Miracle-dz/UniFAR-FTUs huggingface dataset:
Machine Learning Based Prediction of Squamous Cell Carcinoma in Ex Vivo Confocal Laser Scanning Microscopy

Simple Summary Squamous cell carcinoma is the second most common type of skin cancer, with incidence rates rising each year. Micrographic urgery is the treatment of choice for large, aggressive, or recurrent lesions. To ensure complete removal, excised tissue is frozen or embedded in paraffin, cut by a microtome, and stained for examination by an expert Mohs surgeon or a dermatopathologist. Thus, resection of tumor is performed in multiple steps, resulting in delayed wound closure, patient discomfort, longer hospital stay, and in turn, higher healthcare costs. In the last few years, ex vivo confocal laser scanning microscopy (CLSM) has shown promising results in intraoperative almost-real-time detection of skin cancers. This technology is not yet widespread in part due to necessity of training for laboratory technicians, surgeon and dermatopathologists. To increase efficiency and objectivity in the image interpretation process, we have built a machine learning model to detect squamous cell carcinoma lesions in excised tissues. Abstract Image classification with convolutional neural networks (CNN) offers an unprecedented opportunity to medical imaging. Regulatory agencies in the USA and Europe have already cleared numerous deep learning/machine learning based medical devices and algorithms. While the field of radiology is on the forefront of artificial intelligence (AI) revolution, conventional pathology, which commonly relies on examination of tissue samples on a glass slide, is falling behind in leveraging this technology. On the other hand, ex vivo confocal laser scanning microscopy (ex vivo CLSM), owing to its digital workflow features, has a high potential to benefit from integrating AI tools into the assessment and decision-making process. Aim of this work was to explore a preliminary application of CNN in digitally stained ex vivo CLSM images of cutaneous squamous cell carcinoma (cSCC) for automated detection of tumor tissue. Thirty-four freshly excised tissue samples were prospectively collected and examined immediately after resection. After the histologically confirmed ex vivo CLSM diagnosis, the tumor tissue was annotated for segmentation by experts, in order to train the MobileNet CNN. The model was then trained and evaluated using cross validation. The overall sensitivity and specificity of the deep neural network for detecting cSCC and tumor free areas on ex vivo CLSM slides compared to expert evaluation were 0.76 and 0.91, respectively. The area under the ROC curve was equal to 0.90 and the area under the precision-recall curve was 0.85. The results demonstrate a high potential of deep learning models to detect cSCC regions on digitally stained ex vivo CLSM slides and to distinguish them from tumor-free skin.
An estimation of exergy consumption paterns of energy‐intensive building service systems

Abstract This paper represents the estimation of life cycle exergy consumption for building service systems (BSS). The investigation explores public building engineering systems, which are the most energy‐intensive. These include heating, ventilating and lightning. The exergy consumption analysis is divided into three parts: systems production, operating and maintenance (O&M) and decommissioning. The differences between them consist in different exergy demand and consumption intensiveness. The main attention is paid to BSS O&M investigation by categorising and defining exergy demands within the building. Exergy consumption for BSS O&M period is estimated as certain amount of exergy that should be supplied to the buildings boundaries. In this investigation of building engineering systems, 4 typical buildings are explored for the Vilnius’ city conditions in Lithuania.
“You are Irish—and as Irish as Me!”: Antiracism and National Identities in Ireland

What is the role of national identities in doing antiracism? In social psychology, much research on racism has examined processes and practices of exclusion. Scant research however has examined practices of inclusion. In this paper, I examine practices of national majority group members doing antiracism in response to complaints by ethnic minority members about facing racism on Twitter about their national belonging. I examine these instances and responses to these in the Irish context, as in Ireland, being “Irish” can mean both ethnic and national identity. Findings show that respondents’ national identification was central to practices of inclusion, such as that of affirming the Irishness of those facing exclusion. For respondents’ national belonging was oriented to as significant for those complaining about inclusion, for themselves, and for those who were engaging in racist exclusion of ethnic minority members. Together the findings show that while national identities allow for antiracism, these problematically suppress the relevance of race in favor of nations and nationalisms.
Can Autism Be Diagnosed with Artificial Intelligence? A Narrative Review

