SIRIS-Lab/unlabelled-sti-corpus huggingface dataset:
New generation cell therapy: bioartificial pancreas to cure type 1 diabetes

Forty million individuals worldwide suffer from type 1 diabetes. This disease is managed by insulin therapy in a vast majority of patients because of the limited accessibility of beta cell replacement therapies (pancreas or islet of Langerhans transplantation). There is an urgent need for the development of a beta cell replacement therapy that will be available to larger numbers of type 1 diabetic patients. 
The VANGUARD project aims to deliver an Advanced Therapeutic Medicinal Product (ATMP) of high translational potential, with properties of increased functionality and implantability and protection from immune destruction. 
We will construct a bioartificial pancreas by assembling insulin- producing organoids, composed of islet cells, human amniotic epithelial cells (hAEC) and blood outgrowth endothelial cells (BOECs), into an amniotic membrane-derived hydrogel. Components of the amniotic membrane will provide extracellular matrix and mechanical protection and confer their well-defined anti-inflammatory and immunomodulatory properties to the constructs. hAECs will be genome-edited to overexpress and locally release immunomodulatory molecules (HLA-G, HLA-E, CD47 and PD-L1) and endothelial cells will enhance graft revascularization. Functionality, biocompatibility, potency and safety of the bioartificial pancreas will be assessed in vitro and in vivo by implantation in mice reconstituted with a human immune system as pre-clinical model. 
The consortium consists of 5 academic institutions with leading scientists in their field, 2 SMEs and 1 NGO with expertise in ethical and social aspects of transplantation. 
The ATMP delivered upon completion of the project will provide a model for rapid development of a bioartificial pancreas, utilizing “infinite” sources of insulin-producing cells (stem cell-derived, xenogeneic), and available to all type 1 diabetic patients before they develop the devastating chronic complications of the disease.
Animal ethics and contemporary art : an exploration of the intersections between ethics and aesthetics, humans and animals, human and animal injustices

This research provides artistic interventions into the question of institutionalised violence against animals. With a relational and holistic vision in mind, this artistic enquiry explores the intersections between ethics and aesthetics, humans and animals, human and animal injustices. It is dualistic and anthropocentric thinking that underlies both human and animal oppression. A Derridean approach invites us to think about the shared vulnerability among all beings through the presence of the animal other, calling our infinite responsibility towards the animal and dismantling entwined dualisms. With regard and respect, we are encouraged to appreciate the animal as a singular, specific, valuable being, rather than a predetermined, dualistic category. Formally and conceptually informed by contemporary art addressing both human and animal oppression, this enquiry critically reflects on the invisibility of violence towards animals which contributes collective ignorance and indifference to animal suffering. Translating the testimony of animal’s plight into poetic representation, I propose three pieces of large-scale, mixed-media installation works, combining aesthetic elements such as paintings, feathers, fabrics, lights, spaces, and audience experiences to confront the viewer with this question. In so doing, I believe that the poetics of art has the potential of transforming public consciousness of thinking about animals in non-binary and non-instrumental terms.
CROSSLINKED POLYETHYLENE ARTICLE

A method of manufacturing an article may include crosslinking a UHMWPE preform, shaping the crosslinked preform, heat-treating the shape in a temperature-controlled oven and low-oxygen environment, and inspecting the heat-treated shape for conformance to article specifications.
Ovca for precision medicine: personalized ovarian cancer treatment using high-throughput and microfluidic drug screening.

OvCa for Precision Medicine: Personalized Ovarian Cancer Treatment using High-Throughput and Microfluidic Drug Screening.

