Language in a world of plurality:the tree, the bot and the octopus teacher

Abstract. Language has been considered proof of human exceptionalism in the Western European culture since the Enlightenment era. As a result, a rigid hierarchy placing human on the top emerged. Due to human’s capacity to rationalize thought and materialize it using language as a tool, it entitled itself to possess and dispose of anything deemed as less- or non-human. Once the fixed idea of language is destabilized, its accuracy as a tool fit enough to represent the world and human thought comes into question. Once language, a pillar of Humanism, is damaged, the collapse of human exceptionalism is imminent. Post-humanism and ontological pluralism are offering the grounds for exploring a paradigm without the hierarchy. A flattened reality in which the relationships between ways of being are far more complex than mere hierarchies, food chains, or concentric circles. They are entangled, mangled. They are plugging-in and unplugging in an assemblage. For inquiring into an assemblage, tools such as qualitative methodologies, representational logic and data become useless. Meanwhile, post-qualitative inquiries do not pretend to ascend the ultimate, pure knowledge or truth but simply offer a brief, incomplete glimpse into the assemblage. The results of such destabilizations consist of more care and attention being offered to negotiating language and languaging, empty spaces and howls, communication outside the higher senses of sight and hearing. In education, it translates into alternative teachers and teachings. The learners are entangled into an assemblage with which they are inter-acting by forming relationships. They are learning to co-live with rather than to make sense of the ways of being

On Optimal Coverage of a Tree with Multiple Robots

We study the algorithmic problem of optimally covering a tree with $k$ mobile robots. The tree is known to all robots, and our goal is to assign a walk to each robot in such a way that the union of these walks covers the whole tree. We assume that the edges have the same length, and that traveling along an edge takes a unit of time. Two objective functions are considered: the cover time and the cover length. The cover time is the maximum time a robot needs to finish its assigned walk and the cover length is the sum of the lengths of all the walks. We also consider a variant in which the robots must rendezvous periodically at the same vertex in at most a certain number of moves. We show that the problem is different for the two cost functions. For the cover time minimization problem, we prove that the problem is NP-hard when $k$ is part of the input, regardless of whether periodic rendezvous are required or not. For the cover length minimization problem, we show that it can be solved in polynomial time when periodic rendezvous are not required, and it is NP-hard otherwise

Strong Pinning in High Temperature Superconductors

Detailed measurements of the critical current density jc of YBa2Cu3O7 films grown by pulsed laser deposition reveal the increase of jc as function of the filmthickness. Both this thickness dependence and the field dependence of the critical current are consistently described using a generalization of the theory of strong pinning of Ovchinnikov and Ivlev [Phys. Rev. B 43, 8024 (1991)]. From the model, we deduce values of the defect density (10^21 m^-3) and the elementary pinning force, which are in good agreement with the generally accepted values for Y2O3-inclusions. In the absence of clear evidence that the critical current is determined by linear defects or modulations of the film thickness, our model provides an alternative explanation for the rather universal field dependence of the critical current density found in YBa2Cu3O7 films deposited by different methods.Comment: 11 pages; 8 Figures; Published Phys. Rev. B 66, 024523 (2002

Surgical management of symptomatic spinal cord and intracerebral cavernomas in a multiple cavernomas case

Multiple cavernous malformations are associated with familial cases and are present in 10-20% of all cavernoma cases. 5% of cavernomas are located intramedullary and of these only 10% present multiple cavernomas. With the availability of echo gradient MRI the cases of multiple cavernomas are diagnosed earlier and it is not rare that it uncovers multiple cavernomas in cases where only a single lesion can be identified on regular MRI sequences. We present the case of a 55 years old woman presented with a two years history of mild backache, followed by progressive lower legs motor deficit and urinary retention. The spine MRI showed an intramedullary T2/3 lesion and the cerebral MRI established the diagnosis of multiple cavernomas. One year after the intramedullary cavernoma was operated with success, she developed generalized seizures and a new cerebral MRI showed bleeding and volume growth of one right temporal pole cavernoma. The cerebral lesion was resected successfully and the patient was discharged free of seizures. This familial type multiple cavernomas cases should be screened and followed with repeated brain and spine MRI’s every year