Radiomics with deep learning models have become popular in computer-aided diagnosis and have outperformed human experts on many clinical tasks. Specifically, radiomic models based on artificial intelligence (AI) are using medical data (i.e., images, molecular data, clinical variables, etc.) for predicting clinical tasks such as autism spectrum disorder (ASD). In this review, we summarized and discussed the radiomic techniques used for ASD analysis. Currently, the limited radiomic work of ASD is related to the variation of morphological features of brain thickness that is different from texture analysis. These techniques are based on imaging shape features that can be used with predictive models for predicting ASD. This review explores the progress of ASD-based radiomics with a brief description of ASD and the current non-invasive technique used to classify between ASD and healthy control (HC) subjects. With AI, new radiomic models using the deep learning techniques will be also described. To consider the texture analysis with deep CNNs, more investigations are suggested to be integrated with additional validation steps on various MRI sites.
A new model for PV modules angular losses under field conditions

Motivated by the significance of optical losses in many photovoltaic (PV) applications, and by the lack of useful tools that allow easy angular performance calculations, this paper presents a new analytical model for reflection losses in PV modules. It is based on the theoretical analysis of the optical characteristics of different commercial PV modules and results in good agreement with the experimental data in all cases. With this new useful tool, optical losses of PV modules under field conditions can be now easily quantified, as it is shown with an example. A strong dependence of optical losses on PV module tilt angle has been obtained, which has special significance in such applications as PV integration in buildings.
Interdisciplinary Class Observation in Higher Education: Lessons Learned from the Professional Development Experience of Four Teachers

Peer observation of teaching has been adopted as a method to improve the quality of teaching. It involves observers providing descriptive feedback to their peers on learning and teaching practices. However, although extensively described in the literature in the education field, its use as a tool for development beyond teaching skills has not been explored deeply, nor the best practices described. Therefore, the objective of this study was to compare quantitative with qualitative peer observation, as well as to investigate the role of interdisciplinarity in the observation process. The present study results from experimental observation work carried out by four professors of higher education. Veterinary science, social work, pharmaceutical sciences, and education, the disciplinary areas of origin of the teachers, were the ecosystems in which the initial observation techniques were explored and applied, and the intention was to share good practices and pedagogical improvements through peer support. This study reports the experience of building an observation grid and its application, as well as the lessons learned during the observation experience. The aim was to evaluate whether the constructive criticism was focused on the pedagogical practices rather than on the content, which can be useful in understanding if the learning objectives are being attained, from the teacher’s point of view. As such, we employed and assessed peer observation as a constructive, developmental process for higher education teachers from different fields of knowledge. The study concludes that feedback by peers is essential for the development of professional practice in higher education teaching, with the experience of qualitative observation being a fundamental path for teacher self-reflection in the search for their own authenticity. It further supports the notion that interdisciplinary differences, methodologies, styles, contexts, and practices can be used in a constructive way to improve course content and delivery, and, ultimately, to reinforce good teaching.
Sediment Accretion and Total Organic Carbon Accumulation Among Different Mangrove Vegetation Communities in the Kamora Estuary of Mimika Regency, Papua, Indonesia

