The paper presents the results of modeling the bending strength of wood. During the experimental examination and definition of the model, solid wood was taken, where the bending was performed perpendicular to the grain. The experiment was done with thirteen replications and the input values that varied at three levels were wood density and board thickness. The thirteen-repetition experiment also involved four repetitions in the marginal areas, so two more wood densities and two board thicknesses had to be taken. The experimental measurement was performed in the laboratory of the Technical Faculty Bihać. Based on the experimental results, a sufficiently adequate mathematical model of the breaking force of a solid wood panel perpendicular to the grain is obtained.

Paper presents the design of experiment and determining mathematical model to calculate roughness parameter of wood planned surface. For design of experiment three different types of solid wood were taken and processed on the planner with three different displacements and three different cutting speeds. After measuring the roughness parameter Rz, experimental results were obtained on the basis of which the central composite plan of the experiment was made. Based on that, a model of roughness parameter Rz was made, which is adequate and with high accuracy. The significance of the model coefficients was determined using the R software and the results were presented using the Design Expert software.

Introduction unCoVer—Unravelling data for rapid evidence-based response to COVID-19—is a Horizon 2020-funded network of 29 partners from 18 countries capable of collecting and using real-world data (RWD) derived from the response and provision of care to patients with COVID-19 by health systems across Europe and elsewhere. unCoVer aims to exploit the full potential of this information to rapidly address clinical and epidemiological research questions arising from the evolving pandemic. Methods and analysis From the onset of the COVID-19 pandemic, partners are gathering RWD from electronic health records currently including information from over 22 000 hospitalised patients with COVID-19, and national surveillance and screening data, and registries with over 1 900 000 COVID-19 cases across Europe, with continuous updates. These heterogeneous datasets will be described, harmonised and integrated into a multi-user data repository operated through Opal-DataSHIELD, an interoperable open-source server application. Federated data analyses, without sharing or disclosing any individual-level data, will be performed with the objective to reveal patients’ baseline characteristics, biomarkers, determinants of COVID-19 prognosis, safety and effectiveness of treatments, and potential strategies against COVID-19, as well as epidemiological patterns. These analyses will complement evidence from efficacy/safety clinical trials, where vulnerable, more complex/heterogeneous populations and those most at risk of severe COVID-19 are often excluded. Ethics and dissemination After strict ethical considerations, databases will be available through a federated data analysis platform that allows processing of available COVID-19 RWD without disclosing identification information to analysts and limiting output to data aggregates. Dissemination of unCoVer’s activities will be related to the access and use of dissimilar RWD, as well as the results generated by the pooled analyses. Dissemination will include training and educational activities, scientific publications and conference communications.

One of the advantages provided by fused deposition modelling (FDM) 3D printing technology is the manufacturing of product materials with infill structure, which provides advantages such as reduced production time, product weight and even the final price. In this paper, the tensile mechanical properties, tensile strength and elastic modulus, of PLA, Tough PLA and PC FDM 3D printed materials with the infill structure were analysed and compared. Also, the influence of infill pattern on tensile properties was analysed. Material testing were performed according to ISO 527-2 standard. All results are statistically analysed and results showed that infill pattern have influence on tensile mechanical properties for all three materials.

