SIRIS-Lab/unlabelled-sti-corpus huggingface dataset:
Novel advanced encapsulation system for delivery and protection of next-generation cell-based therapies

Cell and gene therapies holds tremendous therapeutic promise for patients worldwide and represent a valuable global market opportunity. Still, cell-based therapies present challenges related chiefly to cell retention, engraftment and survival. Minimally invasive cell delivery and improved retention by means of an encapsulation technology is a driver for generating more predictable clinical outcomes with lesser immune rejection in a variety of disease areas. Stemmatters has built a highly versatile platform technology to design novel molecules with attributes to safeguard cells and support cell function and retention. Based on a chemically defined template, our technology provides rapid generation of compound libraries supporting establishment of safe, less costly and more effective cell-based therapies. The performance and cost effectiveness of our development platform surpasses competing technologies. 
NOAHs-ARK (spelled as Noah´s ark) aims to disrupt the current market landscape by developing Stemmatters’ encapsulation platform to other therapeutic applications of large unmet demand. Recruitment and integration of an Innovation associate (IA) with specific expertise in cell-based therapy into Stemmatters is a significant milestone that will dramatically increase Stemmatters capabilities, strengthen existing collaborations, and expand business opportunities. The IA will provide Stemmatters with important technical expertise and a comprehensive understanding of market unmet needs and current competitive dynamics. The IA will lead development of our innovative platform to other therapeutic applications of large unmet need, by designing in vitro studies for specific disease indications in need of enabling cell encapsulation solutions. Biomaterials entering the pipeline will be supported by technical product dossiers to assist regulatory submissions, smooth translation to the clinic and commercialization by strategic licensing and/or supply agreements.
Improving Environmental and Social Targeting through Adaptive Management in Mexico's Payments for Hydrological Services Program

Natural resource managers are often expected to achieve both environmental protection and economic development even when there are fundamental trade-offs between these goals. Adaptive management provides a theoretical structure for program administrators to balance social priorities in the presence of trade-offs and to improve conservation targeting. We used the case of Mexico's federal Payments for Hydrological Services program (PSAH) to illustrate the importance of adaptive management for improving program targeting. We documented adaptive elements of PSAH and corresponding changes in program eligibility and selection criteria. To evaluate whether these changes resulted in enrollment of lands of high environmental and social priority, we compared the environmental and social characteristics of the areas enrolled in the program with the characteristics of all forested areas in Mexico, all areas eligible for the program, and all areas submitted for application to the program. The program successfully enrolled areas of both high ecological and social priority, and over time, adaptive changes in the program's criteria for eligibility and selection led to increased enrollment of land scoring high on both dimensions. Three factors facilitated adaptive management in Mexico and are likely to be generally important for conservation managers: a supportive political environment, including financial backing and encouragement to experiment from the federal government; availability of relatively good social and environmental data; and active participation in the review process by stakeholders and outside evaluators.
SYSTEM AND METHOD OF BOOTSTRAPPING A TEMPORARY PUBLIC -KEY INFRASTRUCTURE FROM A CELLULAR TELECOMMUNICATION AUTHENTICATION AND BILLING INFRASTRUCTURE

A system, method and computer program for ordering, paying for and delivering goods and services through the use of certificates. These certificates insure that the buyer is only billed once for the good or service purchased and only for the correct amount. This system, method and computer program employs the authentication center used to enable access to a telecommunication infrastructure to bootstrap a public-key infrastructure. This system, method and computer program will validate the identity of the mobile station being used utilizing log term keys stored in the mobile station and an authentication center. The system, method and computer program will then utilize these keys and variables to generate digital certificates and signatures which enable the purchase of goods and services using a mobile station. The gateway will then verify the authenticity of any charges made based on the digital certificates and signatures received. Thus, a user of this system, method and computer program can purchase goods and services without fear of fraud or errors. This mobile station may be a cellular phone and when used with this system, method and computer program the cellular phone may be used similarly to a credit card but with the advantage of little possibility of fraud or error.
Genetic algorithm-neural network : feature extraction for bioinformatics data

