Miracle-dz/UniFAR-FTUs huggingface dataset:
Editorial

In part 2 of this special issue we continue our series of papers from the celebration events for the centenary of the Tavistock Clinic. Exploring the theme of inequalities, the first paper in this issue is entitled ‘Pandemic: challenges in care and recovery’ by Dinesh Sinha. It has long been known that economic disadvantage is linked to higher rates of mortality and poorer access to healthcare (Black, 1982). More recent evidence has suggested that industrialised societies with the greatest income differentials (such as the UK and USA) have the poorest health and social development (Wilkinson & Pickett, 2009). The COVID-19 pandemic, which delayed the Tavistock centenary celebrations, has highlighted once again the inequalities in health within our society. Using the lens of everyday sadism, Sinha identifies corrosive and deliberate counter narratives to the themes of care and courage in this period. He describes how the pre-existing silos of separation between the privileged and dispossessed have prevented survival and wellbeing in the wider society. He cautions health and social care workers about the possible lapse into masochism and bravery as defences against exhaustion and the guilt of having survived when thousands of our colleagues have not. He highlights the need for awareness of our own feelings of guilt and aggression, so that they do not vitiate our capacity to care. Sinha suggests that the process of recovering from the pandemic is not just about the restoration of physical wellbeing but also the creation of healthier conditions in society that actively mitigate the scourge of everyday sadism. The next paper, ‘Under fire in the consulting room’ by Carine Minne, describes her work with patients at the Portman Clinic. The clinic traces its history back to 1933, when the ‘Psychopathic Clinic’ was founded by Edward Glover at the West End Hospital for Nervous Diseases. It was established as the clinical arm of the Institute for the Study and Treatment of Delinquency (ISTD), earlier founded in 1931 as the Institute for the Scientific Treatment of Delinquency. The Institute had been inspired by the work of Dr. Grace Pailthorpe, a psychiatrist and psychoanalyst, who worked in Birmingham and Holloway Prisons. There, she became interested in the personality of women prisoners and in 1932 published Studies in the Psychology of Delinquency. In her article Minne uses clinical vignettes with patients such as a woman who was convicted of infanticide. She illustrates situations when the therapist realised there was a sudden unexpected rise in the ‘temperature’ of a patient’s mind. She likens this to the ignition of a fuse and discusses why this may have Psychoanalytic Psychotherapy, 2022 Vol. 36, No. 1, 1–3, http://dx.doi. org/10.1080/02668734.2022. 2049064
Analytics of human presence and movement behaviour within specific environments

The vast amounts of detailed information, generated by Wi-Fi and other mobile communication technologies, provide an invaluable opportunity to study different aspects of presence and movement behaviours of people within a given environment; for example, a university campus, an organisation office complex, or a city centre. Utilising such data, this thesis studies three main aspects of the human presence and movement behaviours: spatio-temporal movement (where and when do people move), user identification (how to uniquely identify people from their presence and movement historical records), and social grouping (how do people interact). Previous research works have predominantly studied two out of these three aspects, at most. Conversely, we investigate all three aspects in order to develop a coherent view of the human presence and movement behaviour within selected environments. More specifically, we create stochastic models for movement prediction and user identification. We also devise a set of clustering models for the detection of the social groups within a given environment. The thesis makes the following contributions: 1. Proposes a family of predictive models that allows for inference of locations though a collaborative mechanism which does not require the profiling of individual users. These prediction models utilise suffix trees as their core underlying data structure, where predictions about a specific individual are computed over an aggregate model incorporating the collective record of observed behaviours of multiple users. 2. Defines a mobility fingerprint as a profile constructed from the users historical mobility traces. The proposed method for constructing such a profile is a principled and scalable implementation of a variable length Markov model based on n-grams. 3. Proposes density-based clustering methods that discover social groups by analysing activity traces of mobile users as they move around, from one location to another, within an observed environment.
Development of Alveolar Hemorrhage After Pfizer-BioNTech COVID-19 mRNA Vaccination in a Patient With Renal-Limited Anti-neutrophil Cytoplasmic Antibody-Associated Vasculitis: A Case Report