Ex-vivo expanded tumour infiltrating lymphocytes (TIL) show promise in delivering durable responses among several solid tumour indications. However, characterising, quantifying and tracking the active component of TIL therapy remains challenging as the expansion process does not distinguish between tumour reactive and bystander T-cells. Achilles Therapeutics has developed ATL001, a patient-specific TIL-based product, manufactured using the VELOS™ process that specifically targets clonal neoantigens present in all tumour cells within a patient. Two Phase I/IIa clinical trials of ATL001 are ongoing in patients with advanced Non-Small Cell Lung Cancer, CHIRON (NCT04032847), and metastatic or recurrent melanoma, THETIS (NCT03997474). Extensive product characterisation and immune-monitoring are performed through Achilles’ manufacturing and translational science programme. This enables precise quantification and characterisation of the active component of this therapy – Clonal Neoantigen T cells (cNeT) – during manufacture and following patient administration, offering unique insight into the mechanism of action of ATL001 and aiding the development of next generation processes.ATL001 was manufactured using procured tumour and matched whole blood from 8 patients enrolled in the THETIS (n=5) and CHIRON (n=3) clinical trials. Following administration of ATL001, peripheral blood samples were collected up to week 6. The active component of the product was detected via re-stimulation with clonal neoantigen peptide pools and evaluation of IFN-γ and/or TNF-α production. Deconvolution of individual reactivities was achieved via ELISPOT assays. Immune reconstitution was evaluated by flow cytometry. cNeT expansion was evaluated by restimulation of isolated PBMCs with peptide pools and individual peptide reactivities (ELISPOT).The median age was 57 (range 30 – 71) and 6/8 patients were male. The median number of previous lines of systemic anti-cancer treatment at the time of ATL001 dosing was 2.5 (range 1 – 5). Proportion of cNeT in manufactured products ranged from 0.20% - 77.43% (mean 26.78%) and unique single peptide reactivities were observed in 7 of 8 products (range 0 – 28, mean 8.6). Post-dosing, cNeTs were detected in 5/8 patients and cNeT expansion was observed in 3/5 patients.These data underscore our ability to sensitively detect, quantify and track the patient-specific cNeT component of ATL001 – during manufacture and post dosing. As the dataset matures, these metrics of detection and expansion will be correlated with product, clinical and genomic characteristics to determine variables associated with peripheral cNeT dynamics and clinical response.NCT04032847, NCT03997474The first 8 patients described have all been located within the UK and both trials (CHIRON and THETIS) have been approved by the UK MHRA (among other international bodies, e.g FDA). Additionally, these trials have been approved by local ethics boards at active sites within the UK. Patient‘s are fully informed by provided materials and investigators prior to consenting to enrol into either ATL001 trial.

Abstract We analyze if various programs for entrepreneurs with disabilities (EWD) positively impact their self-efficacy. We examine if variations in self-efficacy of EWD are related to perceptions of social support, quality assistance from service providers, and perceived barriers to entrepreneurship as a way to evaluate the impact of programs for EWD. We draw upon Critical Disability Theory to understand if service providers act as ‘sites of injustice’ for EWD, creating further barriers, or as ‘sites of justice’ that positively impact their self-efficacy. Using a sample of 127 EWD, we find a positive relationship between the services received from entrepreneurship and disability-specific support programs on self-efficacy. Conversely, we find a strong negative relationship between barriers to entrepreneurship and the self-efficacy of EWD. We contribute by forwarding Critical Disability Theory to the realm of entrepreneurship and shedding new empirical light on EWD.

Introduction Deep learning techniques are gaining momentum in medical research. Evidence shows that deep learning has advantages over humans in image identification and classification, such as facial image analysis in detecting people’s medical conditions. While positive findings are available, little is known about the state-of-the-art of deep learning-based facial image analysis in the medical context. For the consideration of patients’ welfare and the development of the practice, a timely understanding of the challenges and opportunities faced by research on deep-learning-based facial image analysis is needed. To address this gap, we aim to conduct a systematic review to identify the characteristics and effects of deep learning-based facial image analysis in medical research. Insights gained from this systematic review will provide a much-needed understanding of the characteristics, challenges, as well as opportunities in deep learning-based facial image analysis applied in the contexts of disease detection, diagnosis and prognosis. Methods Databases including PubMed, PsycINFO, CINAHL, IEEEXplore and Scopus will be searched for relevant studies published in English in September, 2021. Titles, abstracts and full-text articles will be screened to identify eligible articles. A manual search of the reference lists of the included articles will also be conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework was adopted to guide the systematic review process. Two reviewers will independently examine the citations and select studies for inclusion. Discrepancies will be resolved by group discussions till a consensus is reached. Data will be extracted based on the research objective and selection criteria adopted in this study. Ethics and dissemination As the study is a protocol for a systematic review, ethical approval is not required. The study findings will be disseminated via peer-reviewed publications and conference presentations. PROSPERO registration number CRD42020196473.