With the advance of gene expression data in the bioinformatics field, the questions which frequently arise,
for both computer and medical scientists, are which genes are significantly involved in discriminating cancer
classes and which genes are significant with respect to a specific cancer pathology. Numerous computational analysis models have been developed to identify informative genes from the microarray data, however, the integrity of the reported genes is still uncertain. This is mainly due to the
misconception of the objectives of microarray study. Furthermore, the application of various preprocessing
techniques in the microarray data has jeopardised the quality of the microarray data. As a result, the
integrity of the findings has been compromised by the improper use of techniques and the ill-conceived
objectives of the study. This research proposes an innovative hybridised model based on genetic algorithms (GAs) and artificial neural networks (ANNs), to extract the highly differentially expressed genes for a specific cancer pathology. The proposed method can efficiently extract the informative genes from the original data set and this has
reduced the gene variability errors incurred by the preprocessing techniques. The novelty of the research comes from two perspectives. Firstly, the research emphasises on extracting informative features from a high dimensional and highly complex data set, rather than to improve classification results. Secondly, the use of ANN to compute the fitness function of GA which is rare in the context
of feature extraction. Two benchmark microarray data have been taken to research the prominent genes expressed in the tumour development and the results show that the genes respond to different stages of tumourigenesis (i.e. different fitness precision levels) which may be useful for early malignancy detection. The extraction ability of the
proposed model is validated based on the expected results in the synthetic data sets. In addition, two bioassay data have been used to examine the efficiency of the proposed model to extract significant features from the large, imbalanced and multiple data representation bioassay data.
Tracing the origin and early evolution of animal cell type regulation with genomics and single-cell approaches

Cell types are the fundamental units of animal multicellularity. Distinct cell types are established and maintained by specific gene regulatory networks (GRNs), as well as epigenomic mechanisms that mediate the asymmetric access to genetic information within each cell. This cell regulation results in complex metazoan functions and structures. However, cell types and their regulation have only been characterized in a few species. Therefore, the origin and evolution of animal cell types remain largely unexplored, and so remains the evolution of the underlying GRNs and epigenomic mechanisms. 
In this project, we will develop a unified comparative framework to study cell type evolution and regulation from a multi-level and phylogenetic perspective. This project will focus on non-bilaterian metazoan lineages (Porifera, Ctenophora, Placozoa, and Cnidaria) as they are maximally informative towards reconstructing the evolutionary origins of metazoan genome regulation and of major cell types and their GRNs (e.g. neurons, secretory cells, stem cells, epithelial cells). To this end, we will integrate single-cell genomics and epigenomic profiling methods with advanced computational tools in order to: (1) investigate the origins of the animal regulatory genome; (2) characterize the diversity of cell type programs in non-bilaterian metazoans; and (3) model the structure and evolutionary dynamics of cell type-specific GRNs in these lineages. 
This evolutionary systems biology approach provides a complementary angle to both phylogenetically-restricted single-cell analyses and traditional cross-species studies based on targeted marker genes. Therefore, our results will fill a large gap of knowledge in our understanding of the origin and diversification of animal cell type programs and epigenomic mechanisms. In a broader context, this research program will provide unprecedented insights into the fundamental question of how cell types and their defining regulatory networks evolve.
The structure of apo ArnA features an unexpected central binding pocket and provides an explanation for enzymatic cooperativity

The bacterial protein ArnA is an essential enzyme in the pathway leading to the modification of lipid A with the pentose sugar 4-amino-4-deoxy-L-arabinose. This modification confers resistance to polymyxins, which are antibiotics that are used as a last resort to treat infections with multiple drug-resistant Gram-negative bacteria. ArnA contains two domains with distinct catalytic functions: a dehydrogenase domain and a transformylase domain. The protein forms homohexamers organized as a dimer of trimers. Here, the crystal structure of apo ArnA is presented and compared with its ATP- and UDP-glucuronic acid-bound counterparts. The comparison reveals major structural rearrangements in the dehydrogenase domain that lead to the formation of a previously unobserved binding pocket at the centre of each ArnA trimer in its apo state. In the crystal structure, this pocket is occupied by a DTT molecule. It is shown that formation of the pocket is linked to a cascade of structural rearrangements that emerge from the NAD + -binding site. Based on these findings, a small effector molecule is postulated that binds to the central pocket and modulates the catalytic properties of ArnA. Furthermore, the discovered conformational changes provide a mechanistic explanation for the strong cooperative effect recently reported for the ArnA dehydrogenase function.
Engineering and commercialization of a smart camera with on-chip image processing for head- and eye-tracking in laboratory animals