Since the coronavirus disease 2019 (COVID-19) pandemic continues and a new variant of the virus has emerged, the COVID-19 vaccination campaign has progressed. Rare but severe adverse outcomes of COVID-19 vaccination such as anaphylaxis and myocarditis have begun to be noticed. Of note, several cases of new-onset antineutrophil cytoplasmic antibody-associated vasculitis (AAV) after COVID-19 mRNA vaccination have been reported. However, relapse of AAV in remission has not been recognized enough as an adverse outcome of COVID-19 vaccination. We report, to our knowledge, a first case of renal-limited AAV in remission using every 6-month rituximab administration that relapsed with pulmonary hemorrhage, but not glomerulonephritis, following the first dose of the Pfizer-BioNTech COVID-19 vaccine. The patient received the COVID-19 vaccine more than 6 months after the last dose of rituximab according to the recommendations. However, his CD19+ B cell counts were found to be increased after admission, indicating that our case might have been prone to relapse after COVID-19 vaccination. Although our case cannot establish causality between AAV relapse and COVID-19 mRNA vaccination, a high level of clinical vigilance for relapse of AAV especially in patients undergoing rituximab maintenance therapy following COVID-19 vaccination should be maintained. Furthermore, elapsed time between rituximab administration and COVID-19 mRNA vaccination should be carefully adjusted based on AAV disease-activity.
Differential Impact of the Khatanga and Lena (Laptev Sea) Runoff on the Distribution and Grazing of Zooplankton

The ecosystems of the Arctic Ocean and their expected changes in a context of Global climate processes are crucially dependent on the freshwater input. The freshwater signal is assumed to be the main structuring factor for the marine fauna on the shallow shelf of the Siberian Arctic seas. The Laptev Sea, as a part of the world’s widest continental shelves surrounding the Arctic Ocean, is a key area for understanding the land–ocean interaction in high latitude regions. The largest freshwater input is provided by the deltaic Lena river followed by the estuarine Khatanga river. The plumes of these rivers differ considerably in their hydrophysical characteristics, suggesting differential impacts on ecosystems of the adjacent shelf. The key component of pelagic ecosystems is zooplankton, which transfers energy from primary producers to higher trophic levels and modifies sedimentations processes. This study is focused on the influence of river discharge on zooplankton in the Laptev Sea at the end of productive season. We studied zooplankton biomass, species composition, distribution patterns of the dominant species and assessed herbivorous feeding rates and grazing pressure of these species along a transect from the inner Khatanga Gulf northward to the continental slope, and a transect in the Lena plume influenced area in August-September 2017. Despite large spatial extension of the Khatanga plume, the impact of river discharge on zooplankton species composition was restricted mainly to the inner Gulf where the brackish species shaped the community. Contrary to the Khatanga input, the Lena freshwater inflow was highly variable and under certain conditions (discharge rate, wind forcing) governed the structure of zooplankton community over a vast shelf area. Distribution patterns of zooplankton biomass, ingestion rates and grazing impact of the dominant species on phytoplankton over the shelf influenced by the Khatanga and Lena plumes were similar. Analysis of our results on demographic structure of Calanus glacialis suggests that seasonal development of the population was largely controlled by the time of ice retreat. Observed climatic changes in the Arctic were not reflected in the total zooplankton biomass and composition of the dominant species.
Diagnosis of Subcortical Ischemic Vascular Cognitive Impairment With No Dementia Using Radiomics of Cerebral Cortex and Subcortical Nuclei in High-Resolution T1-Weighted MR Imaging

Purpose To investigate whether the combination of radiomics derived from brain high-resolution T1-weighted imaging and automatic machine learning could diagnose subcortical ischemic vascular cognitive impairment with no dementia (SIVCIND) accurately. Methods A total of 116 right-handed participants involving 40 SIVCIND patients and 76 gender-, age-, and educational experience-matched normal controls (NM) were recruited. A total of 7,106 quantitative features from the bilateral thalamus, hippocampus, globus pallidus, amygdala, nucleus accumbens, putamen, caudate nucleus, and 148 areas of the cerebral cortex were automatically calculated from each subject. Six methods including least absolute shrinkage and selection operator (LASSO) were utilized to lessen the redundancy of features. Three supervised machine learning approaches of logistic regression (LR), random forest (RF), and support vector machine (SVM) employing 5-fold cross-validation were used to train and establish diagnosis models, and 10 times 10-fold cross-validation was used to evaluate the generalization performance of each model. Correlation analysis was performed between the optimal features and the neuropsychological scores of the SIVCIND patients. Results Thirteen features from the right amygdala, right hippocampus, left caudate nucleus, left putamen, left thalamus, and bilateral nucleus accumbens were included in the optimal subset. Among all the three models, the RF produced the highest diagnostic performance with an area under the receiver operator characteristic curve (AUC) of 0.990 and an accuracy of 0.948. According to the correlation analysis, the radiomics features of the right amygdala, left caudate nucleus, left putamen, and left thalamus were found to be significantly correlated with the neuropsychological scores of the SIVCIND patients. Conclusions The combination of radiomics derived from brain high-resolution T1-weighted imaging and machine learning could diagnose SIVCIND accurately and automatically. The optimal radiomics features are mostly located in the right amygdala, left caudate nucleus, left putamen, and left thalamus, which might be new biomarkers of SIVCIND.
Combining Genome-Wide Association Study and Gene-Based Haplotype Analysis to Identify Candidate Genes for Alkali Tolerance at the Germination Stage in Rice

