Miracle-dz/UniFAR-FTUs huggingface dataset:
A Digitally Current Mode Controlled Non-Inverting Buck-Boost Converter for Fast Voltage Transitions

Mode configurations in a non-inverting buck-boost (NIBB) converter offer wide voltage variations and make it useful for reference tracking applications. However, the reference transient performance is limited by the presence of right-half-plane (RHP) zero in the boost-mode. Further, the controller design based on linear small signal models often ignores switching dynamics and fails to capture the performance under large signal transients. This paper proposes a digital current mode control (CMC) tuning method in a NIBB converter for fast voltage transitions from buck-mode to the boost-mode and back in dynamic voltage scaling (DVS), LED driving, and envelope tracking. This considers a mixed-signal current mode control architecture with a simple PI voltage controller in the digital domain along with a reference feed-forward. Using phase-plane geometry, the objective is to tune the proportional gain, which drives the large signal transient recovery from buck-mode to the boost-mode and vice-versa. The proposed tuning method achieves near time optimal transient recovery using a fixed-frequency modulator throughout. Moreover, a reference feed-forward also ensures smooth mode transitions by adjusting the average inductor current in each mode of operation. A NIBB prototype is made and the proposed tuning method is experimentally verified using a Xilinx Virtex-5 FPGA device.
A Novel Loom of Click Chemistry in Drug Discovery

Click chemistry is an interesting and novel approach for drug discovery, material science, bioconjugation, radiochemistry and nanoscience. It meets an ever-increasing need for rapid reaction as it fulfills the criterion of an ideal synthesis: efficiency, versatility, selectivity and high yield with variety of starting materials. The present review summarizes all the aspects of 1, 3-dipolar cycloaddition reaction “click reaction” between azides and alkynes catalyzed by copper salts. The ease of purification of products and simplicity of this reaction has opened new pathways in generating vast arrays of compounds with biological potential. Many important reactions fit the concept of click chemistry than others such as cycloaddition of unsaturated species. The present review will outline the deeds of click reaction and its medicinal chemistry application in which click chemistry might be relevant in future.
Nano-engineered design and manufacturing of high-performance epoxy matrix composites with carbon fiber/selectively integrated graphene as multi-scale reinforcements

Three different architectural designs are developed for manufacturing advanced multi-scale reinforced epoxy based composites in which graphene sheets and carbon fibers are utilized as nano- and micro-scale reinforcements, respectively. In the first design, electrospraying technique as an efficient and up-scaleable method is employed for the selective deposition of graphene sheets onto the surface of carbon fabric mats. Controlled and uniform dispersion of graphene sheets on the surface of carbon fabric mats enhances the interfacial strength between the epoxy matrix and carbon fibers and increases the efficiency of load transfer between matrix and reinforcing fibers. In the second design, graphene sheets are directly dispersed into the hardener-epoxy mixture to produce carbon fiber/epoxy composites with graphene reinforced matrix. In the third design, the combination of the first and the second arrangements is employed to obtain a multi-scale hybrid composite with superior mechanical properties. The effect of graphene sheets as an interface modifier and as a matrix reinforcement as well as the synergetic effect due to the combination of both arrangements are investigated in details by conducting various physical–chemical characterization techniques. Graphene/carbon fiber/epoxy composites in all three different arrangements of graphene sheets show enhancement in in-plane and out of plane mechanical performances. In the hybrid composite structure in which graphene sheets are used as both interface modifier and matrix reinforcing agent, remarkable improvements are observed in the work of fracture by about 55% and the flexural strength by about 51% as well as notable enhancement on other mechanical properties.
Separation of Isoquinoline and Its Homologue

With quinoline resid as raw material, the influence of PID control on the experimental result under different conditions was evaluated by configuring PID parameters and amplifying properties difference between isoquinoline and its homologue through the use of modified mordenite and metal wire mesh fillings. The result of experiment shows that it is able to obtain quinoline and isoquinoline whose yields range from 80% to 85% and purity ranges from 95% to 98% in the self-made 3 L semi-auto rectification equipment.
The Classical Limit of QuantumTheory