Rodents have become very popular models of cognitive functions, such as perception, memory and decision-making. Understanding the neuronal substrates of these processes requires performing neurophysiological recordings in awake animals, engaged in complex behavioral tasks. This, in turn, calls for tracking in real-time the motor behavior of the animal, to relate it to the underlying brain activity. Custom, as well as commercial, solutions exist that allows tracking basic behaviors in rodents – e.g., the 2D position and orientation of an animal over the arena where he navigates. However, while carrying out the research of the ERC project LEARN2SEE, we realized that methods for 3D reconstruction of some key behavioral features (e.g., pose of the head and gaze direction) are not commercially available, and the custom solutions found in the literature lack generality and are hard to implement and replicate. This prompted us to develop innovative, minimally invasive and user-friendly solutions to head/eye tracking in rodents. Yet, we soon faced another challenge – in order to perform high-throughput experiments, by testing in parallel many subjects (one of the advantages of rodent models over larger laboratory animals), our head/eye trackers would need to be re-engineered to make them easily replicable for series production. Critically, this would also allow transforming them into commercial devices for the ever-growing market of neurophysiology laboratories that, especially in the field of vision science, are employing rodents as model organisms. Here, we present our plan to achieve this goal, by migrating the tracking algorithms we developed for the LEARN2SEE project to smart cameras, engineered for real-time, on-board processing of head/eye video streams. These cameras will become a new product line of CyNexo, a recently established SISSA startup that operates in the market of laboratory equipment and is looking to expand its products’ package to videography tools.
METHODS OF MODULATING ANGIOGENESIS

A method of modulating angiogenesis, e.g., in the eye. The method includes modulating an SH2 domain-containing protein tyrosine phosphatase (PTPs).
Procedure for preparing reticulated polyethylene. (Machine-translation by Google Translate, not legally binding)

Process for preparing crosslinked polyethylene, characterized in that it comprises the steps of mixing polyethylene, a peroxide and a silane and then contacting the resulting mixture with water containing a silane condensation catalyst, to carry out the crosslinking. (Machine-translation by Google Translate, not legally binding)
1,3-Dimethyl- 1H-pyrazolo(4,3-D) pyrimidine-7 (6H)-ones

Novel 1,3-dimethyl-1H-pyrazolo[4,3-d]pyrimidine-7(6H)-ones. The compounds exhibit central nervous system activity, particularly anti-convulsant and sedative activity, and also exhibit anti-inflammatory activity and gastric antisecretory activity.
Using Neural Networks to Estimate Site-Specific Crop Evapotranspiration with Low-Cost Sensors

Irrigation efficiency is facilitated by matching irrigation rates to crop water demand based on estimates of actual evapotranspiration (ET). In production settings, monitoring of water demand is typically accomplished by measuring reference ET rather than actual ET, which is then adjusted approximately using simplified crop coefficients based on calendars of crop maturation. Methods to determine actual ET are usually limited to use in research experiments for reasons of cost, labor and requisite user skill. To pair monitoring and research methods, we co-located eddy covariance sensors with on-farm weather stations over two different irrigated crops (vegetable beans and hazelnuts). Neural networks were used to train a neural network and utilize on-farm weather sensors to report actual ET as measured by the eddy covariance method. This approach was able to robustly estimate ET from as few as four sensor parameters (temperature, solar radiation, humidity and wind speed) with training time as brief as one week. An important limitation found with this machine learning method is that the trained network is only valid under environmental and crop conditions similar to the training period. The small number of required sensors and short training times demonstrate that this approach can estimate site-specific and crop specific ET. With additional field validation, this approach may offer a new method to monitor actual crop water demand for irrigation management.
Large Housing Areas Stabilisation Action

Throughout the CADSES area, large housing areas, often located at the periphery of major cities, are of great importance for the future quality of life in urban areas. In Eastern and Central Europe, prefabricated housing slabs that give a home to about 30 million inhabitants are dominant. East German prefabricated housing areas show today problems of increasing vacancy and fluctuation - baring the dangers of social decline and leading indirectly to urban sprawl as many inhabitants move out into peripheral "green" towns. The problems in the new member states are similar in the long-term but different at present. Still presenting the dominant form of residence in many cities, ownership, shortages of living space and physical decay of the buildings are the main concerns today. LHASA will address both categories of problems. Building on the experiences of the City of Venice and the East German cities of Marzahn- Hellersdorf (Berlin) and Leipzig, which have experienced the transition process much faster than their counterparts in Central and Eastern Europe, the project will provide solutions for the further development of those areas in the contexts of urban planning, housing development, local economy and quality of life. LHASA aims to contribute to the stabilisation of large housing areas by integrated planning efforts (zoning plans), new initiatives for the reconstruction of the housing estate and possibilities to reuse vacant buildings, and through pilot measures to improve employment and social inclusion.
A time discontinuous Galerkin finite element method for generalized thermo-elastic wave analysis, considering non-Fourier effects

