Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of Binding Thermodynamics in the Optimization of BH3 Mimetics

The use of small molecule B‐cell lymphoma 2 homology domain 3 mimetics to neutralize the B‐cell lymphoma 2 protein is an attractive strategy for cancer treatment due to its ability to cause targeted cell apoptosis. We have previously reported the design and optimization of a series of B‐cell lymphoma 2 homology domain 3‐mimetics, called compounds 1–6. In this study, we evaluated the optimization of B‐cell lymphoma 2 homology domain 3‐mimetics from a thermodynamic perspective. Understanding the thermodynamic parameters of B‐cell lymphoma 2 homology domain 3‐mimetics plays a critical role in the development of B‐cell lymphoma 2 small‐molecule inhibitors. The thermodynamic parameters for the interactions of these compounds with the myeloid cell leukemia sequence 1 protein were obtained using isothermal titration calorimetry. Owing to compounds 1–6 overcoming enthalpy–entropy compensation, the affinities of them improved gradually. Toward binding to the myeloid cell leukemia sequence 1 protein, compound 6 was deemed optimal with an obtained Kd value of 238 nm, which is a 104‐fold improvement compared with 1. Analysis of the enthalpy and −TΔS efficiencies showed that ligand efficiencies with respect to molecular size are correlated with the enthalpic efficiencies. Notably, an enthalpy gain of 4.65 kcal/mol identified that an additional hydrogen bond is formed by 2 with myeloid cell leukemia sequence 1 compared with compound 1. For the first time, hydrogen bonding between a small‐molecule inhibitor of B‐cell lymphoma 2 was demonstrated experimentally.
Deployment of an Innovative Resource Choice Method for Process Planning

Designers, process planners and manufacturers naturally consider different concepts for a same object. The stiffness of production means and the design specification requirements mark out process planners as responsible of the coherent integration of all constraints. First, this paper details an innovative solution of resource choice, applied for aircraft manufacturing parts. In a second part, key concepts are instanced for the considered industrial domain. Finally, a digital mock up validates the solution viability and demonstrates the possibility of an in-process knowledge capitalisation and use. Formalising the link between Design and Manufacturing allows to hope enhancements of simultaneous Product / Process developments.
Origin and timing of sand injection, petroleum migration, and diagenesis in Tertiary reservoirs, south Viking Graben, North Sea

Petrographic, fluid-inclusion, and carbon and oxygen stable isotope studies of Tertiary injectite reservoirs in the south Viking Graben of the North Sea allow an understanding of the origin and timing of sand injection, petroleum migration, and diagenesis. Injection from shallowly (400 m; 1300 ft) buried Paleocene and Eocene unconsolidated sandstones occurred at the end of the Eocene, probably in response to earthquake activity. Liquid oil was already present in the parent sands prior to injection and leaked from the injectites to the seabed. Upward-migrating oil and basinal brines mixed with downward-invading mixed meteoric-marine pore fluids in the injectites, causing extensive biodegradation of the oil. Biodegradation of oil provided the driver for early carbonate cementation in injectites, causing diminished reservoir quality. However, early carbonate cementation also sealed off the injectites as potential escape routes for petroleum from the underlying parent sands. Oil (and gas) continued to migrate into the reservoir (parent) sands upon increased burial, causing a mixing of high-API oil with the early charged, extensively biodegraded low-API oil. The study of early diagenetic imprints reveals the evolution of injectite reservoirs, which forms the basis for understanding how to explore and develop them.
Centering: A Parametric Theory and Its Instantiations

Centering theory is the best-known framework for theorizing about local coherence and salience; however, its claims are articulated in terms of notions which are only partially specified, such as utterance, realization, or ranking. A great deal of research has attempted to arrive at more detailed specifications of these parameters of the theory; as a result, the claims of centering can be instantiated in many different ways. We investigated in a systematic fashion the effect on the theory's claims of these different ways of setting the parameters. Doing this required, first of all, clarifying what the theory's claims are (one of our conclusions being that what has become known as Constraint 1 is actually a central claim of the theory). Secondly, we had to clearly identify these parametric aspects: For example, we argue that the notion of pronoun used in Rule 1 should be considered a parameter. Thirdly, we had to find appropriate methods for evaluating these claims. We found that while the theory's main claim about salience and pronominalization, Rule 1a preference for pronominalizing the backward-looking center (CB)is verified with most instantiations, Constraint 1a claim about (entity) coherence and CB uniquenessis much more instantiation-dependent: It is not verified if the parameters are instantiated according to very mainstream views (vanilla instantiation), it holds only if indirect realization is allowed, and is violated by between 20 and 25 of utterances in our corpus even with the most favorable instantiations. We also found a trade-off between Rule 1, on the one hand, and Constraint 1 and Rule 2, on the other: Setting the parameters to minimize the violations of local coherence leads to increased violations of salience, and vice versa. Our results suggest that entity coherencecontinuous reference to the same entitiesmust be supplemented at least by an account of relational coherence.
Sampled-data output regulation of linear system based on input delay approach