This essay treats of the relationship between quantum and classical mechanics. Both physicists and philosophers hold that quantum mechanics reduces to classical mechanics as �� 0, or that classical mechanics is a special case of quantum mechanics in this limit. If one theory reduces to another, certain formal and nonformal conditions must be satisfied. These conditions are formulated and it is shown that the Wigner transformation can serve as a natural reduction function in a reduction which satisfies the formal and non­ formal conditions. Finally, it is argued that this reduction does not aid in solving the problem of providing an adequate metaphysical interpretation of quantum theory.
I Like What You Like: Social Norms and Media Enjoyment

ABSTRACT People consume and enjoy similar media entertainment as their friends and close others do. Yet the underlying psychological processes driving selection and consumption of entertainment considered “mainstream” within a group are still unclear. Given that individuals’ behaviors and attitudes are influenced by the perceived prevalence of others’ behaviors (descriptive norms) and perceptions of what others approve (injunctive norms), we examined the role of descriptive and injunctive norms in media selection and enjoyment. In an online experiment, we tested whether norm messages affected perceptions of group norms, and whether these perceptions influenced the enjoyment of a movie trailer and intention to watch the full film. We also tested the moderating roles of group identity and proximity on perceived norms and subsequent effects. Results showed that norm messages predicted perceived descriptive norms, which in turn predicted enjoyment of the trailer and intention to watch the film. Norm messages also predicted perceived injunctive norms, and the effect of injunctive norms on outcome variables was strengthened by group proximity and identity. The discussion highlights ways that social norms can inform understandings of socially-influenced media enjoyment and selection in future work and unique opportunities to study normative influence in a media setting.
Associating Preoperative MRI Features and Gene Expression Signatures of Early-stage Hepatocellular Carcinoma Patients using Machine Learning

Background and Aims The relationship between quantitative magnetic resonance imaging (MRI) imaging features and gene-expression signatures associated with the recurrence of hepatocellular carcinoma (HCC) is not well studied. Methods In this study, we generated multivariable regression models to explore the correlation between the preoperative MRI features and Golgi membrane protein 1 (GOLM1), SET domain containing 7 (SETD7), and Rho family GTPase 1 (RND1) gene expression levels in a cohort study including 92 early-stage HCC patients. A total of 307 imaging features of tumor texture and shape were computed from T2-weighted MRI. The key MRI features were identified by performing a multi-step feature selection procedure including the correlation analysis and the application of RELIEFF algorithm. Afterward, regression models were generated using kernel-based support vector machines with 5-fold cross-validation. Results The features computed from higher specificity MRI better described GOLM1 and RND1 gene-expression levels, while imaging features computed from lower specificity MRI data were more descriptive for the SETD7 gene. The GOLM1 regression model generated with three features demonstrated a moderate positive correlation (p<0.001), and the RND1 model developed with five variables was positively associated (p<0.001) with gene expression levels. Moreover, RND1 regression model integrating four features was moderately correlated with expressed RND1 levels (p<0.001). Conclusions The results demonstrated that MRI radiomics features could help quantify GOLM1, SETD7, and RND1 expression levels noninvasively and predict the recurrence risk for early-stage HCC patients.
A Sampling-based Motion Planning Framework for Complex Motor Actions

We present a framework for planning complex motor actions such as pouring or scooping from arbitrary start states in cluttered real-world scenes. Traditional approaches to such tasks use dynamic motion primitives (DMPs) learned from human demonstrations. We enhance a recently proposed state-of-the-art DMP technique capable of obstacle avoidance by including them within a novel hybrid framework. This complements DMPs with sampling-based motion planning algorithms, using the latter to explore the scene and reach promising regions from which a DMP can successfully complete the task. Experiments indicate that even obstacle-aware DMPs suffer in task success when used in scenarios which largely differ from the trained demonstration in terms of the start, goal, and obstacles. Our hybrid approach significantly outperforms obstacle-aware DMPs by successfully completing tasks in cluttered scenes for a pouring task in simulation. We further demonstrate our method on a real robot for pouring and scooping tasks.
Integrated radiogenomics models predict response to neoadjuvant chemotherapy in high grade serous ovarian cancer

