Well-defined Trajectories Research Articles

Study of the magnetic and structural properties of the simple perovskite YFeO3

In the present work, an experimental and theoretical study of the synthesis, magnetic, and structural properties of simple perovskite compounds YFeO3 has been investigated based on their potential applications, such as: solid oxide fuel cells, electrochemical sensors, sensor materials, magneto-optical materials, etc. Experimentally, the synthesis was carried out by the sol-gel method. X-rays and Rietveld refinements confirmed the orthorhombic structure. Scanning electron microscopy observations confirmed agglomerates of simple perovskite particles YFeO3. The study of the magnetic phase of the simple perovskite YFeO3 showed that it behaves like a weak ferromagnetic, this property delimits and directs magnetic fields into well-defined trajectories. On the other hand, the structural results, from a theoretical point of view, are in good agreement with the experimental ones. Through energy comparison, a possible competition was identified between the FM and AFM states, where the electronic properties are associated with the directional nature of the hybridization between the p orbitals of oxygen and the t2g states, where the superexchange mechanism prevails with e oxygen as mediator.

Trifurcated Splitting of Water Droplets on Engineered Lithium Niobate Surfaces.

Controlled splitting of liquid droplets is a key function in many microfluidic applications. In recent years, various methodologies have been used to accomplish this task. Here, we present an optofluidic technique based on an engineered surface formed by coating a z-cut iron-doped lithium niobate crystal with a lubricant-infused layer, which provides a very slippery surface. Illuminating the crystal with a light spot induces surface charges of opposite signs on the two crystal faces because of the photovoltaic effect. If the light spot is sufficiently intense, millimetric water droplets placed near the illuminated spot split into two charged fragments, one fragment being trapped by the bright spot and the other moving away from it. The latter fragment does not move randomly but rather follows one of three well-defined trajectories separated by 120°, which reflect the anisotropic crystalline structure of Fe:LiNbO3. Numerical simulations explain the behavior of water droplets in the framework of the forces induced by the interplay of pyroelectric, piezoelectric, and photovoltaic effects, which originate simultaneously inside the illuminated crystal. Such a synergetic effect can provide a valuable feature in applications that require splitting and coalescence of droplets, such as chemical microreactors and biological encapsulation and screening.

Center of Mass Estimation for Impaired Gait Assessment Using Inertial Measurement Units.

Injury or disease often compromise walking dynamics and negatively impact quality of life and independence. Assessing methods to restore or improve pathological gait can be expedited by examining a global parameter that reflects overall musculoskeletal control. Center of mass (CoM) kinematics follow well-defined trajectories during unimpaired gait, and change predictably with various gait pathologies. We propose a method to estimate CoM trajectories from inertial measurement units (IMUs) using a bidirectional Long Short-Term Memory neural network to evaluate rehabilitation interventions and outcomes. Five non-disabled volunteers participated in a single session of various dynamic walking trials with IMUs mounted on various body segments. A neural network trained with data from four of the five volunteers through a leave-one-subject out cross validation estimated the CoM with average root mean square errors (RMSEs) of 1.44cm, 1.15cm, and 0.40cm in the mediolateral (ML), anteroposterior (AP), and inferior/superior (IS) directions respectively. The impact of number and location of IMUs on network prediction accuracy was determined via principal component analysis. Comparing across all configurations, three to five IMUs located on the legs and medial trunk were the most promising reduced sensor sets for achieving CoM estimates suitable for outcome assessment. Lastly, the networks were tested on data from an individual with hemiparesis with the greatest error increase in the ML direction, which could stem from asymmetric gait. These results provide a framework for assessing gait deviations after disease or injury and evaluating rehabilitation interventions intended to normalize gait pathologies.

International Quality Award Models: Innovation Enablers or Inhibitors?

