Miracle-dz/UniFAR-FTUs huggingface dataset:
Observing the Dynamics of Dipole-Mediated Energy Transport by Interaction-Enhanced Imaging

Imaging Excitations Complex processes such as chemical reactions and photosynthesis involve the transport of energy. The mechanisms of how the energy migrates, the influence of the surrounding environment, or the extent to which quantum mechanics affects the process remain unclear. Günter et al. (p. 954, published online 7 November; see the Perspective by Donley) found that a cloud of cold atoms suitably prepared and decorated with “impurity” Rydberg atoms could be used to image the transport of excitations between excited Rydberg atoms directly. This ability to tune the influence of the background environment may help in the study of the coherent transport of energy in complex many-body systems. An imaging technique based on a cloud of cold atoms provides a model system to study the coherent transport of energy. [Also see Perspective by Donley] Electronically highly excited (Rydberg) atoms experience quantum state–changing interactions similar to Förster processes found in complex molecules, offering a model system to study the nature of dipole-mediated energy transport under the influence of a controlled environment. We demonstrate a nondestructive imaging method to monitor the migration of electronic excitations with high time and spatial resolution, using electromagnetically induced transparency on a background gas acting as an amplifier. The continuous spatial projection of the electronic quantum state under observation determines the many-body dynamics of the energy transport.
A new differential evolution with improved mutation strategy

The paper employs Lagrange's mean value theorem of differential Calculus to design a new strategy for the selection of parameter vectors in the Differential Evolution (DE) algorithm. Classical differential evolution selects parameter vectors randomly to obtain the donor vectors. These donor vectors thus cannot be directly used as trial solution to the optimization problem. The recombination step indeed is very useful to generate potential trial solutions. The proposed algorithm eliminates the recombination step as the trial solutions can be directly generated by the extended mutation step only. Performance analysis of the proposed algorithm with respect to standard benchmark functions reveals that both in expected convergence time and accuracy in solutions, the proposed algorithm outperforms classical DE/rand/1. Besides extension in mutation strategy, an adaptive selection strategy in the scaling factor F also improves the performance of the proposed algorithm. In addition, the proposed algorithm outperforms classical DE in noisy optimization problem. Further, the number of function evaluation with scaled up dimensions of the optimization problem adds insignificantly small complexity in comparison to that in classical differential evolution to meet up a prescribed level of accuracy in solution quality.
Cell Surface ABP1-TMK Auxin-Sensing Complex Activates ROP GTPase Signaling

A Different Route The plant hormone auxin regulates a variety of developmental processes and responses to environmental inputs, often via changes in gene transcription. Xu et al. (p. 1025) analyzed a signaling pathway involving ABP1 (auxin-binding protein 1) that affects the cytoskeleton and endocytosis in Arabidopsis without changing gene transcription. Instead, ABP1 functions at the cell surface to bind auxin and a family of membrane kinases, thereby activating intracellular guanosine triphosphatases to initiate important developmental changes in cell shape. An alternate signaling route for the plant hormone auxin goes directly inside from the cell surface. Auxin-binding protein 1 (ABP1) was discovered nearly 40 years ago and was shown to be essential for plant development and morphogenesis, but its mode of action remains unclear. Here, we report that the plasma membrane–localized transmembrane kinase (TMK) receptor–like kinases interact with ABP1 and transduce auxin signal to activate plasma membrane–associated ROPs [Rho-like guanosine triphosphatases (GTPase) from plants], leading to changes in the cytoskeleton and the shape of leaf pavement cells in Arabidopsis. The interaction between ABP1 and TMK at the cell surface is induced by auxin and requires ABP1 sensing of auxin. These findings show that TMK proteins and ABP1 form a cell surface auxin perception complex that activates ROP signaling pathways, regulating nontranscriptional cytoplasmic responses and associated fundamental processes.
Bereavement after sibling death: a population‐based longitudinal case‐control study

