Miracle-dz/UniFAR-FTUs huggingface dataset:
Preoperative characteristics and functional outcomes of lower limb amputees treated at Southern Älvsborg Hospital, Sweden

Background: Within the prosthetics profession, there is a lack of evidence to support many clinical practices. It is therefore important that clinicians systematically document and evaluate their daily practices. Objectives: To record preoperative characteristics and functional outcomes for patients with a lower limb amputation and to investigate variations between prosthetic users and non-prosthetic users. Study Design: Prospective cohort study. Methods: A total of 23 patients (mean age = 80 years, standard deviation = 7.3) who underwent a major lower limb amputation were assessed within 2 weeks of admission and 6 months post-operatively. Locomotor Capabilities Index-5, the Timed-Up-and-Go Test and prosthetic use were used to evaluate functional outcomes. Results: A total of 13 participants (57%) received a prosthesis within 6 months of amputation. Mean time to prosthetic fitting was 48 days (range = 28–97). No statistically significant difference was found between prosthetic users and non-prosthetic users regarding age, time to rehabilitation and Locomotor Capabilities Index-5 (p > 0.05). Locomotor Capabilities Index-5 basic was significantly lower at 6 months than prior to amputation (p = 0.039). Conclusion: The functional outcome at 6 months indicates a sizable restriction in mobility among lower limb amputees. No variation in preoperative characteristics between prosthetic users and non-prosthetic users could be confirmed in this study. Clinical relevance This study highlights the need for prosthetists to better incorporate research findings into their daily practice and presents an example of how to implement a procedure for assessment and documentation of patients’ functional outcomes in a clinical setting. Results confirm difficulties in identifying amputees who will become prosthetic users based on preoperative characteristics.
Taxonomic position of Hormaphis similibetulae Qiao & Zhang, 2004 (Hemiptera, Aphididae): molecular and biological evidences

Abstract The taxonomic position of Hormaphis similibetulae Qiao & Zhang, 2004 has been reexamined. The phylogenetic position of Hormaphis similibetulae was inferred by maximum parsimony, maximum likelihood and Bayesian analyses on the basis of partial nuclear elongation factor-1α and mitochondrial tRNA leucine/cytochrome oxidase II sequences. The results showed that this species fell into the clade of Hamamelistes species, occupying a basal position, and was clearly distinct from other Hormaphis species. A closer relationship between Hormaphis similibetulae and Hamamelistes species was also revealed by life cycle analysis. Therefore, we conclude that Hormaphis similibetulae should be transferred to the genus Hamamelistes as Hamamelistes similibetulae (Qiao & Zhang), comb. n.
Techniques for Conditioning Bit-Stream Signals for Single-Phase Power Electronics Applications

Bitstream-based control, which uses one-bit-wide signals to control power electronics applications, is a new approach for controller design. Bit-Stream signals can be directly applied to control electronic devices, but the high-frequency nature of bitstream signals can lead to excessive switching losses. Thus, it is essential to downsample bitstream signals to reduce switching losses to acceptable levels. This paper presents a novel modulator, which downsamples high-frequency bitstreams to low-frequency switching signals that are suitable for driving two-level half-bridge or three-level full-bridge inverters. Methods for compensating for switch dead time and balancing switching losses of the inverter legs are presented, and the performance of the proposed modulators are compared to the standard pulse width modulation strategies. Simulation and experimental results of a 2-kW single-phase inverter show that the proposed bitstream modulators consume fewer logic resources, produce spread-spectrum output currents, and can deliver lower total harmonic distortion than similar fixed-frequency pulse width modulators.
A complex consisting of pp 60 c " src / pp 60 csrcN and a 38 kDa protein is highly enriched in growth cones from differentiated SH-SY 5 Y neuroblastoma cells

Nerve growth cones of primary neurons are highly enriched in the proto-oncogene product pp^'TM. In order to investigate this molecule further in growing neuronal cells, growth cone and cell body fractions were prepared from human SH-SY5Y neuroblastoma cells differentiated neuronally in vitro under the influence of phorbol ester. The fractions were characterized ultrastructurally and by biochemical criteria. The neuronal (pp^^) and the fibroblastic (pp^-*TM) forms of pp60 are slightly enriched and activated in the growth cones relative to the perikarya. Immunoprecipitates of ppeO"TM from differentiated SH-SY5Y growth cones contain at least four phosphoproteins in addition to pp60. One of these, pp38, migrates as a 100-140 kDa complex with pp60 under non-reducing conditions of gel electrophoresis. The pp38/pp60 complex is not easily detected in non-differentiated SH-SY5Y cells or perikarya of differentiated SH-SY5Y cells, but it is highly enriched in the growth cone preparation. These data suggest that growth-cone pp60 exists in a disulfide-linked oligomeric complex. The complex appears to be assembled only in the cell periphery and may be dependent upon neuronal differentiation.
Bayesian multivariate augmented Beta rectangular regression models for patient-reported outcomes and survival data