The social significance and quality of scientific research largely depend on the usefulness of research results for the social and scientific community. The lack of funds and the desire to allocate funding to high-quality research projects make the assessment of the quality of research and the valorization of knowledge increasingly important. However, it is very difficult to apply criteria that can objectively assess scientific research, providing precise qualitative and quantitative data on which funding agencies could base their decisions. The product of scientific research is mainly information published in scientific journals. They are the basis for the dissemination of knowledge and the basic criteria for academic and scientific evaluation, fundraising for scientific research and career advancement. In addition to the evaluation of scientific publications, there is a wide range of other activities that reflect the scientific credibility of scientists, such as: number and quality of grants for scientific research projects, leadership in national or international academic societies, membership in editorial boards of reputable journals, doctoral dissertation mentorships and the like. Although these activities are important and give credibility to the scientist, the relevant scientometric systems cover only publications, neglecting other criteria of scientific importance in evaluation for purpose of academic advancement of a scientist, as well as competitions for grants for financial support of scientific research. The reason for this is the fact that these activities, regardless of their importance, are very heterogeneous, with specific characteristics, and require very diverse parameters for evaluation. Therefore, there are no universal evaluation criteria for these activities and their quality is generally assessed individually, depending on the purpose of the assessment. Regardless of the shortcomings, university ranking systems are important comparative parameters for assessing the quality of scientific and educational value of universities.

Društveni značaj i kvalitet naučnog istraživanja u velikoj mjeri ovise o korisnosti rezultata istraživanja za društvenu i naučnu zajednicu. Nedostatak sredstava i želja da se sredstva dodijele visokokvalitetnim istraživanjima čine sve značajnijim procjenu kvaliteta istraživanja i valorizaciju znanja. Međutim, vrlo je teško primijeniti kriterije koji mogu objektivno procijeniti naučna istraživanja, pružajući precizne kvalitativne i kvantitativne podatke na kojima bi agencije za finansiranje mogle temeljiti svoje odluke. Proizvod naučnog istraživanja uglavnom su informacije objavljene u naučnim časopisima. One su temelj širenja znanja i osnovni kriterij za akademsku i naučnu evaluaciju, regrutovanje sredstava za naučna istraživanja i napredovanje u karijeri. Pored evaluacije naučnih publikacija, postoji širok spektar drugih aktivnosti koji odražavaju naučni kredibilitet znanstvenika, kao što su: broj i kvalitet grantova za naučnoistraživačke projekte, liderstvo u nacionalnim ili međunarodnim akademskim društvima, članstvo u redakcijama uglednih časopisa, mentorstva u doktorskim disertacijama i slično. Mada su te aktivnosti važne i daju kredibilitet znanstveniku, relevantni scientimetrijski sistemi pokrivaju samo publikacije, izostavljajući druge kriterije od naučne važnosti, u ocjenjivanju prilikom akademskog napredovanja znanstvenika, kao i konkursima za dobijanje grantova za finansijsku potporu naučnim istraživanjima. Razlog tome je činjenica da su ove aktivnosti, bez obzira na važnost, vrlo heterogene, sa specifičnim karakteristikama i zahtijevaju veoma raznolike parametre za ocjenu. Stoga, za ove aktivnosti ne postoje univerzalni kriterijumi vrednovanja i njihov se kvalitet, uglavnom, procjenjuje individualno, ovisno o namjeni procjene. Bez obzira na manjkavosti, sistemi rangiranja univerziteta su važni komparativni parametri za procjenu kvaliteta naučne i edukativne vrijednosti univerziteta.

Iterative methods are widely used for solving sparse linear systems of equations and eigenvalue problems. Their performances are relevant to the conditioning of the linear systems. This work explores factors which affects the conditioning of the discretized system, including material heterogeneity, different constitutive characteristics and element sizes, and reveals the dependencies among solvers performance and the conditioning of linear systems. Results show that multiple materials can alter the eigenvalue distributions significantly, while lowering Young’s modulus results in higher condition numbers but has less effects on the spectral scope, additionally, there is a approximately reciprocal square linear relation between element size and condition numbers. These entangled effects along with the chosen pre-conditioners render that there is no simple monotonic increasing dependency among condition numbers and solving time, except with specific conditions. It is hoped that this work will provide more understanding of the iterative sparse linear solver behavior used in similar structural problems.