High grade serous ovarian cancer (HGSOC) is a highly heterogeneous disease that often presents at an advanced, metastatic state. The multi-scale complexity of HGSOC is a major obstacle to measuring response to neoadjuvant chemotherapy (NACT) and understanding its determinants. Here we propose a radiogenomic framework integrating clinical, radiomic, and blood-based biomarkers to measure and predict the response of HGSOC patients to NACT, showing how quantitative imaging data can serve as the backbone of multi-scale data integration. We developed and validated our approach in two independent highly-annotated multi-omic multi-lesion data sets. In a discovery cohort (n=72) we found that different tumour sites present distinct response patterns, and identified volumetric response assessment as a better predictor of overall survival (OS) than RECIST~1.1 status. We trained an ensemble machine learning approach to predict tumour volume response to NACT from data obtained prior to treatment, and validated the model in an internal hold-out cohort (n=20) and an independent external patient cohort (n=42). Benchmarking integrated models against models built on single data types highlighted the importance of comprehensive patient characterisation. Our study sets the foundation for developing new clinical trials of NACT in HGSOC.
Using the Weighted Kendall Distance to Analyze Rank Data in Psychology

Although the Kendall distance is a standard metric in computer science, it is less widely used in psychology. We demonstrate the usefulness of the Kendall distance for analyzing psychological data that take the form of ranks, lists, or orders of items. We focus on weighted extensions of the metric that allow for heterogeneity of item importance, item position, and item similarity, as well showing how the metric can accommodate missingness in the form of top-k lists. To demonstrate how the Kendall distance can help address research questions in psychology, we present four applications to previous data. These applications involve the recall of events on September 11, people's preference rankings for the months of the year, people's free recall of animal names in a clinical setting, and expert predictions involving American football outcomes.
Manufacturing Revolutions: Industrial Policy and Industrialization in South Korea

I study the impact of industrial policy on industrial development by considering a canonical intervention. Following a political crisis, South Korea dramatically altered its development strategy with a sector-specific industrial policy: the Heavy and Chemical Industry (HCI) drive, 1973-1979. With newly assembled data, I use the sharp introduction and withdrawal of industrial policies to study the impacts of industrial policy---during and after the intervention period. I show (1) HCI promoted the expansion and dynamic comparative advantage of directly targeted industries. (2) Using variation in exposure to policies through the input-output network, I show HCI indirectly benefited downstream users of targeted intermediates. (3) I find direct and indirect benefits of HCI persisted even after the end of HCI, following the 1979 assassination of the president. These effects include the eventual development of directly targeted exporters and their downstream counterparts. Together, my findings suggest that the temporary drive shifted Korean manufacturing into more advanced markets and created durable industrial change. These findings clarify lessons drawn from South Korea and the East Asian growth miracle.
De-anchored Long-term Inflation Expectations in a Low Growth, Low Rate Environment

This paper provides evidence of de-anchoring of long-term inflation expectations in the euro area based on both time series and panel methods and data from the ECB Survey of Professional Forecasters. Long-term inflation expectations recorded two sharp and permanent declines: the first after the 2013 disinflation, the second in early 2019. Long-term inflation expectations also started reacting to short-term developments in inflation after the 2013 disinflation. Long-term growth expectations have declined continuously since the early 2000s. Looking forward, the increased likelihood of a low growth and low inflation environment may reduce the monetary policy space. The positive correlation between long-term real GDP growth and inflation expectations suggests that forecasters view future macroeconomic developments as driven mainly by demand-side shocks. Under these circumstances, the risk of a further de-anchoring of long-term inflation expectations remains high.
Influence of isomorphous substitution of metal ion on the low-frequency dielectric dispersion in NH2(CH3)2Al1−xCrx(SO4)2⋅6H2O ferroelectrics