 The main issue with current Ovarian Cancer (OvCa) treatments is the eventual resistance to standard platinum-based chemotherapy, which ultimately leads patients to relapse. Identifying drugs and drug combinations that overcome platinum resistance by new treatment strategies is an unmet medical need in OvCa patients that I plan to address with our technology pipeline as a Proof-of-Concept. I, Deepak Balaji Thimiri Govinda Raj, under the supervision and mentorship of Dr. Dalu Mancama (Precision Medicine) and Dr. Janine Scholefield (Synthetic Biology) at CSIR South Africa along with Prof. Nicholas Dunne and Dr. David Kinahan at Dublin City University (DCU), propose developing a cutting-edge technology pipeline with which I will identify and screen drugs and drug combinations for relapsed OvCa patients who have exhausted all other treatment options. I will use OvCa patient samples to validate the drug screening pipeline as a Proof-of-Concept. Our technology pipeline includes strategies where I will combine tissue engineering (Prof. Nicholas Dunne’s team) with microfluidic technology (Dr. David Kinahan, DCU), Chemstress platform (Dr. Jerry Clifford, ValitaCell) and my expertise in chemical biology accumulated during my PhD and three post-doctoral placements. Using this pipeline, we aim to identify drug combinations that can overcome platinum resistance and ultimately provide tailored-specific therapy options for OvCa patients. We intend our technologies to provide clinically relevant drug combinations information to oncologists.
Changes in the Human Metabolome Associated With Alcohol Use: A Review

The metabolome refers to the functional status of the cell, organ or the whole body. Metabolomic methods measure the metabolome (metabolite profile) which can be used to examine disease progression and treatment responses. Here, our aim was to review metabolomics studies examining effects of alcohol use in humans.We performed a literature search using PubMed and Web of Science for reports on changes in the human metabolite profile associated with alcohol use; we found a total of 23 articles published before end of 2018.Most studies had investigated plasma, serum or urine samples; only four studies had examined other sample types (liver, faeces and broncho-alveolar lavage fluid). Levels of 51 metabolites were altered in two or more of the reviewed studies. Alcohol use was associated with changes in the levels of lipids and amino acids. In general, levels of fatty acids, phosphatidylcholine diacyls and steroid metabolites tended to increase, whereas those of phosphatidylcholine acyl-alkyls and hydroxysphingomyelins declined. Common alterations in circulatory levels of amino acids included decreased levels of glutamine, and increased levels of tyrosine and alanine.More studies, especially with a longitudinal study design, or using more varied sample materials (e.g. organs or saliva), are needed to clarify alcohol-induced diseases and alterations at a target organ level. Hopefully, this will lead to the discovery of new treatments, improved recognition of individuals at high risk and identification of those subjects who would benefit most from certain treatments.
Using Lorenz Curve to Analyze Land Use Structure in Xinjiang Production and Construction Corps

Based on land use data from 1996 to 2009 in Xinjiang Production and Construction Corps,the quantitative analysis of land use structure was conducted by using Lorenz curve and Gini coefficients which were applied to measure property,the extent of the resource allocation.The results indicated that town village and industrial land and the transportation land distribution is more balanced,the spatial gene coefficient are 0.064,0183 respectively;garden distribution is the most concentrated with the gene coefficient 0.485.The last 10a,forest land,town village and industrial land,transportation land use distribution trend is balanced,the rest of class distribution tend to concentrate.Among them,the garden change is the most significant.Space Lorentz curve theory can reflect the regional land use types in the region configuration and contrast relations,concentration quantitative research by using Gini coefficient can provide a reference for land use structure optimization of Xinjiang Production and Construction Corps.
Corrector equations and random operators

Consider a partial differential equation (PDE) with random coefficients as in engineering or applied physics: When combined with a spatial scale separation, the randomness and the differential operator interact to give rise to some effective behavior. The recent growing mathematical activity in this domain has led to a ``seemingly'' complete theory of stochastic homogenization  of linear elliptic operators. Central to this theory is the so-called corrector equation, a degenerate elliptic equation posed on the (infinite-dimensional) probability space. The context of linear elliptic operators yields the simplest such equation.  Time-dependent and/or nonlinear PDEs also involve corrector equations (or a family thereof), albeit with a significantly more complex structure. Their study and use to characterize the large-scale/time behavior of solutions of PDEs with random coefficients are at the heart of this project.  Whereas the relevance of corrector equations is clear in problems such as diffusion in random media, sedimentation of randomly placed particles in a fluid, or water waves on a rough bottom, it is less obvious for the long-time behavior of waves in disordered media. The latter is related to the spectrum of the associated random elliptic operator, the characterization of which still remains a largely open question today. We propose to relate the long-time behavior of waves to the properties of a family of corrector equations.     These corrector equations are widely unstudied and offer many analytical challenges. They constitute the first half of the project. Even in the ``well-understood'' setting of linear elliptic operators, this requires to revisit the corrector equation in the light of much weaker topologies than considered before.  The second half of the project aims at using correctors to establish the large-scale behavior of solutions as random objects. This may involve surprising quantities such as the recently introduced ``homogenization commutator"".
Assessment of Children in Pain in the Emergency Department