Salinity–alkalinity stress is one of the main abiotic factors limiting rice production worldwide. With the widespread use of rice direct seeding technology, it has become increasingly important to improve the tolerance to salinity–alkalinity of rice varieties at the germination stage. Although we have a more comprehensive understanding of salt tolerance in rice, the genetic basis of alkali tolerance in rice is still poorly understood. In this study, we measured seven germination-related traits under alkali stress and control conditions using 428 diverse rice accessions. The alkali tolerance levels of rice germplasms varied considerably during germination. Xian/indica accessions had generally higher tolerance to alkali stress than Geng/japonica accessions at the germination stage. Using genome-wide association analysis, 90 loci were identified as significantly associated with alkali tolerance. Eight genes (LOC_Os01g12000, LOC_Os03g60240, LOC_Os03g08960, LOC_Os04g41410, LOC_Os09g25060, LOC_Os11g35350, LOC_Os12g09350, and LOC_Os12g13300) were selected as important candidate genes for alkali tolerance based on the gene functional annotation and gene-CDS-haplotype analysis. According to the expression levels of LOC_Os09g25060 (OsWRKY76), it is likely to play a negative regulatory role in alkali tolerance during rice germination. An effective strategy for improving rice alkali tolerance may be to pyramid alkali-tolerant haplotypes of multiple candidate genes to obtain the optimal haplotype combination. Our findings may provide valuable genetic information and expand the use of alkali tolerance germplasm resources in rice molecular breeding to improve the alkali tolerance at the germination stage.
Unexpected Intraspecific Variability of Perennial Ryegrass (Lolium perenne L.) in Response to Constant Temperature During Germination and Initial Heterotrophic Growth

Lolium perenne (L.) is one of the most important species in temperate grasslands. Temperature is a major factor controlling plant development. Breeding L. perenne cultivars adapted to new ranges of temperature could be necessary under most climate change scenarios. However, before any breeding effort in such direction, knowing the intraspecific variability of responses to temperature is essential. Our objective was to analyze a sample of accessions of L. perenne for their response to constant temperature during germination and initial heterotrophic growth. Eight accessions were taken out from a genebank containing 160 accessions. Six accessions were wild populations collected in different places in France and the other two were populations from a selection program. For germination, four replicates of 100 seeds per accession were tested in Petri dishes in the dark at eight constant temperatures, from 5 to 40°C with increases of 5°C. Germination countings were carried out at variable time intervals and durations that depended on treatments. For initial heterotrophic growth analysis, seeds were germinated at 25°C. Sets of 30 seedlings per accession were placed in polypropylene boxes on blotter blue paper and transferred to each one of the eight treatments in the dark. They were pictured at variable time intervals for root and shoot growth measurement by image analysis. Neither seed germination nor heterotrophic growth was observed at 40°C, for any accession. Temperature and time course response surfaces were markedly different between accessions. Equally, maximum germinability and the shape of the response curves to temperature were significantly different between accessions. This means that limited similarities between responses were observed. Furthermore, germination rates followed the non-linear beta function with significant differences between some accessions. These also showed significant differences in their root and shoot growth rate in response to temperature. In general, the relative growth rates of roots and shoots were slow at 5°C, peaked between 25 and 30°C, and showed a sharp reduction afterward. These results reveal, for the first time, high genetic variability within L. perenne germplasm for the response to temperature in the initial life phases. This discovered variability should serve breeders to create perennial ryegrass varieties for the future.
Nanotechnology in Kidney and Islet Transplantation: An Ongoing, Promising Field

Organ transplantation has evolved rapidly in recent years as a reliable option for patients with end-stage organ failure. However, organ shortage, surgical risks, acute and chronic rejection reactions and long-term immunosuppressive drug applications and their inevitable side effects remain extremely challenging problems. The application of nanotechnology in medicine has proven highly successful and has unique advantages for diagnosing and treating diseases compared to conventional methods. The combination of nanotechnology and transplantation brings a new direction of thinking to transplantation medicine. In this article, we provide an overview of the application and progress of nanotechnology in kidney and islet transplantation, including nanotechnology for renal pre-transplantation preservation, artificial biological islets, organ imaging and drug delivery.
Experimental Investigation on BN-Based Flexible Composite Phase-Change Material for Battery Module