Historical development of models and criteria supporting major international quality awards is driven more by continuous or incremental improvement than by breakthrough improvement. This has been the case in particular relative the most enduring such awards - the European Foundation for Quality Management (EFQM) Business Excellence Award, America’s Baldrige National Quality Award for Performance Excellence (MBNQA), and the Shingo Prize for Operational Excellence. In possible contrast are initiatives such as the United Nations Sustainable Development Goals (UN SDGs) and the imputed urgency for improvement, innovation and change associated with these, due in large to the sheer scope and magnitude of change needed – especially with respect to societal or environmental challenges. While sufficiently rapid iteration across a large enough number of cycles has the potential of rivaling the magnitude of innovation attained through a focus on breakthrough improvement, such an approach is unlikely to precisely match the destination of innovation attained through breakthrough improvement approaches. One significant reason is that incremental improvements often target minor course corrections with well-defined trajectories, whereas breakthrough efforts target larger strides with more mystery between the point of origination and the targeted destination. Differences in these approaches impact products and services reaching the market in many ways, hence impacting their marketplace performance. Among differences of note are ones in the natures of the product or service brought to market, the timing of their market arrival, the levels of creativity and innovation required, design innovations introduced, consumer receptivity and perception of iteration vs. innovation, perceived impact, consumer perception of the company, and – not to be ignored – risk and reward elements. Questions explored herein are whether the models and criteria used by international quality award frameworks enable innovation and entre-intrapreneurship, inhibit these, or are innovation and entre-intrapreneurial neutral. Similarly, the impact of the UN SDGs in relation to innovation are discussed.

Evolutionary quantization and matter-antimatter distribution in accelerated expanding of Universe

In this paper we consider ultimate generalization of classical/quantum mechanics that directly follows from the causality principle and topology of a system’s state space. Interestingly that in generalized mechanics, the Hamiltonian/Schrodinger equations remain the same, but the Hamiltonian may depend on the action and its canonically conjugated variables as additional dynamical variables. This extension of quantum mechanics indicates that the quantization of matter could be an evolutionary process, and in the distant future, even massive bodies may become entirely quantum objects without well-defined trajectories and shapes. In the classical limit, the first approximation of the Hamiltonian with respect to the action explains the accelerated expansion of the Universe, Hubble’s law, formation of spiral galaxies with a non-Kepler curve of rotation velocity, and observed asymmetry between distributions of matter and antimatter. This theory predicts that our open universe could have extended pre-history and be preceded by a long set of closed precursor universes.

Enhanced DC-Link Voltage Dynamics for Grid-Connected Converters

Three-phase pulsewidth modulated converters are usually controlled to achieve sinusoidal currents in the grid side and tight voltage regulation in the dc-link capacitor. The implementation of linear controllers based on small-signal models is a well-established solution for these converters. However, the dynamic performance can be improved only to a limited extent and it deteriorates under different operating conditions which may result in the uncontrollability of the dc-bus voltage during transients. In this work, a state-plane model and control strategy are introduced to improve the dc-link dynamics for three-phase converters. The proposed method provides fast, reliable, and consistent transient responses under the entire operating range, including rectifier and inverter modes. First, a normalized model that describes the natural dynamic behavior of the converter is derived and represented in the state-plane. In this way, the dynamic evolution of the operating point is described in a graphical domain as circular trajectories with well-defined characteristics. The insight provided by these natural trajectories is used to develop a control strategy to improve the dc-link dynamics by selecting a unique combination of circular paths to solve the transients. As a result, the operating point follows well-defined trajectories to achieve fast and consistent dc-link voltage responses under a wide operating range. The effectiveness and feasibility of the proposed control strategy are validated by several simulation and experimental results.

High-Resolution Micro-object Separation by Rotating Magnetic Chromatography.

The development of new technologies for the separation, selection, and isolation of microparticles such as rare target cells, circulating tumor cells, cancer stem cells, and immune cells has become increasingly important in the last few years. Microparticle separation technologies are usually applied to the analysis of disease-associated cells, but these procedures often face a cell separation problem that is often insufficient for single specific cell analyses. To overcome these limitations, a highly accurate size-based microparticle separation technique, herein called "rotating magnetic chromatography", is proposed in this work. Magnetic nanoparticles, placed in a microfluidic separation channel, are forced to move in well-defined trajectories by an external magnetic field, colliding with microparticles that are in this way separated on the basis of their dimensions with high accuracy and reproducibility. The method was optimized by using fluorescein isothiocyanate-modified polystyrene particles (chosen as a reference standard) and then applied to the analysis of cancer cells like Hep-3B and SK-Hep-1, allowing their fast and high-resolution chromatographic separation as a function of their dimensions. Due to its unmatched sub-micrometer cell separation capabilities, RMC can be considered a break-through technique that can unlock new perspectives in different scientific fields, that is, in medical oncology.