Generalized thermo-elastic theory, which is based on the non-Fourier theory, indicates that there is a time delay between the heat flux vector and the temperature gradient. At present, the traditional numerical method for solving the thermo-elastic problem subjected to high-frequency heat source generally fails to properly capture discontinuities of impulsive waves in space and produces spurious numerical oscillations in the simulation of high modes and sharp gradients. In the paper, a time discontinuous Galerkin finite element method (DGFEM) for the solution of generalized thermo-elastic coupled problems is presented on the basis of well-known Lord–Shulman theory. The essential feature of the DGFEM is that the general temperature-displacement vector and its temporal gradient are assumed to be discontinuous and interpolated individually at each time level in time domain, respectively. In order to filter out the spurious wave-front oscillations, an artificial damping scheme is implemented in the final finite element formula. Numerical results show that the present DGFEM shows good abilities and provides much more accurate solutions for generalized thermo-elastic coupled behavior. It can capture the discontinuities effectively at the wave front and filter out the effects of spurious numerical oscillation induced by a high-frequency thermal shock.
BIOMETRIC BASED CITIZEN INFORMATION SYSTEM

This paper presents a detailed study of implementations which we need in ‘Biometric Based Citizen Information System’. This system is used for maintaining the information of citizens and provides a simple interface for it. A number of organisations can use it for maintaining the citizen records easily. We cannot achieve said objective using a manual system because in these systems information is scattered, redundant and may consume large amount of time. These problems can be solved using Biometric Based Information System. The fundamental attention is on providing the information in an intelligent and easy manner. This system would be accustomed by the People who want to comphrend about such management systems, this system can be very identical for them. They can also develop number of software products for the same concept. A number of facilities like registration and profile creation of an individual are provided by this system, thereby reducing hectic paper work and hence automating generation of records.
MOTA: A Many-Objective Tuning Algorithm Specialized for Tuning under Multiple Objective Function Evaluation Budgets

Control parameter studies assist practitioners to select optimization algorithm parameter values that are appropriate for the problem at hand. Parameter values are well suited to a problem if they result in a search that is effective given that problem’s objective function(s), constraints, and termination criteria. Given these considerations a many-objective tuning algorithm named MOTA is presented. MOTA is specialized for tuning a stochastic optimization algorithm according to multiple performance measures, each over a range of objective function evaluation budgets. MOTA’s specialization consists of four aspects: (1) a tuning problem formulation that consists of both a speed objective and a speed decision variable; (2) a control parameter tuple assessment procedure that utilizes information from a single assessment run’s history to gauge that tuple’s performance at multiple evaluation budgets; (3) a preemptively terminating resampling strategy for handling the noise present when tuning stochastic algorithms; and (4) the use of bi-objective decomposition to assist in many-objective optimization. MOTA combines these aspects together with differential evolution operators to search for effective control parameter values. Numerical experiments consisting of tuning NSGA-II and MOEA/D demonstrate that MOTA is effective at many-objective tuning.
Lightweight and reliable emergency exits and cabin footstep for fast rotorcraft

To save more lives, civilian rotorcraft operators need to reduce operating time in the Search and Rescue missions or Emergency Medical Services. The primary answer to this time saving challenge is firstly, increase the speed of the rotorcraft and secondly, develop some innovative rotorcraft sub-systems facilitating patients access to the rescuers and the rotorcraft. Coupled to speeder, safer, more environmentally friendly, and more cost-efficient demands for the next generation of rotorcraft, CLEVER project is a perfect response to this challenge. Participating to the LifeRCraft Fast Rotorcraft development lead by Airbus Helicopter, Vision Systems Aeronautics through the CLEVER project will focus on the two main sub-systems development in the rotorcraft access in period of urgency: the emergency exits and the cabin footstep. In addition, acoustical and optical performances enhancements are proactively proposed to reinforce pilot’s safety and passenger’s comfort. Being a recognized EASA Part 21G Tier One System Supplier, Vision Systems Aeronautics proposes to completely develop and produce enhanced lightweight and aerodynamically efficient innovative composite doors and cabin footstep for the Clean Sky 2 FRC program able to be shortly introduced in mass-production. From first concept study at TRL4, up-to final qualification and flight test campaign completion and support at TRL8, Vision Systems Aeronautics will be the Partner expected by the Topic Leader, proposing simultaneously innovations and safe production readiness. A total of three complete high performant doors (left cockpit, right cockpit and cabin) and one cabin footstep demonstrators will be produced to issue required qualification tests, to deliver first functional airworthy prototypes and to equip the flying ITD LifeRCraft demonstrator.