Pediatric Oncology Intensive Care Unit University of Sao Paulo Sao Paulo, SP, Brazil [email protected] Disclosure: The authors declare no conflict of interest.
Differential evolution optimisation of a two echelon inventory system.

In this thesis, we consider the effectiveness of Differential Evolution as a computational algorithm in the context of spare part inventory optimisation in a two-echelon supply chain setting. The study of DE in application to supply chain planning is limited; thus, we present a well-known hard discrete non-linear stochastic optimisation problem to determine the inventory investment for a two-echelon supply chain system. The underlying optimisation problem is notoriously difficult since it has discrete variables and is combinatorial in nature. We assume the best-in-class algorithm in the field of Operations Research to be the optimum optimisation algorithm for the problem under study. We aim to determine the accuracy of DE in generating to the best-in-class optimum solutions for the problem. We select DE control parameters that best fit the problem and select two DE Algorithm variants for the analysis. We create a series of complex conditions in which we expect DE to achieve the optimum solutions and present our case for comparison to the best-in-class method. We show specific enhancements to the DE algorithm to provide a robust method of achieving the optimum solutions unique to the problem under study. In addition, we derive conclusions on the scalability of DE and which DE algorithm is the preferred algorithm for the problem under study. Further, we formulate conclusions under which problem conditions; each DE Algorithm is best suited to achieve the optimum solutions and which DE Algorithm is comparable to the best-in-class analytical method. Finally, we present areas of further research for the application of DE in the context of inventory supply chain.
Hydrogen release by thermolysis of ammonia borane NH3BH3 and then hydrolysis of its by-product [BNHx]

Abstract Ammonia borane (AB) is one of the most attractive hydrides owing to its high hydrogen density (19.5 wt%). Stored hydrogen can be released by thermolysis or catalyzed hydrolysis, both routes having advantages and issues. The present study has envisaged for the first time the combination of thermolysis and hydrolysis, AB being first thermolyzed and then the solid by-product believed to be polyaminoborane [NH 2 BH 2 ] n (PAB) being hydrolyzed. Herein we report that: (i) the combination is feasible, (ii) PAB hydrolyzes in the presence of a metal catalyst (Ru) at 40 °C, (iii) a total of 3 equiv. H 2 is released from AB and PAB–H 2 O, (iv) high hydrogen generation rates can be obtained through hydrolysis, and (v) the by-products stemming from the PAB hydrolysis are ammonium borates. The following reactions may be proposed: AB → PAB + H 2 and PAB +  x H 2 O → 2H 2  + ammonium borates. All of these aspects as well as the advantages and issues of the combination of AB thermolysis and PAB hydrolysis are discussed.
A METHOD, APPARATUS AND COMPUTER PROGRAM FOR MOVING DATA IN MEMORY

A memory resource is divided between multiple memory banks, each of which can be powered-down individually. In order to minimise power consumption by the resource, each bank is assigned a priority and data is compacted into those banks having the highest priorities. As low-priority banks are emptied, they can be powered down. In one arrangement, the banks with the highest power consumption and lowest performance are assigned the lowest priorities.
Structure and magnetic properties of bulk nanocrystalline Tm2(Co1−xFex)17 permanent magnet