Self-organization of kinetochore-fibers in human mitotic spindles.

During eukaryotic cell division, chromosomes are linked to microtubules (MTs) in the spindle by a macromolecular complex called the kinetochore. The bound kinetochore microtubules (KMTs) are crucial to ensuring accurate chromosome segregation. Recent reconstructions by electron tomography (Kiewisz et al., 2022) captured the positions and configurations of every MT in human mitotic spindles, revealing that roughly half the KMTs in these spindles do not reach the pole. Here, we investigate the processes that give rise to this distribution of KMTs using a combination of analysis of large-scale electron tomography, photoconversion experiments, quantitative polarized light microscopy, and biophysical modeling. Our results indicate that in metaphase, KMTs grow away from the kinetochores along well-defined trajectories, with the speed of the KMT minus ends continually decreasing as the minus ends approach the pole, implying that longer KMTs grow more slowly than shorter KMTs. The locations of KMT minus ends, and the turnover and movements of tubulin in KMTs, are consistent with models in which KMTs predominately nucleate de novo at kinetochores in metaphase and are inconsistent with substantial numbers of non-KMTs being recruited to the kinetochore in metaphase. Taken together, this work leads to a mathematical model of the self-organization of kinetochore-fibers in human mitotic spindles.

Multimodal Dimension Reduction and Subtype Classification of Head and Neck Squamous Cell Tumors.

Traditional analysis of genomic data from bulk sequencing experiments seek to group and compare sample cohorts into biologically meaningful groups. To accomplish this task, large scale databases of patient-derived samples, like that of TCGA, have been established, giving the ability to interrogate multiple data modalities per tumor. We have developed a computational strategy employing multimodal integration paired with spectral clustering and modern dimension reduction techniques such as PHATE to provide a more robust method for cancer sub-type classification. Using this integrated approach, we have examined 514 Head and Neck Squamous Carcinoma (HNSC) tumor samples from TCGA across gene-expression, DNA-methylation, and microbiome data modalities. We show that these approaches, primarily developed for single-cell sequencing can be efficiently applied to bulk tumor sequencing data. Our multimodal analysis captures the dynamic heterogeneity, identifies new and refines subtypes of HNSC, and orders tumor samples along well-defined cellular trajectories. Collectively, these results showcase the inherent molecular complexity of tumors and offer insights into carcinogenesis and importance of targeted therapy. Computational techniques as highlighted in our study provide an organic and powerful approach to identify granular patterns in large and noisy datasets that may otherwise be overlooked.

Neural alterations of emotion processing in atypical trajectories of psychotic-like experiences

The aim of this study was to investigate the neural bases of facial emotion processing before the onset of clinical psychotic symptoms in youth belonging to well-defined developmental trajectories of psychotic-like experiences (PLEs). A unique sample of 86 youths was recruited from a population-based sample of over 3800 adolescents who had been followed from 13 to 17 years of age. Three groups were identified based on validated developmental trajectories: a control trajectory with low and decreasing PLEs, and two atypical trajectories with moderate to elevated baseline PLEs that subsequently decreased or increased. All had functional magnetic resonance imaging data collected during a facial emotion processing task. Functional activation and connectivity data were analyzed for different contrasts. The increasing PLE trajectory displayed more positive psychotic symptoms while the decreasing trajectory exhibited more negative symptoms relative to the control group. During face processing, both atypical trajectories displayed decreased activations of the right inferior frontal gyrus (IFG), while the increasing trajectory displayed a negative signal in the precentral gyrus. The increasing PLE trajectory also displayed impaired connectivity between the amygdala, ventromedial prefrontal cortex, and cerebellum, and between the IFG, precuneus, and temporal regions, while the decreasing trajectory exhibited reduced connectivity between the amygdala and visual regions during emotion processing. Both atypical PLE trajectories displayed alterations in brain regions involved in attention salience. While the increasing trajectory with more positive symptoms exhibited dysconnectivity in areas that influence emotion salience and face perception, the decreasing trajectory with more negative symptoms had impairments in visual information integration areas. These group-specific features might account for the differential symptom expression.