The objective of this study was to examine mental disorders and treatment use among bereaved siblings in the general population. Siblings (N=7243) of all deceased children in the population of Manitoba, Canada who died between 1984 and 2009 were matched 1:3 to control siblings (N=21,729) who did not have a sibling die in the study period. Generalized estimating equations were used to compare the two sibling groups in the two years before and after the index child's death on physician‐diagnosed mental disorders and treatment utilization, with adjustment for confounding factors including pre‐existing mental illness. Analyses were stratified by age of the bereaved (<13 vs. 13+). Results revealed that, in the two years after the death of the child, bereaved siblings had significantly higher rates of mental disorders than control siblings, even after adjusting for pre‐existing mental illness. When comparing the effect of a child's death on younger versus older siblings, the rise in depression rates from pre‐death to post‐death was significantly higher for siblings aged under 13 (p<0.0001), increasing more than 7‐fold (adjusted relative rate, ARR=7.25, 95% CI: 3.65‐14.43). Bereaved siblings aged 13+ had substantial morbidity in the two years after the death: 25% were diagnosed with a mental disorder (vs. 17% of controls), and they had higher rates of almost all mental disorder outcomes compared to controls, including twice the rate of suicide attempts (ARR=2.01, 95% CI: 1.29‐3.12). Siblings in the bereaved cohort had higher rates of alcohol and drug use disorders already before the death of their sibling. In conclusion, the death of a child is associated with considerable mental disorder burden among surviving siblings. Pre‐existing health problems and social disadvantage do not fully account for the increase in mental disorder rates.
Biologically inspired obsolescence management in mobile agent systems: A dynamic, service oriented approach

Ubiquitous computing heralds an era marked by the increasing pervasiveness of computational hardware throughout a given environment. In order to capitalize on the increased abundance of the underlying infrastructure multi-agent systems will be required to reflect the characteristics of the ubiquitous networks upon which they operate. Due to the potential for limited communication capacity experienced by agents in the wild it will become increasingly important for mobile agents to migrate to devices in greater proximity to the problem upon which they are working or the resources they require. A result of highly mobile agents operating in potentially constrained computational and communication environments is that widely used command and coordination structures are no longer able to scale efficiently. Engineers are currently struggling with aspects of managing the physical devices which comprise such networks, particularly the obsolescence management of their constituent, highly dispersed, hardware. Analogously, the obsolescence management of deployed agents is of increasing concern. The paper examines and synthesizes several biological metaphors which may be employed in order to mitigate the inherent complexity of managing deployed mobile agent systems and presents this functionality in a service oriented manner.
Realizing a Proactive, Self-Optimizing System Behavior within Adaptive, Heterogeneous Many-Core Architectures

For maintaining high performance and minimizing power consumption, adaptive, heterogeneous many-core architectures can be adapted at runtime to changing environmental requests or conditions as well as to changes resulting from the dynamics of the workload itself. However, the huge complexity of such architectures makes their optimization very challenging at runtime. This challenge is therefore addressed within this paper by an Organic Computing approach for realizing a proactive, self-optimizing system behavior within adaptive, heterogeneous systems using a light-weight Learning Classifier System and a Run Length Encoding Markov predictor. The first realizes a self-optimizing behavior, freeing the user from the burden of optimizing the system manually, and the latter captures the system behavior, permits prediction of future system states, and therefore permits exploiting regular behavior for further improving the overall system performance. Using the use case of optimizing the overall system performance, results showed that the proactive, self-optimizing system achieved a performance improvement of 11.3% in comparison to a non-optimizing system.
Impaired social behaviour and molecular mediators of associated neural circuits during chronic Toxoplasma gondii infection in female mice