In this paper, a output regulation problem with time-varying sampling interval is investigated. An input delay approach is used to convert a sampled data feedback system into a continuous time-delay systems. Two sufficient conditions for the output regulation problem are presented in terms of LMIs. Finally, a numerical simulation example is given to demonstrate the effectiveness of the developed analytic results.
Heterogeneous multi-hop LEACH routing protocol

An energy efficient routing protocol is the major concern in Wireless Sensor Networks (WSNs). In this paper, we describe LEACH routing protocol and some of its new versions. After that we propose an energy efficient hierarchical routing protocol, developed from LEACH. The basic concept involved in increasing energy efficiency and hence lifetime is to keep radio communication distance as minimum as possible The new version of LEACH uses heterogeneous multilevel clustering approach based on the distance of base station from cluster heads. We have used three different types of nodes based on their initial energy level. They have played different roles depending whether they are the member nodes or the cluster heads. The proposed algorithm is successfully simulated in MATLAB and the results show that it is more energy efficient than homogeneous LEACH.
Gap Junctions Compensate for Sublinear Dendritic Integration in an Inhibitory Network

Spreading the Excitation Inhibitory interneurons balance network excitation, control spike-time precision of principal neurons, and control synchrony within and across brain regions. Vervaeke et al. (p. 1624, published online 8 March) combined electrophysiology, immunohistology, and numerical simulation to investigate the properties of Golgi cells, the main inhibitory interneurons in the input layer of the cerebellar cortex. The dendrites of these neurons were truly passive and acted as linear cables. Gap junctions were distributed nonuniformly on the Golgi cell surface, with a higher density on distal dendrites. Thus, gap junction-mediated lateral excitation preferentially enhanced the distal inputs, enabling distal synapses to drive network activity more effectively. Synaptic charge spreads into the dendrites of neighboring interneurons via dendritic gap junctions. Electrically coupled inhibitory interneurons dynamically control network excitability, yet little is known about how chemical and electrical synapses regulate their activity. Using two-photon glutamate uncaging and dendritic patch-clamp recordings, we found that the dendrites of cerebellar Golgi interneurons acted as passive cables. They conferred distance-dependent sublinear synaptic integration and weakened distal excitatory inputs. Gap junctions were present at a higher density on distal dendrites and contributed substantially to membrane conductance. Depolarization of one Golgi cell increased firing in its neighbors, and inclusion of dendritic gap junctions in interneuron network models enabled distal excitatory synapses to drive network activity more effectively. Our results suggest that dendritic gap junctions counteract sublinear dendritic integration by enabling excitatory synaptic charge to spread into the dendrites of neighboring inhibitory interneurons.
Collaboration and Team Science

Interdisciplinary efforts are becoming more critical for scientific discovery and translational research efforts. Highly integrated and interactive research teams share a number of features that contribute to their success in developing and sustaining their efforts over time. Through analysis of in-depth interviews with members of highly successful research teams and others who did not meet their goals or ended because of conflicts, we identified key elements that are critical for team success and effectiveness. There is no debate that the scientific goal sits at the center of the collaborative effort. However, supporting features need to be in place to avoid the derailment of the team. Among the most important of these is trust: without trust, the team dynamic runs the risk of deteriorating over time. Other critical factors of which both leaders and participants need to be aware include developing a shared vision, strategically identifying team members and purposefully building the team, promoting disagreement while containing conflict, and setting clear expectations for sharing credit and authorship. Self-awareness and strong communication skills contribute greatly to effective leadership and management strategies of scientific teams. While all successful teams share the characteristic of effectively carrying out these activities, there is no single formula for execution with every leader exemplifying different strengths and weaknesses. Successful scientific collaborations have strong leaders who are self-aware and are mindful of the many elements critical for supporting the science at the center of the effort.
Stochastic Dual Coordinate Ascent with Adaptive Probabilities

This paper introduces AdaSDCA: an adaptive variant of stochastic dual coordinate ascent (SDCA) for solving the regularized empirical risk minimization problems. Our modification consists in allowing the method to adaptively change the probability distribution over the dual variables throughout the iterative process. AdaSDCA achieves provably better complexity bound than SDCA with the best fixed probability distribution, known as importance sampling. However, it is of a theoretical character as it is expensive to implement. We also propose AdaSDCA+: a practical variant which in our experiments outperforms existing non-adaptive methods.
NUND: Non-Uniform Node Distribution in Cluster-based Wireless Sensor Networks