Joint quantum–classical Hamilton variational principle in the phase space

We show that the dynamics of a closed quantum system obeys the Hamilton variational principle. Even though quantum particles lack well-defined trajectories, their evolution in the Husimi representation can be treated as a flow of multidimensional probability fluid in the phase space. By introducing the classical counterpart of the Husimi representation in a close analogy to the Koopman–von Neumann theory, one can largely unify the formulations of classical and quantum dynamics. We prove that the motions of elementary parcels of both classical and quantum Husimi fluid obey the Hamilton variational principle, and the differences between associated action functionals stem from the differences between classical and quantum pure states. The Husimi action functionals are not unique and defined up to the Skodje flux gauge fixing (Skodje et al 1989 Phys. Rev. A 40 2894). We demonstrate that the gauge choice can dramatically alter flux trajectories. Applications of the presented theory for constructing semiclassical approximations and hybrid classical–quantum theories are discussed.

A Spherical Atom Model of Helium Based on Well-Defined Electron Trajectories

A Spherical Atom Model of Helium Based on Well-Defined Electron Trajectories

A Humidity-Powered Soft Robot with Fast Rolling Locomotion.

A range of soft robotic systems have recently been developed that use soft, flexible materials and respond to environmental stimulus. The greatest challenge in their design is the integration of the actuator, energy sources, and body of robots while achieving fast locomotion and well-defined programmable trajectories. This work presents such a design that operates under constant conditions without the need for an externally modulated stimulus. By using a humidity-sensitive agarose film and overcoming the isotropic and random bending of the film, the robot, which we call the Hydrollbot, harnesses energy from evaporation for spontaneous and continuous fast self-rolling locomotion with a programmable trajectory in a constant-humidity environment. Moreover, the geometric parameters of the film were fine-tuned to maximize the rolling speed, and the optimised hydrollbot is capable of carrying a payload up to 100% of its own weight. The ability to self-propel fast under constant conditions with programmable trajectories will confer practical advantages to this robot in the applications for sensors, medical robots, actuation, etc.

Patterns of healthcare utilisation in children and young people: a retrospective cohort study using routinely collected healthcare data in Northwest London

ObjectivesWith a growing role for health services in managing population health, there is a need for early identification of populations with high need. Segmentation approaches partition the population based on...

Digitalisation and temporary agencies: Impact on the business model and internal organisation

ABSTRACT This study investigated the potential impact of upcoming technologies on the business model of temporary agencies, as well as the required organisational changes to effectively digitalise. Although this research does not focus on temporary agencies in hospitality specifically, the outcomes underline previous research undertaken by others on the future of hospitality jobs, in which for example artificial intelligence-driven technology is identified as a disruptor in the labour market. For this research, semi-structured interviews were conducted with industry experts and digitalisation experts. The main findings of this study are that technologies like artificial intelligence (AI), the Internet of Things and blockchain will have a large impact on temporary agencies – mostly on back-office processes, which will be made more efficient and less labour intensive. To effectively digitalise, cultural elements are of importance, such as a strong customer centricity and well-defined change management trajectories. Additionally, C-level executives (e.g. CEO, CFO, COO, etc.) diversity, digital savvy and willingness to invest are key elements. The positive effects of digitalisation should be clearly communicated: it will make work more fun, easier, and it will free up time to spend on human contact and teamwork. The key to success is adopting the opportunities that digitalisation brings, but making a difference by building true human connections.

Long-GRIN-Lens Microendoscopy Enabled by Wavefront Shaping for a Biomedical Microdevice: An Analytical Investigation.

We analytically investigate the feasibility of long graded-index (GRIN)-lens-based microendoscopes through wavefront shaping. Following the very well-defined ray trajectories in a GRIN lens, mode-dependent phase delay is first determined. Then, the phase compensation needed for obtaining diffraction limited resolution is derived. Finally, the diffraction pattern of the lens output is computed using the Rayleigh–Sommerfeld diffraction theory. We show that diffraction-limited resolution is obtained for a 0.5 mm diameter lens with a length over 1 m. It is also demonstrated that different imaging working distances (WDs) can be realized by modifying the phase compensation. When a short design WD is used, a large imaging numerical aperture (NA) higher than 0.4 is achievable even when a low NA lens (NA = 0.1) is used. The long- and thin-GRIN-lens-based microendoscope investigated here, which is attractive for biomedical applications, is being prioritized for use in a clinical stage microdevice that measures three-dimensional drug responses inside the body. The advance described in this work may enable superior imaging capabilities in clinical applications in which long and flexible imaging probes are favored.