Structure and magnetic properties were studied for Tm2(Co1−xFex)17 bulk nanocrystalline magnet synthesized by spark plasma sintering technique. X-ray diffraction results indicate both ingot and sintered magnet of Tm2(Co0.7Fe0.3)17 alloy exhibit hexagonal Th2Ni17 type structure. The microstructure of the magnet is composed of Th2Ni17 type nanograins with an average size of 35 nm detected by transmission electron microscopy and selected area electron diffraction patterns. Magnetic measurement shows that the remanence of the magnet is higher at 573 K than at 300 K, indicating there is a positive remanence temperature coefficient in the magnet. The anisotropy field of Tm2(Co0.7Fe0.3)17 alloy is 3.8 T, which is much higher than the HA of 2.3 T for the pure Tm2Co17 alloy. The coercivity of the sintered magnet increases from 0.25 to 0.354 T after optimal annealing.
Elastic covering material having improved flame retardant properties and production thereof

The invention relates to an elastic covering material, which comprises, as a flame retardant, a phosphinate salt of the formula (I) and/or a diphosphinate salt of the formula (II) and/or polymers thereof where R<1>, R<2 >are the same or different and are each C1-C6-alkyl, linear or branched, and/or aryl; R<3 >is C1-C10-alkylene, linear or branched, C6-C10-arylene, -alkylarylene or -arylalkylene; M is Mg, Ca, Al, Sb, Sn, Ge, Ti, Zn, Fe, Zr, Ce, Bi, Sr, Mn, Li, Na, K and/or a protonated nitrogen base; m is from 1 to 4; n is from 1 to 4; x is from 1 to 4. The invention relates to processes for producing such elastic covering materials.
Time Reversal Guided Waves for Inspecting Crack in Pipeline by Non-axisymmetric Excitation

Currently guided wave time-reversal method for pipe inspection requires using multi-channels to excite and receive signal at the same time.After studying the flexural modal cluster exciting properties,a new time-reversal method based on single oblique transducer with partial loading exciting L(M,2) modal cluster is presented.The feasibility of time reversal focusing method with L(M,2) modal cluster is verified using oblique transducer array and self-developed excitation/receiving board.The focusing effect is experimentally studied in pipeline with crack by using different initial excitation signal types,center frequencies and time reversal window width.The results show that in different inspection frequencies with narrow or wide bandwidth initial excitation signal,amplitude of the defect echo and S/N ratio have significant improvement after using time reversal focusing method,thus defect echo signal can be obviously distinguished by time reversal focusing inspection.
BIODEGRADABLE EXCIPIENT SYSTEMS FOR THERAPEUTICALLY ACTIVE SUBSTANCES AND METHOD FOR PRODUCING THE SAME

The invention relates to a formulation for a sustained-release biodegradable medicament that contains an excipient system. Said excipient system consists of biodegradable blood plasma products that have been dried in a fluidized bed while maintaining their properties and an active substance to be applied as a sustained-release substance or a combination of active substances.
4th National Congress of the Bulgarian Society for Dermatologic Surgery, Sofia, 12th March 2022 with main topics: one step melanoma surgery and drug induced melanoma

Not available
ROLLABLE RABBIT HUTCH

The invention relates to an arrangement for a hutch (2) for rabbits (3) or other similar animals, which hutch (2) is in the form of a grille construction. The hutch (2) exhibits round circumferential form enabling it to roll on a base (4), the envelope surface of the hutch is formed by a large number of wires (6) or rods extending between pairs of end walls (7, 8) situated at a mutual distance from one another, and the hutch is so arranged as to be capable of being accommodated in a box frame (9). The hutch exhibits a screened-off space, inside which the animal can be protected from the sun and the rain, which space is formed by a separate box so arranged as to be detachably attachable to one end wall of the hutch on its outside by means of connecting devices.
A probabilistic imputation framework for predictive analysis using variably aggregated, multi-source healthcare data