Toxoplasma gondii (T. gondii) is a neurotropic parasite that is associated with various neuropsychiatric disorders. Rodents infected with T. gondii display a plethora of behavioural alterations, and Toxoplasma infection in humans has been strongly associated with disorders such as schizophrenia, in which impaired social behaviour is an important feature. Elucidating changes at the cellular level relevant to neuropsychiatric conditions can lead to effective therapies. Here, we compare changes in behaviour during an acute and chronic T. gondii infection in female mice. Further, we notice that during chronic phase of infection, mice display impaired sociability when exposed to a novel conspecific. Also, we show that T. gondii infected mice display impaired short-term social recognition memory. However, object recognition memory remains intact. Using c-Fos as a marker of neuronal activity, we show that infection leads to an impairment in neuronal activation in the medial prefrontal cortex, hippocampus as well as the amygdala when mice are exposed to a social environment and a change in functional connectivity between these regions. We found changes in synaptic proteins that play a role in the process of neuronal activation such as synaptophysin, PSD-95 and changes in downstream substrates of cell activity such as cyclic AMP, phospho-CREB and BDNF. Our results point towards an imbalance in neuronal activity that can lead to a wider range of neuropsychiatric problems upon T. gondii infection.
An ACO inspired weighting approach for the spectral partitioning of co-authorship networks

Spectral partitioning is a well known method in the area of graph and matrix analysis. Several approaches based on spectral partitioning and spectral clustering were used to detect structures in real world networks and databases. In this paper, we use the spectral partitioning to detect communities in a co-authorship network. The partitioning depends heavily on the weighting of the underlying network. We use an intuitive weighting scheme based on the ant colony optimization and show the communities found by spectral partitioning when using the ACO inspired weighting and when using trivial weighting based on the number of interactions between the authors.
An adaptive constraint handling approach embedded MOEA/D

This paper proposes an efficient, adaptive constraint handling approach that can be used within the class of evolutionary multi-objective optimization (EMO) algorithms. The proposed constraint handling approach is presented within the framework of one of the most successful algorithms i.e. multi-objective evolutionary algorithm based on decomposition (MOEA/D) [1]. The constraint handling mechanism adaptively decides on the violation threshold for comparison. The violation threshold is based on the type of constraints, size of the feasible space and the search outcome. Such a process intrinsically treats constraint violation and objective function values separately and adds a selection pressure, wherein infeasible solutions with violations less than the identified threshold are considered at par with feasible solutions. As illustrated, the constraint handling scheme extends the current capability of MOEA/D to deal with constraints. The performance of the algorithm is illustrated using 10 commonly studied benchmark problems and a real-world constraint optimization problem, and compared with the results obtained using yet another commonly used form i.e. Nondominated Sorting Genetic Algorithm (NSGA-II).
Polyphonic accompaniment using genetic algorithm with music theory

Computational creativity using artificial intelligence and computational intelligence has received increasing attention. Automatic music composition is a blooming field in computational creativity; especially, automatic accompaniment has gained some promising results. However, most of the automatic accompaniment systems based on evolutionary computation require human feedback as evaluation criterion, which is vulnerable to the fatigue and decreased sensitivity after long-time listening. This study adopts music theory as the basis of evaluation criterion for accompaniment to address this issue. Specifically, we develop a genetic algorithm (GA) to generate polyphonic accompaniment, in which the fitness function consists of several evaluation rules based on music theory. Three accompaniments, i.e., main, bass, and chord accompaniments are considered in the study. Experimental results show that, given a dominant melody, the proposed method can effectively generate multiple scores to form polyphonic accompaniment.
Institutionalised Consensus in Vehicular Networks: Executable Specification and Empirical Validation

We propose to manage consensus formation in open, decentralised and resource-constrained systems like vehicular networks using self-organising electronic institutions. This requires the institution members (agents) to maintain institutional facts in the face of inadvertent failure, non-compliant behaviour, and environmental change. To do this, we extend and adapt the well-known Paxos algorithm, for fault-tolerant consensus in distributed databases, to the IPCon algorithm, for robust collective-choice in electronic institutions. We address issues of developing an executable specification of IPCon and provide an empirical validation of its correctness that complements a previously-presented formal proof of the theoretical properties.
Effector Specialization in a Lineage of the Irish Potato Famine Pathogen