Statistical analysis of compressive low rank tomography with random measurements

We consider the statistical problem of 'compressive' estimation of low rank states (r«d ) with random basis measurements, where r, d are the rank and dimension of the state respectively. We investigate whether for a fixed sample size N, the estimation error associated with a 'compressive' measurement setup is 'close' to that of the setting where a large number of bases are measured. We generalise and extend previous results, and show that the mean square error (MSE) associated with the Frobenius norm attains the optimal rate rd/N with only O(rlogd) random basis measurements for all states. An important tool in the analysis is the concentration of the Fisher information matrix (FIM). We demonstrate that although a concentration of the MSE follows from a concentration of the FIM for most states, the FIM fails to concentrate for states with eigenvalues close to zero. We analyse this phenomenon in the case of a single qubit and demonstrate a concentration of the MSE about its optimal despite a lack of concentration of the FIM for states close to the boundary of the Bloch sphere. We also consider the estimation error in terms of a different metric–the quantum infidelity. We show that a concentration in the mean infidelity (MINF) does not exist uniformly over all states, highlighting the importance of loss function choice. Specifically, we show that for states that are nearly pure, the MINF scales as 1/√N but the constant converges to zero as the number of settings is increased. This demonstrates a lack of 'compressive' recovery for nearly pure states in this metric

Bioengineering bacterial encapsulin nanocompartments as targeted drug delivery system

The development of Drug Delivery Systems (DDS) has led to increasingly efficient therapies for the treatment and detection of various diseases. DDS use a range of nanoscale delivery platforms produced from polymeric of inorganic materials, such as micelles, and metal and polymeric nanoparticles, but their variant chemical composition make alterations to their size, shape, or structures inherently complex. Genetically encoded protein nanocages are highly promising DDS candidates because of their modular composition, ease of recombinant production in a range of hosts, control over assembly and loading of cargo molecules and biodegradability. One example of naturally occurring nanocompartments are encapsulins, recently discovered bacterial organelles that have been shown to be reprogrammable as nanobioreactors and vaccine candidates. Here we report the design and application of a targeted DDS platform based on the Thermotoga maritima encapsulin reprogrammed to display an antibody mimic protein called Designed Ankyrin repeat protein (DARPin) on the outer surface and to encapsulate a cytotoxic payload. The DARPin9.29 chosen in this study specifically binds to human epidermal growth factor receptor 2 (HER2) on breast cancer cells, as demonstrated in an in vitro cell culture model. The encapsulin-based DDS is assembled in one step in vivo by co-expressing the encapsulin-DARPin9.29 fusion protein with an engineered flavin-binding protein mini-singlet oxygen generator (MiniSOG), from a single plasmid in Escherichia coli. Purified encapsulin-DARPin_miniSOG nanocompartments bind specifically to HER2 positive breast cancer cells and trigger apoptosis, indicating that the system is functional and specific. The DDS is modular and has the potential to form the basis of a multi-receptor targeted system by utilising the DARPin screening libraries, allowing use of new DARPins of known specificities, and through the proven flexibility of the encapsulin cargo loading mechanism, allowing selection of cargo proteins of choice

Neuro-immune signatures in chronic low back pain subtypes

We recently showed that patients with different chronic pain conditions (such as chronic low back pain, fibromyalgia, migraine, and Gulf War Illness) demonstrated elevated brain and/or spinal cord levels of the glial marker 18 kDa translocator protein, which suggests that neuroinflammation might be a pervasive phenomenon observable across multiple etiologically heterogeneous pain disorders. Interestingly, the spatial distribution of this neuroinflammatory signal appears to exhibit a degree of disease specificity (e.g. with respect to the involvement of the primary somatosensory cortex), suggesting that different pain conditions may exhibit distinct “neuroinflammatory signatures”. To further explore this hypothesis, we tested whether neuroinflammatory signal can characterize putative etiological subtypes of chronic low back pain patients based on clinical presentation. Specifically, we explored neuroinflammation in patients whose chronic low back pain either did or did not radiate to the leg (i.e. “radicular” vs. “axial” back pain). Fifty-four chronic low back pain patients, twenty-six with axial back pain (43.7 ± 16.6 y.o. [mean±SD]) and twenty-eight with radicular back pain (48.3 ± 13.2 y.o.), underwent PET/MRI with [11C]PBR28, a second-generation radioligand for the 18 kDa translocator protein. [11C]PBR28 signal was quantified using standardized uptake values ratio (validated against volume of distribution ratio; n = 23). Functional MRI data were collected simultaneously to the [11C]PBR28 data 1) to functionally localize the primary somatosensory cortex back and leg subregions and 2) to perform functional connectivity analyses (in order to investigate possible neurophysiological correlations of the neuroinflammatory signal). PET and functional MRI measures were compared across groups, cross-correlated with one another and with the severity of “fibromyalgianess” (i.e. the degree of pain centralization, or “nociplastic pain”). Furthermore, statistical mediation models were employed to explore possible causal relationships between these three variables. For the primary somatosensory cortex representation of back/leg, [11C]PBR28 PET signal and functional connectivity to the thalamus were: 1) higher in radicular compared to axial back pain patients, 2) positively correlated with each other and 3) positively correlated with fibromyalgianess scores, across groups. Finally, 4) fibromyalgianess mediated the association between [11C]PBR28 PET signal and primary somatosensory cortex-thalamus connectivity across groups. Our findings support the existence of “neuroinflammatory signatures” that are accompanied by neurophysiological changes, and correlate with clinical presentation (in particular, with the degree of nociplastic pain) in chronic pain patients. These signatures may contribute to the subtyping of distinct pain syndromes and also provide information about inter-individual variability in neuro-immune brain signals, within diagnostic groups, that could eventually serve as targets for mechanism-based precision medicine approaches

