1 to 4 MPa, respectively. The liquid-phase density of ammonia-saturated bitumen was measured for the samples that were taken during solubility measurements. The experimental data for ammonia solubility in bitumen were modeled using the Peng–Robinson equation of state. The volume-shift parameters of ammonia were tuned to represent the experimental density data of ammonia-saturated bitumen with an average absolute relative deviation percent (AARD%) of 0.218%. Also, tuning the binary interaction coefficient between ammonia and bitumen allowed the prediction of solubility data with an AARD of 8.537%. The data and the tuned model find applications in the reservoir modeling of solvent-aided thermal recovery of bitumen and heavy oil.
The Law of Load Variation and User’s Behavior Based on FFT Analysis

In order to study the change of load and the behavior of power users, this paper chooses the load of a large customer to analyze the power consumption. We can find the change trend and characteristics of power factor of power load by comparing the change trend between active and reactive power consumption. Using FFT filter on the active power and reactive power for low-pass filtering and high-pass filtering. And we can find the approximate range of frequency of power consumption. Finally, combing with band-pass filtering we can determine the frequency of power consumption fluctuating within a very small range. The research on the law of load variation and user's behavior can provide theoretical support for the follow-up power system research, which can improve the stability of power grid and improve the accuracy of load forecasting.
Production and Characterization of a New Variant of an Anti-Tnfα Antibody with Improved Affinity and Potency

Rapid growth in the therapeutic antibody market leads to a drastic development of antibody engineering to optimize biophysical properties. One of the main focuses of biopharmaceutical researches was the expansion of different approaches for affinity maturation of antibodies to enhance biological activity. Adalimumab (D2E7) is an anti-tumor necrosis factor alpha (TNFα) antibody used in the treatment of some autoimmune disorders like rheumatoid arthritis, psoriasis, etc. In this study, by engineering complementary determining regions (CDRs) of D2E7 antibody, we produced a new variant of the antibody with improved affinity and potency to TNFα. We designed four D2E7 mutants that harbored a single point mutation in their CDRs. The native antibody, lc-A94K, lc-A50Y, lc-A33R, and lc-A92R mutant models were transiently produced and characterized. Data showed mutation of ALA to LYS in CDR3 of D2E7 antibody generated new hydrogen bonds with TNFα, thus the lc-A94K model revealed significantly higher binding activity (EC50) and kinetic affinity (KD) to its antigen, in comparison to the wild antibody. Moreover, this model was found to have significantly stronger biological activity (IC50) to activate antibody-dependent cell-mediated cytotoxicity in the mouse fibroblast L929 cells. Secondary structure analysis demonstrated the mutation has no inappropriate conformational impact on the beta and alpha structures of lc-A94K antibody. In conclusion, our study revealed that it is possible to manipulate antibody’s CDRs to increase affinity and potency by single point mutation and also preserve basic structure of the original antibody during CDRs engineering to avoid adverse effects of CDRs mutations on specificity and stability.
In Silico Prediction of Isoliquiritigenin and Oxyresveratrol Compounds to BCL-2 dan VEGF-2 Receptors

Isoliquiritigenin and oxyresveratrol are compounds that have been reported to have anticancer activities. This study aimed to predict cytotoxic activity, toxicity and physicochemical properties of the compounds isoliquiritigenin and oxyresveratrol. Prediction of physicochemical properties referred to Lipinski rules of five using the pkCSM online tool. Prediction of compounds toxicity using Protox II online tool while ligand interaction with receptors using Molegro Virtual Docker (MVD). Vascular Endothelial Growth Factor Receptor-2 (VEGFR-2) (PDB: 2RL5) and B Cell Lymphoma BCL-2 (PDB: 4AQ3) were used as target cancer receptor proteins. In silico predictive results showed that oxyresveratrol and isoliquiritigenin complied with Lipinski rules of five, predictive values of LD50 between 500-2000 mg/kg respectively 1560 mg/kg and 1048 mg/kg. The docking result was in the form of bound energy described by Rerank Score (RS). A compound having a small RS value was predicted to have greater activity. RS of oxyresveratrol on 2RL5: -73.0413 and 4AQ3: -87.9985, while isoliquiritigenin on 2RL5: -68.0282 and 4AQ3: -78.5041. The cytotoxic activity of oxyresveratrol was also shown by hydrogen bonds in active amino acids (2RL5: Cys 919 in 4AQ3: Tyr 67). From docking results of both compounds, oxyreveratrol had greater activity than isoliquiritigenin to both target cancer receptor proteins and complied Lipinski rules of five and have a low toxicity.Keywords: cytotoxicity, toxicity, isoliquiritigenin, oxyresveratrol, in silico.
Nanoparticle Formation of Puerarin-beta-Cyclodextrin Inclusion Complex Using SEDS: Dissolution Enhancement

Inclusion complex nanoparticles of puerarin and β-cyclodextrin were prepared using solution-enhanced dispersion by supercritical fluids to improve the dissolution rate of puerarin. The factors that influenced particle size and inclusion yield such as, pressure, temperature, flow rate of CO2, and flow rate of the solution, were investigated. Scanning electron microscopy, X-ray diffraction and Fourier-transform infrared spectroscopy were used to characterize the products. Release behavior of inclusion complex nanoparticles of puerarin was also studied. Elevated temperatures increased the inclusion yield. Elevated pressures reduced the particle size. Scanning electron microscopy, X-ray diffraction and Fourier-transform infrared spectroscopy confirmed the formation of inclusion complex nanoparticles of puerarin. The accumulated release rate of inclusion complex nanoparticles of puerarin reached 98 % within 5 min, markedly higher than that of the puerarin powder and its physical mixture. Inclusion complex nanoparticles of puerarin prepared by solution-enhanced dispersion by supercritical fluids can greatly improve the in vitro release of puerarin.
Theoretical studies of pentazole-based compounds with high detonation performance