A sediment accretion and carbon accumulation study was carried out in Kamora Estuary, Mimika Regency, Papua Province, Indonesia, to determine the accretion rate and total organic carbon loading in the area as well their correlation with geographical setting and mangrove aerial root type. The sediment stake method was used to measure the elevation changes, whereas the sediment trap method was used to determine sediment accretion and total organic carbon accumulation. Three locations were selected, namely at upstream, middle and downstream the mangrove communities, with each location installed up to 500 m perpendicular to the riverbank. The elevation changes based on sediment stakes were 8.4–12.3 mm year-1. Sediment accretion based on sediment traps was 18.5–25.4 mm year-1 or 1.88–2.98 g cm-2 year-1, while the mean total organic carbon accumulation was 736.8 ±169 g m-2 year-1. The results are higher than those of similar studies in other regions, but they are consistent with other studies in Papua New Guinea. This study found that higher sediment accretion occurred at the riverbank compared with the interior area, while the elevation changes were greater in the upstream area. Higher relative density and higher basal area had a negative correlation with sediment accretion, but the number of roots had a positive correlation with sedimentation. The high sedimentation in the Kamora Estuary is resulting in the expansion of the mangrove forest at a rate of 3% year-1. Assisted mangrove colonization can be applied to expand the mangrove forest, especially considering the use of Rhizophora species, which this study found to be more effective at trapping sediment.
A new 3D CAP system

In this paper, we demonstrate that the original 3D carrierless AM/PM (CAP) waveforms are fairly sensitive to quantisation noise. An in-depth investigation to obtain new waveforms that are noise insensitive is presented. The paper also presents numerical studies of the new 3D CAP system under non-ideal scenarios with quantisation noise and NEXT over lossy UTP channels. A comparative study with conventional 2D CAP systems leads to the important conclusion that the new 3D CAP system increases overall system throughput by 50% with very little performance degradation.
The geometry of the ICRF-induced wave–SOL interaction. A multi-machine experimental review in view of the ITER operation

As part of ITPA-Integrated Operational Scenario activities, this contribution reviews recent experimental characterizations of radio-frequency (RF)-induced scrape-off layer (SOL) modifications of various tokamaks worldwide and of the LArge Plasma Device at UCLA. The phenomenology, as observed using a large variety of measurement techniques, is consistent with expectations from RF sheath rectification. Emphasis is then put on the complex three-dimensional (3D) spatial patterns of the RF–SOL interaction, in relation to the magnetic topology and the spatial distribution of RF currents over the metallic structures surrounding the RF wave launchers. Dependence on the local plasma parameters in the antenna vicinity is also briefly addressed. The final part discusses implications for future devices.
Electroacupuncture Ameliorates Depression-Like Behaviour in Rats by Enhancing Synaptic Plasticity via the GluN2B/CaMKII/CREB Signalling Pathway

Background Hippocampal synaptic plasticity during the pathological process of depression has received increasing attention. Hippocampal neuron atrophy and the reduction in synaptic density induced by chronic stress are important pathological mechanisms of depression. Electroacupuncture (EA) exerts beneficial effects on depression, but the mechanism is unclear. This study explored the effect of EA on synaptic plasticity and the potential mechanism. Methods Forty-eight SD rats were randomly divided into the control, chronic unpredictable mild stress (CUMS), EA, and fluoxetine (FLX) groups, and each group consisted of 12 rats. The sucrose preference test, open field test, and forced swimming test were used for the evaluation of depression-like behaviour, and Golgi and Nissl staining were used for the assessment of synaptic plasticity. Western blotting and immunofluorescence were conducted to detect proteins related to synaptic plasticity and to determine their effects on signalling pathways. Results We found that CUMS led to depression-like behaviours, including a reduced preference for sucrose, a prolonged immobility time, and reduced exploration activity. The dendritic spine densities and neuron numbers and the protein levels of MAP-2, PSD-95, and SYN were decreased in the hippocampi of rats with CUMS-induced depression, and these trends were reversed by EA. The molecular mechanism regulating this plasticity may involve the GluN2B/CaMKII/CREB signalling pathway. Conclusion These results suggest that EA can improve depression-like behaviour and hippocampal plasticity induced by CUMS, and the mechanism may be related to the GluN2B/CaMKII/CREB pathway.
Arabidopsis SUMO E3 Ligase SIZ1 Interacts with HDA6 and Negatively Regulates HDA6 Function during Flowering