ABSTRACT This paper is devoted to the study of the influence of metal ion isomorphous substitution on the ferroelastic-ferroelectric phase transition and dispersion caused by the motion of domain walls in dimethylammonium metal sulfate hexahydrate DMAAl1−xCrxS ferroelectric crystals (x = 0, 0.065, 0.2). It is shown that such a substitution significantly changes the phase transition temperature and parameters of the dielectric dispersion. These changes are explained in terms of interaction between the metal-hydrate complexes and DMA groups that carry the dipole moment and due to this they are responsible for the phase transitions and motion of the domain walls.
National Culture and the Value Implications of Corporate Environmental and Social Performance

We examine why environmental and social (E/S) performance vary across countries and firms, and evaluate the value implications. Using a sample of 33,021 firm-year observations representing 4,587 firms from 43 countries over the 2003–2015 period and applying hierarchical linear modeling, we find that individualism is positively associated with firm-level E/S performance. We show that two country-level channels—freedom of the press and protection of equal rights—and three firm-level channels—managerial discretion, board diversity, and corporate transparency—link individualism to E/S performance. We find a positive association between firm-level E/S performance and firm value, with three firm-level channels—cash flows, cash flow variability, and cost of equity—linking E/S performance to firm value. This positive association is stronger in more individualistic countries. Finally, we find that internationalization weakens the role of national culture; however, it accentuates the positive association between firm-level E/S performance and firm value.
Integrating LSTMs and GNNs for COVID-19 Forecasting

The spread of COVID-19 has coincided with the rise of Graph Neural Networks (GNNs), leading to several studies proposing their use to better forecast the evolution of the pandemic. Many such models also include Long Short Term Memory (LSTM) networks, a common tool for time series forecasting. In this work, we further investigate the integration of these two methods by implementing GNNs within the gates of an LSTM and exploiting spatial information. In addition, we introduce a skip connection which proves critical to jointly capture the spatial and temporal patterns in the data. We validate our daily COVID-19 new cases forecast model on data of 37 European nations for the last 472 days and show superior performance compared to state-of-the-art graph time series models based on mean absolute scaled error (MASE). This area of research has important applications to policy-making and we analyze its potential for pandemic resource control.
Correlation between Molecular Packing and Surface Potential at Vanadyl Phthalocyanine/HOPG Interface

We report on the thickness-dependent morphology and surface potential of vanadyl phthalocyanine (VOPc) ultrathin films due to the variations between lying-down and tilted molecular packing configurations at the interface of VOPc film/highly ordered pyrolytic graphite (HOPG). Transition from a bilayer-thickness-dependent distribution to an orientation-dependent inhomogeneity of surface potential is observed in the same film. The surface potential change in the initial lying-down bilayers can be described by the abrupt junction model. In areas thicker than ca. 6 nm, a potential energy difference of about 100 meV between differently oriented VOPc molecular layers is found, indicating that the boundaries act as significant barriers for hole transport.
Crystal Structures and Exotic Behavior of Magnesium under Pressure

The high-pressure structures of magnesium (Mg) have been extensively explored through our newly developed particle swarm optimization algorithm on crystal structural prediction. Two structures with face-centered cubic (fcc) and simple hexagonal (sh) symmetries are discovered to be stable at 456−756 GPa and above 756 GPa, respectively. Especially, the sh structure, which is known to occur at high pressure in P, Si, and Ge, is reported here for Mg. This structure can be derived from the fcc lattice by distortion of the α and γ angles from 60° to 90°. More intriguingly, the calculated valence electron localization function reveals an electride nature of the fcc and sh structures with valence electrons localized in the interstitial regions, analogous to what was recently reported in Li, Na, K, and Ca under high pressure. However, what makes Mg unique is that it remains metallic. The temperature−pressure phase diagram of Mg has also been explored using quasi-harmonic approximation, and the finite-temperature p.
VERTICAL DISTRIBUTIONS OF SIZE-FRACTIONATED IRON IN THREE TYPICAL BAYS OF LAKE DIANCHI (CHINA)