ABSTRACT Four types of pentazole ring-based organic compounds, including triaminotripentazolobenzene (TATPB), triaminotripentazolocyclohexane (TATPH), trinitrotripentazolobenzene (TNTPB) and trinitrotripentazolocyclohexane (TNTPH) were designed and investigated by ab initio quantum chemistry methods. The geometric structure in the gas phase, electrostatic potential, HOMO-LUMO orbitals, and Wiberg bond orders was calculated at the level of B3LYP/6-311g. Several properties were predicted based on the calculation results above. Among the four compounds, TNTPB has the highest predicted packing density (1.85 g cm−3), the highest theoretical enthalpy of formation in solid phase (1486.89 kJ mol−1) and the most powerful theoretical detonation performance (D = 9.36 km s−1 and P = 38.05 GPa). The detonation properties of TNTPB are comparable to the new generation of explosives. Two possible solid phases of TNTPB in P and P21/c space groups were predicted. The periodic structures were optimized by periodic first-principles calculations with van der Waals correction. Ab initio molecular dynamics simulations were performed to confirm that TNTPB had the higher detonation growth rate than TATB (2,4,6-trinitro-1,3,5-benzenetriamine). We proposed that introducing the pentazole rings into designing high energy density materials (HEDMs) is an effective method for not only improving the detonation performance but also accelerating the detonation growth.
Deactivation Pathway of Ras GTPase Underlies Conformational Substates as Targets for Drug Design

Aberrant activation of Ras GTPase is closely associated with human cancers. Mechanistic and structural insights into conformational transitions underlying the Ras deactivation pathway provide opportunities for the development of targeted therapies for the treatment of Ras-driven cancers. It remains challenging, however, to completely capture a large-scale conformational transition by atomistic molecular dynamics (MD) simulations. Here, we carry out a computational scheme that combines a transition pathway generation algorithm, extensive MD simulations, and Markov state model analysis for disclosing the conformational landscape of the Ras deactivation pathway. Our findings suggest a stepwise deactivation pathway for Ras hydrolysis and identify several key conformational substates along the deactivation pathway. Furthermore, we discover an unexplored and potentially allosteric binding site on the effector-binding region of Ras in the conformational substates, which is further supported by site-directed muta.
Effects of microplastic and microglass particles on soil microbial community structure in an arable soil (Chernozem)

Abstract. Microplastic and microglass particles from different sources enter aquatic and terrestrial environments. The complexity of their environmental impact is difficult to capture, and the consequences for ecosystem components, for example, the soil microorganisms, are virtually unknown. To address this issue, we performed an incubation experiment by adding 1 % of five different types of impurities (≤100 µm) to an agriculturally used soil (Chernozem) and simulating a worst-case scenario of contamination. The impurities were made of polypropylene (PP), low-density polyethylene (LDPE), polystyrene (PS), polyamide 12 (PA12) and microglass. After 80 d of incubation at 20 ∘C, we examined the soil microbial community structure by using phospholipid fatty acids (PLFAs) as markers for bacteria, fungi and protozoa. The results showed that soil microorganisms were not significantly affected by the presence of microplastic and microglass. However, PLFAs tend to increase with LDPE (28 %), PP (19 %) and microglass (11 %) in treated soil in comparison with untreated soil, whereas PLFAs in PA12 (32 %) and PS (11 %) in treated soil decreased. Interestingly, PLFAs revealed significant differences in PA12 (−89 %) and PS (−43 %) in comparison with LDPE. Furthermore, variability of bacterial PLFAs was much higher after microplastic incubation, while fungi seemed to be unaffected from different impurities after 80 d of incubation. Similar results were shown for protozoa, which were also more or less unaffected by microplastic treatment as indicated by the minor reduction in PLFA contents compared to the control group. In contrast, microglass seems to have an inhibiting effect on protozoa because PLFAs were under the limit of determination. Our study indicated that high amounts of different microplastics may have contrary effects on soil microbiology. Microglass might have a toxic effect for protozoa.
Utilizing the Organizational Power of DNA Scaffolds for New Nanophotonic Applications

Rapid development of DNA technology has provided a feasible route to creating nanoscale materials. DNA acts as a self‐assembled nanoscaffold capable of assuming any three‐dimensional shape. The ability to integrate dyes and new optical materials such as quantum dots and plasmonic nanoparticles precisely onto these architectures provides new ways to exploit their near‐ and far‐field interactions. A fundamental understanding of these optical processes will help drive development of next‐generation photonic nanomaterials. This review is focused on latest progress in DNA‐based photonic materials and highlights DNA scaffolds for rapidly assembling and prototyping nanoscale optical devices. Three areas are discussed including intrinsically active DNA structures displaying chiral properties, DNA scaffolds hosting plasmonic nanomaterials, and fluorophore‐labeled DNAs that engage in Förster resonance energy transfer and give rise to complex molecular photonic wires. An explanation of what is desired from these optical processes when harnessed sets the tone for what DNA scaffolds are providing toward each focus. Examples from the literature illustrate current progress along with a discussion of challenges to overcome for further improvements. Opportunities to integrate diverse classes of optically active molecules including light‐generating enzymes, fluorescent proteins, nanoclusters, and metal–chelates in new structural combinations on DNA scaffolds are also highlighted.