The changes in histone acetylation mediated by histone deacetylases (HDAC) play a crucial role in plant development and response to environmental changes. Mammalian HDACs are regulated by post-translational modifications (PTM), such as phosphorylation, acetylation, ubiquitination and small ubiquitin-like modifier (SUMO) modification (SUMOylation), which affect enzymatic activity and transcriptional repression. Whether PTMs of plant HDACs alter their functions are largely unknown. In this study, we demonstrated that the Arabidopsis SUMO E3 ligase SAP AND MIZ1 DOMAIN-CONTAINING LIGASE1 (SIZ1) interacts with HISTONE DEACETYLASE 6 (HDA6) both in vitro and in vivo. Biochemical analyses indicated that HDA6 is not modified by SUMO1. Overexpression of HDA6 in siz1-3 background results in a decreased level of histone H3 acetylation, indicating that the activity of HDA6 is increased in siz1-3 plants. Chromatin immunoprecipitation (ChIP) assays showed that SIZ1 represses HDA6 binding to its target genes FLOWERING LOCUS C (FLC) and MADS AFFECTING FLOWERING 4 (MAF4), resulting in the upregulation of FLC and MAF4 by increasing the level of histone H3 acetylation. Together, these findings indicate that the Arabidopsis SUMO E3 ligase SIZ1 interacts with HDA6 and negatively regulates HDA6 function.
Modulation of Yield and Yield Attributes of Transplanted Aman Rice through Organic and Inorganic Fertilization in Terrace Soil

Rice production has increased almost doubled over the last decade in Bangladesh as a result of additional application of chemical fertilizers and high yielding varieties. Present experiment was undertaken for elucidating the combined effect of organic materials (OM) and nitrogen (N) fertilizer on yield contributing attributes and yield of transplanted aman ( T. aman) rice. Experiment was set in a factorial randomized complete block design (RCBD) with three replications. Five types of OMs viz. RS (rice straw), VC (vermicompost), RHB (rice husk biochar), CD (cowdung) and PM (poultry manure) considering two ton carbon per hectare and three level of N viz. N0, N100 and N150 kg ha-1 were used in this experiment. Findings revealed that among the five OMs; cowdung significantly improved the studied parameters. Besides 150 kg ha-1 dose of N has pronounced effect on the grain yield of T. aman rice. In general OMs alone cannot contribute to the maximum yield and yield contributing parameters. Maximum plant height (98.5cm), no of tillers (20), no of effective tillers (18), no of grains (145.0 g), no of filled grains (138), no of unfilled grains (7.0) per panicle, length of panicle (27.5 cm), 1000-seed weight (23.65g), straw yield (8.97 t ha-1), grain yield (5.41 t ha-1) and biological yield (14.34 t ha-1) was attributed by the mixed application of PM and N150 dose of nitrogen. While maximum harvest index (45.09%) was found in the plot received RS in combination of N150 treatment and its minimum value was recorded also solely in RS treated plot. Findings suggest that the use of PM along with 150 kg ha-1 N can render superior crop growth and yield of T. aman rice.
Belatacept Use after Kidney Transplantation and Its Effects on Risk of Infection and COVID-19 Vaccine Response

Introduction: Belatacept is a common immunosuppressive therapy used after kidney transplantation (KT) to avoid calcineurin-inhibitor (CNI) use and its related toxicities. It is unclear whether its use exposes KT recipients (KTx) to a greater risk of infection or a poorer response to vaccines. Areas covered: We reviewed PubMed and the Cochrane database. We then summarized the mechanisms and impacts of belatacept use on the risk of infection, particularly opportunistic, in two settings, i.e., de novo KTx and conversion from CNIs. We also focused on COVID-19 infection risk and response to SARS-CoV-2 vaccination in patients whose maintenance immunosuppression relies on belatacept. Expert opinion: When belatacept is used de novo, or after drug conversion the safety profile regarding the risk of infection remains good. However, there is an increased risk of opportunistic infections, mainly CMV disease and Pneumocystis pneumonia, particularly in those with a low eGFR, in older people, in those receiving steroid-based therapy, or those that have an early conversion from CNI to belatacept (i.e., <six months post-transplantation). Thus, we recommend, if possible, delaying conversion from CNI to belatacept until at least six months post-transplantation. Optimal timing seems to be eight months post-transplantation. In addition, KTx receiving belatacept respond poorly to SARS-CoV-2 vaccination.
Effects of Cold Decompression on Hemodynamic Function and Decompression Sickness Risk in a Dry Diving Rat Model