Anatomy-Aware Self-supervised Fetal MRI Synthesis from Unpaired Ultrasound Images

Fetal brain magnetic resonance imaging (MRI) offers exquisite images of the developing brain but is not suitable for anomaly screening. For this ultrasound (US) is employed. While expert sonographers are adept at reading US images, MR images are much easier for non-experts to interpret. Hence in this paper we seek to produce images with MRI-like appearance directly from clinical US images. Our own clinical motivation is to seek a way to communicate US findings to patients or clinical professionals unfamiliar with US, but in medical image analysis such a capability is potentially useful, for instance, for US-MRI registration or fusion. Our model is self-supervised and end-to-end trainable. Specifically, based on an assumption that the US and MRI data share a similar anatomical latent space, we first utilise an extractor to determine shared latent features, which are then used for data synthesis. Since paired data was unavailable for our study (and rare in practice), we propose to enforce the distributions to be similar instead of employing pixel-wise constraints, by adversarial learning in both the image domain and latent space. Furthermore, we propose an adversarial structural constraint to regularise the anatomical structures between the two modalities during the synthesis. A cross-modal attention scheme is proposed to leverage non-local spatial correlations. The feasibility of the approach to produce realistic looking MR images is demonstrated quantitatively and with a qualitative evaluation compared to real fetal MR images.Comment: MICCAI-MLMI 201

The pandemic brain: Neuroinflammation in non-infected individuals during the COVID-19 pandemic

While COVID-19 research has seen an explosion in the literature, the impact of pandemic-related societal and lifestyle disruptions on brain health among the uninfected remains underexplored. However, a global increase in the prevalence of fatigue, brain fog, depression and other “sickness behavior”-like symptoms implicates a possible dysregulation in neuroimmune mechanisms even among those never infected by the virus. We compared fifty-seven ‘Pre-Pandemic’ and fifteen ‘Pandemic’ datasets from individuals originally enrolled as control subjects for various completed, or ongoing, research studies available in our records, with a confirmed negative test for SARS-CoV-2 antibodies. We used a combination of multimodal molecular brain imaging (simultaneous positron emission tomography / magnetic resonance spectroscopy), behavioral measurements, imaging transcriptomics and serum testing to uncover links between pandemic-related stressors and neuroinflammation. Healthy individuals examined after the enforcement of 2020 lockdown/stay-at-home measures demonstrated elevated brain levels of two independent neuroinflammatory markers (the 18 kDa translocator protein, TSPO, and myoinositol) compared to pre-lockdown subjects. The serum levels of two inflammatory markers (interleukin-16 and monocyte chemoattractant protein-1) were also elevated, although these effects did not reach statistical significance after correcting for multiple comparisons. Subjects endorsing higher symptom burden showed higher TSPO signal in the hippocampus (mood alteration, mental fatigue), intraparietal sulcus and precuneus (physical fatigue), compared to those reporting little/no symptoms. Post-lockdown TSPO signal changes were spatially aligned with the constitutive expression of several genes involved in immune/neuroimmune functions. This work implicates neuroimmune activation as a possible mechanism underlying the non-virally-mediated symptoms experienced by many during the COVID-19 pandemic. Future studies will be needed to corroborate and further interpret these preliminary findings