Cluster-based wireless sensor network (WSN) can significantly reduce the energy consumption by data aggregation and has been widely used in WSN applications. However, due to the intrinsic many-to-one traffic pattern in WSN, the network lifetime is generally deteriorated by the unbalanced energy consumption in a cluster-based WSN. Therefore, energy efficiency and network lifetime improvement are two crucial and challenging issues in cluster-based WSNs. In this paper, we propose a Non-Uniform Node Distribution (NUND) scheme to improve the energy efficiency and network lifetime in cluster-based WSNs. Specifically, we first propose an analytic model to analyze the energy consumption and the network lifetime of the cluster-based WSNs. Based on the analysis results, we propose a node distribution algorithm to maximize the network lifetime with a fixed number of sensor nodes in cluster-based WSNs. Extensive simulations demonstrate that the theoretical analysis results determined by the proposed analytic model are consistent with the simulation results, and the NUND can significantly improve the energy efficiency and network lifetime.
Empowering Technology Enabled Care Using IoT and Smart Devices: A Review

Designing power aware wearable devices is the main key in building compact size autonomous smart devices to successfully connect health Internet of things solutions. With their ability to perform tasks ranging from simple self-monitoring to complex interactive tasks, these devices hold great promises in providing a large scale cost effective solution to the challenges facing nowadays healthcare systems. Despite the advances in sensing and hardware design, there still remain several technical challenges facing the research community to build devices that meet the computational requirements with a self-powered capability. Overcoming these challenges require major improvements in all the building blocks of wearable devices including sensors, power management, signal processing, computing architectures, and communication. This paper surveys some of the past milestones related to these subsystems and discusses promising research directions addressing their limitations.
Coordinating Agents' Meta-Level Control

Embedded systems consisting of collaborating agents capable of interacting with their environment are becoming ubiquitous. It is crucial for these systems to be able to adapt to the dynamic and uncertain characteristics of an open environment. The question of when this adaptation process should be done and how much effort should be invested in the adaptation becomes especially challenging in the context of multi-agent systems. We present a generalized agent framework for meta-level control called GeMEC. We describe GEMEC’s decentralized Markov Decision Process (DEC-MDP)-based model for decision making in Netrads, a tornado tracking application. This model will capture interactions where meta-level decisions made in one agent’s MDP can affect meta-level MDPs of other agents. The cost of meta-level control can be controlled by constructing and evaluating the DEC-MDPs offline.
Insight into Hypoxia Tolerance in Cowpea Bruchid: Metabolic Repression and Heat Shock Protein Regulation via Hypoxia-Inducible Factor 1

Oxygen is of fundamental importance for most living organisms including insects. Hermetic storage uses airtight containment facilities to withhold oxygen required for development, thus preventing damage by insect pests in stored grain. Cowpea bruchid (Callosobruchus maculatus) ceases feeding and growth when exposed to 2% oxygen. However, although population expansion is temporarily arrested, the bruchids (especially late stage larvae) can survive extended periods of hypoxia and recover development if normoxic conditions resume, an ability rarely found in mammals. To begin to understand fundamental mechanisms that enable insects to cope with oxygen deprivation, we constructed a 3′-anchored cDNA library from 4th instar larvae subjected to normoxic and hypoxic treatments (respectively), and performed 454-pyrosequencing. Quality filtering and contig assembly resulted in 20,846 unique sequences. Of these, 5,335 sequences had hits in BlastX searches (E = 10−6), constituting a 2,979 unigene set. Further analysis based on gene ontology terms indicated that 1,036 genes were involved in a diverse range of cellular functions. Genes encoding putative glycolytic and TCA cycle enzymes as well as components of respiratory chain complexes were selected and assessed for transcript responses to low oxygen. The majority of these genes were down-regulated, suggesting that hypoxia repressed metabolic activity. However, a group of genes encoding heat shock proteins (HSPs) was induced. Promoter analyses of representative HSP genes suggested the involvement of hypoxia-inducible transcription factor 1 (HIF1) in regulating these hypoxia-induced genes. Its activator function has been confirmed by transient co-transfection into S2 cells of constructs of HIF1 subunits and the HSP promoter-driven reporter.
The Threat of War and Psychological Distress Among Civilians Working in Iraq and Afghanistan