In order to elucidate the vertical distributions of iron in three typical bays (Haigeng bay, Macun bay and Haidong bay) of Lake Dianchi (China), the investigation was conducted on March, 2003. Results showed that the vertical distributions were influenced by monsoon, cyanobacterial bloom and water depth as well as sediment resuspension, which indicated that their translocations and transformations were decided by geographical and physical as well as chemical and biological characteristics.
Toward the Supramolecular Cyclodextrin Dimers Using Nucleobase Pairs

The synthesis of eleven new cyclodextrin derivatives having nucleobase moiety - thymin-1-yl, adenin-9-yl, and guanin- 9-yl - is described. These two moieties are linked by different spac- ers, such as aminoethyl and 1,2,3-triazolyl group. Direct nucleo- philic substitution and 1,3-dipolar cycloaddition were performed in good yields (13-73%) for some of the synthesized compounds.
Using a Veriﬁable and Decentralized Ledger as a Basis for Trusting Hospital Endpoints

The whitebox system is a system for controlling access to conﬁdential medical data. General practicioners hold conﬁdential data for their patients, and own a whitebox which controls remote access to that data. These whiteboxes establish hospital endpoints as trusted to access conﬁdential data by having patients transfer a code to the hospital organization. Once enough of these code transfers have taken place, an endpoint is considered trusted. We propose a system for registering trust between an endpoint and a whitebox. By recording trust by whiteboxes in a decentralized blockchain ledger, we allow whiteboxes to check trust in an endpoint by other whiteboxes. Endpoints trusted by other whiteboxes may be considered trusted. The ledger uses a proof-of-authority consensus algorithm, where white-boxes are the authority on blocks describing their own trust. By recording both positive and negative trust, the system provides a mechanism for removing the trust from an endpoint that acts maliciously. We analyze the security of the proposed system by considering its vulnerability to denial-of-service and inference attacks, as well as attempts to establish false trust by malicious whiteboxes. Finally, we analyze the scaling of a prototype implementation. For application within the dutch healthcare system, we ﬁnd that the proposed system scales well enough both in term of disk-space use and trust check speed.
Astrocytes in the Ventromedial Hypothalamus Involve Chronic Stress-Induced Anxiety and Bone Loss in Mice

Chronic stress is one of the main risk factors of bone loss. While the neurons and neural circuits of the ventromedial hypothalamus (VMH) mediate bone loss induced by chronic stress, the detailed intrinsic mechanisms within the VMH nucleus still need to be explored. Astrocytes in brain regions play important roles in the regulation of metabolism and anxiety-like behavior through interactions with surrounding neurons. However, whether astrocytes in the VMH affect neuronal activity and therefore regulate chronic stress-induced anxiety and bone loss remain elusive. In this study, we found that VMH astrocytes were activated during chronic stress-induced anxiety and bone loss. Pharmacogenetic activation of the Gi and Gq pathways in VMH astrocytes reduced and increased the levels of anxiety and bone loss, respectively. Furthermore, activation of VMH astrocytes by optogenetics induced depolarization in neighboring steroidogenic factor-1 (SF-1) neurons, which was diminished by administration of N-methyl-D-aspartic acid (NMDA) receptor blocker but not by alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor blocker. These results suggest that there may be a functional “glial-neuron microcircuit” in VMH nuclei that mediates anxiety and bone loss induced by chronic stress. This study not only advances our understanding of glial cell function but also provides a potential intervention target for chronic stress-induced anxiety and bone loss therapy.