Many longitudinal studies (e.g. observational studies and randomized clinical trials) have collected multiple rating scales at each visit in the form of patient-reported outcomes (PROs) in the close unit interval [0,1]. We propose a joint modeling framework to address the issues from the following data features: (1) multiple correlated PROs; (2) the presence of the boundary values of zeros and ones; (3) extreme outliers and heavy tails; (4) the PRO-dependent terminal events such as death and dropout. Our modeling framework consists of a multivariate augmented mixed-effects sub-model based on Beta rectangular distributions for the multiple longitudinal outcomes and a Cox model for the terminal events. The simulation studies suggest that in the presence of outliers, heavy tails, and dependent terminal event, our proposed models provide more accurate parameter estimates than the joint model based on Beta distributions. The proposed models are applied to the motivating Long-term Study-1 (LS-1 study, n = 1741) of Parkinson’s disease patients.
A data-driven online ADP of exponential convergence based on k-nearest-neighbor Averager, stable term and persistence excitation

With the development of marine science, aeronautics and astronautics, energy, chemical industry, biomedicine and management science, many complex systems face the problem of optimization and control. Approximate dynamic programming solves the curse of dimensionality problem of dynamic programming, and it is a new kind of approximate optimization solution that emerges in recent years. Based on the analysis of optimization system, this paper proposes a nonlinear multi-input multi-output, online learning, and data-driven approximate dynamic programming structure and its learning algorithm. The method is achieved from the following three aspects: 1) the critic function of multi-dimensional input critic module of the approximate dynamic programming is approximated with a data-driven k-nearest neighbor method; 2) the multi-output policy iteration of the approximate dynamic programming actor module is calculated with an exponential convergence performance; 3) The critic and actor modules are learned synchronously, and achieve the online optimal and control effect. The optimal control for the longitudinal motion of a thermal underwater glider is used to show the effect of the proposed method. This work can lay a foundation for the theory and application of a nonlinear data-driven multi-input multi-output approximate dynamic programming method. It's also the consensus needs in optimization control and artificial intelligence of many scientific and engineering fields, such as energy conservation, emission reduction, decision support and operational management etc.
Interpretable modelling with sparse kernels

A drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is difficult to interpret. The principal focus of this thesis is the development of advanced non-linear interpretable models. Interpretable modelling offers us a powerful tool with which to understand the structure of a model constructed from data, allowing model validation and assisting in model selection. Gibbs (1997) observes the easiest way to introduce model interpretability is to use models where the parameters and the related hyperparameters have clearly interpretable meanings. The Bayesian methodology of Automatic Relevance Determination (ARD) (MacKay, 1994; Neal, 1995) is one such approach. In this thesis Laplace approximations, variational learning and Markov Chain Monte Carlo (MCMC) methods for hyperparameter determination are assessed within a Bayesian neural network. Empirical results highlight the numerical instability of the Laplace and variational methods with convergence to a local rather than global minima. Kernel methods have become a popular modelling approach (Vapnik, 1998; Smola, 1998; Williams, 1998). In this thesis the constructed kernel models are equipped with hyperparameters that allow: the ability to select important input variables, the ability to visualise the model structure and the ability to incorporate prior or expert knowledge. Ideas from the Bayesian and the signal processing communities together with the representational advantage of a sparse ANOVA decomposition have been merged. Interpretability is introduced by using two forms of regularisation: a 1-norm based structural regulariser to enforce interpretability, and a 2-norm based regulariser to control smoothness. The model structure can be visualised showing the overall effects of different inputs, their interactions, and the strength of the interactions. The performance of these interpretable learning algorithms is demonstrated on both synthetic and “real” data, notably the AMPG dataset, the Boston house price dataset, and the problem of predicting the mechanical property proof stress of a metal based on its chemical composition. Results from these different approaches are compared in terms of their interpretabilty by exploiting prior knowledge of the problem, and show the potential of interpretable data models.
C-erbB-2 immunostaining: problems with interpretation.

AIMS--To assess the consistency and reproducibility of assessment of c-erbB-2 immunostaining, and to examine some of the problems relating to inter- and intraobserver variability in the documentation of positive staining; to profile the spectrum of cytoplasmic and membranous staining in a wide range of tumour types. METHODS--A total of 283 neoplasms were examined for immunohistochemical expression of the c-erbB-2 oncoprotein. Three independent observers were required to assess intensity both of membrane and cytoplasmic staining on a three point and then a four point scale. Extent of positive staining was also assessed on a two point scale. A minimum of two weeks elapsed between assessments using the differing scales. RESULTS--Positive membrane staining was documented by one or more observers in 16.6% of tumours examined. This positivity was largely restricted to bladder, renal, and breast tumours. The overall level of disagreement as to the presence or absence of membranous staining was 11.3%. Cytoplasmic staining was identified in 55.5% of tumours studied. The level of disagreement as to the presence or absence of cytoplasmic staining was 26.5%. CONCLUSIONS--Intraobserver variability was minimal, indicating that each pathologist was adhering to internal reproducible standards. Interobserver variability was greater, indicating that the interpretation of c-erbB-2 immunostaining may require set guidelines. It is suggested that assessment should be referenced to a standard positive control, that a three tier system for grading of intensity and a two tier system for grading of extent should be adopted, and that the evaluation should be agreed by at least two pathologists. The presence of cytoplasmic staining should continue to be routinely recorded until its biological role and clinical implications are fully understood.
Design and Evaluation of an Integrated Online Motion Control Training Package