Research documents the mental health toll of combat operations on military personnel in Iraq and Afghanistan, but little research examines civilians who work alongside members of the military. In this research, we argue that a sense of threat is an “ambient stressor” that permeates daily life among civilians who work in these war zones, with mastery likely to both mediate and moderate the mental health effects of this stressor. Using a unique probability sample of Department of Army civilians, we find that threat is positively related to distress, but mastery mediates this relationship nonlinearly, with the indirect relationship between threat and distress strengthening as threat increases. The moderating function of mastery is also nonlinear, with moderate levels of mastery providing maximum stress buffering. This research suggests that contextual conditions of constraint can create nonlinearities in the way that mastery mediates and moderates the effects of ambient stressors.
Tieline reconnection of microgrids using controllable variable reactors

In this paper, a tuned controller of variable reactors is developed to realize a reliable tieline reconnection of microgrids. It is very useful to solve the problem caused by synchronization issue during tieline reconnection, especially in absence of large-area communication network to cover all microgrids. The theoretical fundamental of this method is analyzed, based on which a set of tuning process of variable reactors' controller are derived. The feasibility and effectiveness of this tieline reconnection method with tuned controller is analyzed and verified by simulations. This method can greatly improve the transient stability of non-conventional grid, which consists of multiple microgrids and require an ability of frequent reliable reconnections, and limit system oscillation to less than 50%. The tieline reconnection controller can be easily integrated with power flow control into existing variable reactor devices at low cost. And the tuning process of the controller is simple and suitable for industrial applications.
Effect of Compaction on Soil Physical and Hydraulic Properties: Experimental Results and Modeling

Soil compaction affects soil physical properties and, eventually, crop production. A severe drop in the productivity of the state of Parana, southern Brazil, was observed due to soil compaction. Two oxisols from this region, a Haplic Acrothox from the site of Cascavel and a Haplic Eutrothox from the site of Palotina, presenting different compaction behaviors in the field, are studied under laboratory conditions. Uniaxial compressive pressures, from 50 to 1000 kPa, are applied to soil samples at different initial matric potentials, varying from -0.1 to -1000 kPa. The bulk density of the Palotina soil is always higher than that of the Cascavel soil and is the highest when the initial matric tension is -32 kPa. Differences in pH, cation-exchange capacity, organic matter, and clay particle thickness also tend to explain the different compaction behaviors. A model of the soil bulk density increase during compaction is proposed and compared with a multiplicative model and a logarithmic model. The performances of the proposed and the multiplicative models are practically similar and better than those of the logarithmic model. The major advantage of the proposed model is that it has one fitting parameter less than the multiplicative model. Compaction affects the soil water retention curves for the whole range of matric tensions, up to - 100 MPa. An approach that allows the evaluation of the hydraulic conductivity functions of the compacted samples is proposed. Applied to the Brooks and Corey relationship, the main drying curves of the compacted samples are well reproduced using one fitting parameter only.
I/O optimal isosurface extraction

The authors give I/O-optimal techniques for the extraction of isosurfaces from volumetric data, by a novel application of the I/O-optimal interval tree of Arge and Vitter (1996). The main idea is to preprocess the data set once and for all to build an efficient search structure in disk, and then each time one wants to extract an isosurface, they perform an output-sensitive query on the search structure to retrieve only those active cells that are intersected by the isosurface. During the query operation, only two blocks of main memory space are needed, and only those active cells are brought into the main memory, plus some negligible overhead of disk accesses. This implies that one can efficiently visualize very large data sets on workstations with just enough main memory to hold the isosurfaces themselves. The implementation is delicate but not complicated. They give the first implementation of the I/O-optimal interval tree, and also implement their methods as an I/O filter for Vtk's isosurface extraction for the case of unstructured grids. They show that, in practice, the algorithms improve the performance of isosurface extraction by speeding up the active-cell searching process so that it is no longer a bottleneck. Moreover, this search time is independent of the main memory available. The practical efficiency of the techniques reflects their theoretical optimality.
Seq no more: better strategies for parallel Haskell

We present a complete redesign of evaluation strategies, a key abstraction for specifying pure, deterministic parallelism in Haskell. Our new formulation preserves the compositionality and modularity benefits of the original, while providing significant new benefits. First, we introduce an evaluation-order monad to provide clearer, more generic, and more efficient specification of parallel evaluation. Secondly, the new formulation resolves a subtle space management issue with the original strategies, allowing parallelism (sparks) to be preserved while reclaiming heap associated with superfluous parallelism. Related to this, the new formulation provides far better support for speculative parallelism as the garbage collector now prunes unneeded speculation. Finally, the new formulation provides improved compositionality: we can directly express parallelism embedded within lazy data structures, producing more compositional strategies, and our basic strategies are parametric in the coordination combinator, facilitating a richer set of parallelism combinators. We give measurements over a range of benchmarks demonstrating that the runtime overheads of the new formulation relative to the original are low, and the new strategies even yield slightly better speedups on average than the original strategies