This study aims toward the application of composite phase-change material (CPCM) in electric vehicles, which suffers from leakage, high rigidity, and low thermal conductivity. In this study, a novel flexible composite phase-change material (CPCM) with high thermal conductivity and low leakage has been proposed, presented, and utilized in a battery module. Among these, polyethylene glycol (PEG), as a phase-change component, styrene–butadiene–styrene (SBS) as support material, and ethylene–propylene–diene monomer (EPDM) as assisted packaging material could greatly enhance the flexibility and deformability of CPCM. Besides, boron nitride (BN) was adopted to enhance the heat-dissipating capacity and reduce the temperature difference in the module. In addition, compared with other cooling methods, the battery module with compact and efficient advantages are analyzed at different discharge rates. The results revealed that the flexible CPCM was controlled below 44.8°C, and the temperature difference was maintained within 5.6°C at 3C discharge rate. Even during the charge–discharge cycles, it displayed lower temperature fluctuation within the acceptable range. These outstanding shape recovery and antileakage performances of BN-based flexible CPCM would provide insights into battery modules with desirable assembly methods and process flexibility.
Vision Aided Inertial Navigation

Camera measurements can be used to replace or supplement gps measurements for aiding inertial navigation systems. This is especially useful in cases where gps is unavailable or unreliable, whether it is because the signals are blocked by the environment or intentionally corrupted. In this thesis a system is developed for aiding inertial navigation by a simple vision system consisting of a single camera, and computer simulations are done to test its performance. The system is represented as a state space model which is used in an extended Kalman lter to estimate the navigation states. The system model is created by relating the acceleration and angular velocity to the rate of change of the orientation, velocity and position of a vehicle and to the relative position of a stationary landmark, which is represented by a pinhole camera projection. Noise values used for simulating inertial sensor noise are calculated based on speci cations obtained from a user manual. The state space model is based on considering the inertial measurements as control inputs, directly a ecting the states, whle the camera and gps measurements are outputs of the system. An extended Kalman lter is then implemented, which uses measured inputs and outputs to estimate the state based on a linearized model. Simulations are done which show that the system works as intended and is able to restrain the drift in position from the inertial navigation. Monte Carlo simulations show that the best results are achieved when the vehicle swings from side to side as it approaches the landmark, however the lter has problems estimating the standard deviations correctly. Suggested further work includes using more landmarks and replacing the extended Kalman lter with an unscented lter.
Freezing of Gait in Multiple System Atrophy

Background and Purpose Freezing of gait (FOG) is a common gait disturbance phenomenon in multiple system atrophy (MSA) patients. The current investigation assessed the incidence FOG in a cross-sectional clinical study, and clinical correlations associated with it. Methods Ninety-nine MSA patients from three hospitals in China were consecutively enrolled in the study. Eight patients were subsequently excluded from the analysis due to incomplete information. The prevalence of FOG symptoms in the MSA cohort was determined, and clinical manifestations in MSA patients with and without FOG were assessed. Results Of 91 MSA patients, 60 (65.93%) exhibited FOG. The incidence of FOG increased with disease duration and motor severity and was correlated with modified Hoehn and Yahr (H-Y) stages [odds ratio (OR), 0.54; 95% confidence interval (CI), 0.33–3.92], longer disease duration (OR, 0.54, 95% CI, 0.37–0.78), higher Unified Multiple System Atrophy Rating Scale (UMSARS) score (OR, 0.96, 95% CI, 0.93–0.99), MSA-cerebellum subtype (OR, 2.99, 95% CI, 1.22–7.33), levodopa-equivalent dose (LDED) (OR, 0.998, 95% CI, 0.997–1.00), and higher Scale for the Assessment and Rating of Ataxia (SARA) score (OR, 0.80, 95% CI, 0.72–0.89) (logistic regression). Motor dysfunction was significantly positively associated with lower quality of life scores (p < 0.01). Conclusion FOG is a common symptom in MSA patients and it is correlated with poor quality of life, disease progression and severity, levodopa-equivalent dose, and cerebellum impairment.
Predicting the Proliferation of Tongue Cancer With Artificial Intelligence in Contrast-Enhanced CT

Tongue squamous cell carcinoma (TSCC) is the most common oral malignancy. The proliferation status of tumor cells as indicated with the Ki-67 index has great impact on tumor microenvironment, therapeutic strategy making, and patients’ prognosis. However, the most commonly used method to obtain the proliferation status is through biopsy or surgical immunohistochemical staining. Noninvasive method before operation remains a challenge. Hence, in this study, we aimed to validate a novel method to predict the proliferation status of TSCC using contrast-enhanced CT (CECT) based on artificial intelligence (AI). CECT images of the lesion area from 179 TSCC patients were analyzed using a convolutional neural network (CNN). Patients were divided into a high proliferation status group and a low proliferation status group according to the Ki-67 index of patients with the median 20% as cutoff. The model was trained and then the test set was automatically classified. Results of the test set showed an accuracy of 65.38% and an AUC of 0.7172, suggesting that the majority of samples were classified correctly and the model was stable. Our study provided a possibility of predicting the proliferation status of TSCC using AI in CECT noninvasively before operation.