In healthcare-related studies, individual patient or hospital data are not often publicly available due to privacy restrictions, legal issues or reporting norms. However, such measures may be provided at a higher or more aggregated level, such as state-level, county-level summaries or averages over health zones (HRR1 or HSA2). Such levels constitute partitions of the underlying individual level data, which may not match the data segments that would have been obtained if one clustered individual-level data. Treating these aggregated values as representatives for the individuals can result in the ecological fallacy. How can one run data mining procedures on such data where different variables are available at different levels of aggregation or granularity? We examine this problem in a clustering setting given a mix of individual-level and (arbitrarily) aggregated-level data. For this setting, a generative process of such data is constructed using a Bayesian directed graphical model. This model is further developed to capture the properties of the aggregated-level data using the Central Limit theorem. The model provides reasonable cluster centroids under certain conditions, and is extended to estimate the masked individual values for the aggregated data. The model parameters are learned using an approximated Gibbs sampling method, which employs the Metropolis-Hastings algorithm efficiently. A deterministic approximation algorithm is derived from the model, which scales up to massive datasets. Furthermore, the imputed features can help to improve the performance in subsequent predictive modeling tasks. Experimental results using data from the Dartmouth Health Atlas, CDC, and the U.S. Census Bureau are provided to illustrate the generality and capabilities of the proposed framework.
Comparison of Machine Learning Classifiers for Recognition of Online and Offline Handwritten Digits

Automated recognition of handwritten digits has applications in several industries such as Postal and Banking for reading of addressed packages and cheques respectively. This paper compares four machine learning classifiers namely Naive Bayes, Instance Based Learner, Decision Tree and Neural Network for single digit recognition. Our experiments were conducted using the WEKA machine learning tool on two datasets; the MNIST offline handwritten digits and a collection of online ISGL handwritten digits acquired with a pen digitiser. Experiments were designed to allow for comparison within the datasets in a cross validation and across them where the online dataset is used for training and the offline dataset for testing and vice versa. We also compared classification accuracy at different levels of down sampling. Results indicate that the lazy learning instance based classifier performed slightly better than the neural network with a maximal accuracy of 97.86% and they both outperformed the other two classifiers: Naive Bayes and Decision Tree. The decision tree gave the worst performance of the four classifiers. We also discovered that better results were obtained with using the online digits when tested in a cross validation experiment. However, the pre-processed MNIST offline digits gave higher accuracies when used for training and tested with the online ISGL digits not vice versa. Also, we discovered down sampled size of 14x14 gave the best results for most of the four classifiers although these were not significantly different from the other down sampled sizes of 7x7, 21x21 and 28x28. We intend to investigate the performance of these classifiers in recognition of other characters (alphabets, punctuation and other symbols) as well as extend the recognition task to other levels of text granularity such as words, sentences and paragraphs. Keywords: Digits recognition, machine learning, classifiers, handwritten character recognition, Weka
Analyses of peg‐hole jamming in automatic assembly machines

Purpose The purpose of this paper is to investigate theoretically the process of jamming in the peg‐hole type parts and to derive a mathematical model of jamming. Design/methodology/approach The mathematical model of the jamming of the peg‐hole type parts in assembly process was performed and its boundary conditions, which lead to jamming, defined. Findings The equation of the critical angles of declination for the peg, which leads to the peg‐hole jam, was derived. The boundary condition of the angles of declination and the depth of the peg insertion into the hole were defined. Research limitations/implications A mathematical model is developed for rigid parts with a hole and for the peg clamped in the rigid assembly mechanisms. The research has not considered flexible deformations and stiffness of the assembly mechanisms, which result in the peg's declination in the assembly process. Practical implications The results are represented in the form of the peg's critical angles of declination and critical depth of insertion into the hole, which leads to jamming of the peg‐hole type parts to be assembled. On the basis of the obtained results, it is possible to formulate the tolerances of the declination angles for the assembly mechanisms, which clamp the peg‐type parts. Originality/value The proposed method calculating the critical angles of the peg's declination and critical depth of the peg's insertion into the hole for assembly of the peg‐hole type parts, enables one to increase the reliability of the assembly process in the manufacturing industry.