Single-molecule mechanics of synthetic aromatic amide helices: Ultrafast and robust non-dissipative winding

Summary Because of proteins’ many degrees of conformational freedom, programming protein folding dynamics, overall elasticity, and motor functions remains an elusive objective. Instead, smaller and simpler objects, such as synthetic foldamers, may be amenable to design. However, little is known about their mechanical performance. Here, we show that reducing molecular size may not compromise mechanical properties. We report that helical aromatic oligoamides as small as 1 nm possess outstanding elasticity and outperform most natural helices. Using single-molecule force spectroscopy, we characterize their folding trajectories and intermediate states. We show that they cooperatively and reversibly unwind at high forces. They extend up to 3.8 times their original length and rewind against considerable forces on a timescale of 10 μs. Pulling and relaxing cycles follow the same trace up to a very high loading rate, indicating that the mechanical energy accumulated during the stretching does not dissipate and is immediately reusable.

Experimental quantum communication enhancement by superposing trajectories

In quantum communication networks, wires represent well-defined trajectories along which quantum systems are transmitted. In spite of this, trajectories can be used as a quantum control to govern the order of different noisy communication channels, and such a control has been shown to enable the transmission of information even when quantum communication protocols through well-defined trajectories fail. This result has motivated further investigations on the role of the superposition of trajectories in enhancing communication, which revealed that the use of quantum control of parallel communication channels, or of channels in series with quantum-controlled operations, can also lead to communication advantages. Building upon these findings, here we experimentally and numerically compare different ways in which two trajectories through a pair of noisy channels can be superposed. We observe that, within the framework of quantum interferometry, the use of channels in series with quantum-controlled operations generally yields the largest advantages. Our results contribute to clarify the nature of these advantages in experimental quantum-optical scenarios, and showcase the benefit of an extension of the quantum communication paradigm in which both the information exchanged and the trajectory of the information carriers are quantum.

Gene Therapy of Dominant CRX-Leber Congenital Amaurosis using Patient Stem Cell-Derived Retinal Organoids.

SummaryMutations in the photoreceptor transcription factor gene cone-rod homeobox (CRX) lead to distinct retinopathy phenotypes, including early-onset vision impairment in dominant Leber congenital amaurosis (LCA). Using induced pluripotent stem cells (iPSCs) from a patient with CRX-I138fs48 mutation, we established an in vitro model of CRX-LCA in retinal organoids that showed defective photoreceptor maturation by histology and gene profiling, with diminished expression of visual opsins. Adeno-associated virus (AAV)-mediated CRX gene augmentation therapy partially restored photoreceptor phenotype and expression of phototransduction-related genes as determined by single-cell RNA-sequencing. Retinal organoids derived from iPSCs of a second dominant CRX-LCA patient carrying K88N mutation revealed the loss of opsin expression as a common phenotype, which was alleviated by AAV-mediated augmentation of CRX. Our studies provide a proof-of-concept for developing gene therapy of dominant CRX-LCA and other CRX retinopathies.

Human-in-the-Loop Robotic Process Automation (RPA) with Deep Reinforcement Learning (DRL)

In this article, the authors attempt to extend human feedback as a critical decision-making tool to improve DRL for RPA systems, especially in application domains sensitive to change, such as healthcare and legal practice. The previous methods of implementing RPA moved in well-defined trajectories, meaning they have low adaptability for complex decision-making or other atypical cases. These systems can integrate DRL and hence can learn and evolve over the period required. Nevertheless, DRL models often work independently from human beings. They are used in applications with low human interaction, which can cause issues in decision-making procedures that require a higher understanding of regulation. The article puts human-in-the-loop, with human experts returning to the DRL models. It encapsulates human feedback into meaningful rewards or penalties for the DRL algorithms, ensuring correction and improvement of decision-making brought about by the expert’s input. This approach can enhance the management of exceptions/corner cases typical to regulated domains, the automation of which must consider compliance and legal requirements. The paper focuses on how human intervention can be combined in DRL to augment the reward schemes that are superior to those provided by purely automated systems to human overseers. The efficiency of the hybrid system of DRL coupled with RPA in real-world use cases that involve processing legal documents and medical records is well supported. Currently, feedback from people in DRL for RPA has the potential to create more dynamic, dependable, and adherent robotic processes in various stringent compliance contexts.