The Makings of a Choosy Pathogen The oomycete Phytophthora infestans is responsible for potato blight. A closely related pathogen afflicts the 4 o'clock flower. To assess why such similar pathogens are restricted to one host or the other, Dong et al. (p. 552; see the Perspective by Coaker) analyzed similar effectors from both pathogens. The results suggest that the host specialization that led to evolutionary divergence depends on reciprocal single–amino acid changes that tailor the pathogen effector to a specific host protease that is being disabled. Thus, small changes can open the door for a pathogen to jump to another species of host and, itself, diversify into another species of pathogen. A potato pathogen has changed one of its protease inhibitors that targets its new host plant protease. [Also see Perspective by Coaker] Accelerated gene evolution is a hallmark of pathogen adaptation following a host jump. Here, we describe the biochemical basis of adaptation and specialization of a plant pathogen effector after its colonization of a new host. Orthologous protease inhibitor effectors from the Irish potato famine pathogen, Phytophthora infestans, and its sister species, Phytophthora mirabilis, which is responsible for infection of Mirabilis jalapa, are adapted to protease targets unique to their respective host plants. Amino acid polymorphisms in both the inhibitors and their target proteases underpin this biochemical specialization. Our results link effector specialization to diversification and speciation of this plant pathogen.
Wiedemann-Steiner Syndrome With 2 Novel KMT2A Mutations

Wiedemann-Steiner syndrome is a rare genetic disorder characterized by short stature, hairy elbows, facial dysmorphism, and developmental delay. It can also be accompanied by musculoskeletal anomalies such as muscular hypotonia and small hands and feet. Mutations in the KMT2A gene have only recently been identified as the cause of Wiedemann-Steiner syndrome; therefore, only 16 patients from 15 families have been described, and new phenotypic features continue to be added. In this report, we describe 2 newly identified patients with Wiedemann-Steiner syndrome who presented with variable severity. One girl exhibited developmental dysplasia of the hip and fibromatosis colli accompanied by other clinical features, including facial dysmorphism, hypertrichosis, patent ductus arteriosus, growth retardation, and borderline intellectual disability. The other patient, a boy, showed severe developmental retardation with automatic self-mutilation, facial dysmorphism, and hypertrichosis at a later age. Exome sequencing analysis of these patients and their parents revealed a de novo nonsense mutation, p.Gln1978*, of KMT2A in the former, and a missense mutation, p.Gly1168Asp, in the latter, which molecularly confirmed the diagnosis of Wiedemann-Steiner syndrome.
Many Paths to the Origin of Life

A plethora of prebiotic chemistries are fueling research on the pathway to the first self-replicating system. The origin of life remains a daunting mystery in part because rather than knowing too little, we increasingly know about too many possible mechanisms that might have led to the self-sustaining replication of nucleic acids and the cellularization of genetic material that is the basis of life on Earth.
Iron Fertilization of the Subantarctic Ocean During the Last Ice Age

Productive Dustiness The idea that biological productivity in the surface ocean is limited by a lack of available iron has been widely accepted, but it has been difficult to show that this effect might have operated in the geological past. Martínez-García et al. (p. 1347) investigated the isotopic composition of foraminifera-bound nitrogen in samples from an Ocean Drilling Project sediment core and found millennial-scale changes in nitrate consumption correlated with fluxes in the iron burial and productivity proxies over the past 160,000 years. Hence, in the Southern Ocean the biological pump was strengthened when dust fluxes were high, which explains a significant part of the difference in atmospheric CO2 concentrations observed to occur across glacial cycles. Nitrogen isotopes in foraminifera show the role of iron fertilization on atmospheric carbon dioxide during the last ice age. John H. Martin, who discovered widespread iron limitation of ocean productivity, proposed that dust-borne iron fertilization of Southern Ocean phytoplankton caused the ice age reduction in atmospheric carbon dioxide (CO2). In a sediment core from the Subantarctic Atlantic, we measured foraminifera-bound nitrogen isotopes to reconstruct ice age nitrate consumption, burial fluxes of iron, and proxies for productivity. Peak glacial times and millennial cold events are characterized by increases in dust flux, productivity, and the degree of nitrate consumption; this combination is uniquely consistent with Subantarctic iron fertilization. The associated strengthening of the Southern Ocean’s biological pump can explain the lowering of CO2 at the transition from mid-climate states to full ice age conditions as well as the millennial-scale CO2 oscillations.
U6 RNA biogenesis and disease association