Background: Diving in cold water is thought to increase the risk of decompression sickness (DCS), especially if the diver is cold during decompression. In this study, we investigated hemodynamic function and DCS risk in an animal model, where cold decompression was followed by rewarming at the surface. Methods: Nine female Sprague Dawley rats had pressure-volume catheters inserted into their left heart ventricle and femoral artery before they were exposed to dry air dives in which their core temperature was normothermic during the bottom phase, cold (35°C) during decompression, and normothermic after the dive. Data from an earlier study were used as controls. The rats were compressed in air to 600kPa, maintained at pressure for 45min, and decompressed at 50kPa/min. Hemodynamic data were recorded before, during, and 60min after decompression. Venous gas bubbles were recorded in the right heart ventricle and pulmonary artery for 60min after the dive. Results and Conclusion: During decompression, cardiac output (CO), and stroke volume (SV) decreased equally in cold rats and controls. CO and SV were temporarily re-established at the surface, before falling again in the cold rats. There was no difference in post-dive venous bubble grades. However, as the post-dive fall in CO and SV could be a sign of gas emboli obstructing the pulmonary circulation, we cannot conclude whether the DCS risk was increased. More sensitive bubble detection methods are needed to elucidate this point.
Clarifying the concept of conscience in nurses’ ethical performance in Iran: a concept analysis study

Although conscience, as an ethical concept, has emerged widely in the field of nursing, its functional meaning and its effects on nurses' performance are not clear. Therefore, the present study aimed to analyze the concept of conscience in the context of Iranian nurses’ ethical performance. This study used a hybrid model including theoretical, fieldwork, and final analytic stages. In the theoretical phase, English and Persian articles published up to 2020 and indexed by scientific databases were analyzed. In the fieldwork phase, semi-structured in-depth interviews were conducted on nurse participants. The last two stages were jointly considered to draw the study’s conclusions. In the theoretical phase, conscience was considered as a context-dependent concept, an inner voice, and a criterion for distinguishing right from wrong. The fieldwork phase’ results were categorized into three themes: “perception of conscience”, “commands of conscience”, and “obedience to conscience. The final definition was reached by merging the theoretical and field stages. This article aimed at investigating the relevance of conscience to ethical practice in the nursing field. Findings show that conscience is an inner feeling or voice that plays a vital role in providing ethical care by nurses.
Trends of Major Foodborne Outbreaks in the European Union during the Years 2015–2019

The incidence of the most common foodborne outbreaks reported by the European Food Safety Authority and the European Centre for Disease Prevention and Control during the years 2015–2019 is described. Campylobacter spp. , Salmonella spp. , Listeria monocytogenes, and Yersinia enterocolitica are the investigated microorganisms, and symptomatology, food categories responsible for human disease, as well as some prevention measures are the most important information schedules supplied to the readers. Campylobacteriosis and salmonellosis are the most common zoonoses with a notification rate of 59.7 and 20.0 per 100,000 population, respectively, in the year 2019. Good hygienic practices both at farm and domestic level could prevent such infections. The highest number of deaths is reported for listeriosis, corresponding to 31 fatal events in the year 2019. Therefore, awareness of the hazards linked to L. monocytogenes is particularly recommended amongst high-risk groups. By contrast, most cases of yersiniosis are sporadic and the most important prophylactic measures include adequate sanitation in pork chain, personnel hygiene, and protection of water supplies.