U6 snRNA is one of five uridine‐rich noncoding RNAs that form the major spliceosome complex. Unlike other U‐snRNAs, it reveals many distinctive aspects of biogenesis such as transcription by RNA polymerase III, transcript nuclear retention and particular features of transcript ends: monomethylated 5′‐guanosine triphosphate as cap structure and a 2′,3′‐cyclic phosphate moiety (>P) at the 3′ termini. U6‐snRNA plays a central role in splicing and thus its transcription, maturation, snRNP formation, and recycling are essential for cellular homeostasis. U6 snRNA enters the splicing cycle as part of the tri‐U4/U6.U5snRNP complex, and after significant structural arrangements forms the catalytic site of the spliceosome together with U2 snRNA and Prp8. U6 snRNA also contributes to the splicing reaction by coordinating metal cations required for catalysis. Many human diseases are associated with altered splicing processes. Disruptions of the basal splicing machinery can be lethal or lead to severe diseases such as spinal muscular atrophy, amyotrophic lateral sclerosis, or retinitis pigmentosa. Recent studies have identified a new U6 snRNA biogenesis factor Usb1, the absence of which leads to poikiloderma with neutropenia (PN) (OMIM 604173), an autosomal recessive skin disease. Usb1 is an evolutionarily conserved 3′→5′ exoribonuclease that is responsible for removing 3′‐terminal uridines from U6 snRNA transcripts, which leads to the formation of a 2′,3′ cyclic phosphate moiety (>P). This maturation step is fundamental for U6 snRNP assembly and recycling. Usb1 represents the first example of a direct association between a spliceosomal U6 snRNA biogenesis factor and human genetic disease.WIREs RNA 2013, 4:581–592. doi: 10.1002/wrna.1181
Vertebrate Limb Bud Formation Is Initiated by Localized Epithelial-to-Mesenchymal Transition

Where Do You Want Your Leg? Initiation of limb formation is the key to understanding limb-cell specification and patterning during development. Gros and Tabin (p. 1253) show that a localized epithelial-to-mesenchymal transition triggers the formation of the limb. Finding that limbs initiate through cell-state change, and not through differential proliferation, redefines questions such as how limb buds are placed on the body plan. Cell state change, rather than differential proliferation, initiates limb formation during development. Vertebrate limbs first emerge as small buds at specific locations along the trunk. Although a fair amount is known about the molecular regulation of limb initiation and outgrowth, the cellular events underlying these processes have remained less clear. We show that the mesenchymal limb progenitors arise through localized epithelial-to-mesenchymal transition (EMT) of the coelomic epithelium specifically within the presumptive limb fields. This EMT is regulated at least in part by Tbx5 and Fgf10, two genes known to control limb initiation. This work shows that limb buds initiate earlier than previously thought, as a result of localized EMT rather than differential proliferation rates.
Fast Iterative Graph Computation: A Path Centric Approach

Large scale graph processing represents an interesting challenge due to the lack of locality. This paper presents Path Graph for improving iterative graph computation on graphs with billions of edges. Our system design has three unique features: First, we model a large graph using a collection of tree-based partitions and use an path-centric computation rather than vertex-centric or edge-centric computation. Our parallel computation model significantly improves the memory and disk locality for performing iterative computation algorithms. Second, we design a compact storage that further maximize sequential access and minimize random access on storage media. Third, we implement the path-centric computation model by using a scatter/gather programming model, which parallels the iterative computation at partition tree level and performs sequential updates for vertices in each partition tree. The experimental results show that the path-centric approach outperforms vertex centric and edge-centric systems on a number of graph algorithms for both in-memory and out-of-core graphs.