The aim of this paper is to present an integrated Internet-based package for teaching the fundamentals of motion control by using a wide range of resources: theory, videos, simulators, games, quizzes, and a remote lab. The package is aimed at automation technicians, pupils at vocational schools and students taking an introductory course in automatic control, and was designed to complement traditional teaching methods and not as a substitute for them. The scope of this package was also chosen to complement the control engineering curriculum. The evaluation data collected from the users suggest that this strategy gave very good results and raised the interest of learners.
2-Butoxyethanol Female-Rat Model of Hemolysis and Disseminated Thrombosis: X-Ray Characterization of Osteonecrosis and Growth-Plate Suppression

We recently proposed a chemically induced rat model for human hemolytic disorders associated with thrombosis. The objective of the present investigation was to apply a noninvasive, high-magnification X-ray analysis, the Faxitron radiography system, to characterize the protracted bone damage associated with this 2-butoxyethanol model and to validate it by histopathology. Groups of female Fischer 344 rats were given 0, 250, or 300 mg of 2-butoxyethanol/kg body weight daily for 4 consecutive days. Groups were then sacrificed 2 hours or 26 days after the final treatment. The treated animals displayed a darkened purple-red discoloration on the distal tail. Histopathological evaluation, including phosphotungstic acid-hematoxylin staining of animals sacrificed 2 hours after the final treatment, revealed disseminated thrombosis and infarction in multiple organs, including bones. The Faxitron MX-20 specimen radiography system was used to image selected bones of rats sacrificed 26 days posttreatment. Premature thinning of the growth plate occurred in the calcaneus, lumbar and coccygeal vertebrae, femur, and ilium of the treated animals. Areas of decreased radiographic densities were seen in the diaphysis of the femur of all treated animals. The bones were then examined histologically and showed a range of changes, including loss or damage to growth plates and necrosis of cortical bone. No thrombi were seen in the animals sacrificed at 30 days, but bone and growth plate changes consistent with prior ischemia were noted. The Faxitron proved to be an excellent noninvasive tool that can be used in future studies with this animal model to examine treatment modalities for the chronic effects of human thrombotic disorders.
When age matters: Developmental perspectives on “cognition and emotion”

Even though the study of cognition emotion links is a relatively young field, some findings seem so well-established that they are rarely questioned. For example, researchers interested in cognition emotion links are unlikely to dispute the existence of negativity dominance; that is, the notion that negatively valenced stimuli are more potent in eliciting perceptual and cognitive responses than are positive ones (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001; Rozin & Royzman, 2001). Theoretical accounts of negativity dominance are typically framed in evolutionary terms: Negative information dominates the cognitive system relative to positive information because it signals threats or obstacles to goal attainment and can hence be potentially relevant for ensuring survival. Positive information is less potent in eliciting cognitive responses because there is no positive counterpart that is as potent as avoiding death. It is therefore widely assumed that negativity dominance is universal. This assumption is frequently used as the starting point for generating further hypotheses about the processing of emotional information (e.g., Morewedge, 2009; Rozin, Berman, & Royzman, 2010). In light of all this, it may be surprising that a prominent theme in recent studies on cognition emotion links in older adults refers not to negativity dominance but instead to ‘‘positivity effects’’ in information processing. How can this be? Are the ‘‘laws’’ of the psychological study of emotion’s influence on cognition not so universal after all? This is the guiding question of this special section, which specifically focuses on the role of age as a potential moderator of cognition emotion links. The search for potential moderators of cognition emotion links is not new to readers of Cognition and Emotion. In recent issues, for example, stimulus-level moderators such as featural distinctiveness (Calvo & Marrero, 2009), as well as person-level moderators such as social phobia (Kolassa et al., 2009), alexithymia (Vermeulen, Luminet, de Sousa, & Campanella, 2008) and trait anxiety (Fales, Becerril, Luking, & Barch, 2010) have been considered as factors that could influence the extent to which emotion and cognition are interrelated. The role that people’s
Evaluation of delirium in critically ill patients: Validation of the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU)

ObjectiveTo develop and validate an instrument for use in the intensive care unit to accurately diagnose delirium in critically ill patients who are often nonverbal because of mechanical ventilation. DesignProspective cohort study. SettingThe adult medical and coronary intensive care units of a tertiary care, university-based medical center. PatientsThirty-eight patients admitted to the intensive care units. Measurements and Main Results We designed and tested a modified version of the Confusion Assessment Method for use in intensive care unit patients and called it the CAM-ICU. Daily ratings from intensive care unit admission to hospital discharge by two study nurses and an intensivist who used the CAM-ICU were compared against the reference standard, a delirium expert who used delirium criteria from the Diagnostic and Statistical Manual of Mental Disorders (fourth edition). A total of 293 daily, paired evaluations were completed, with reference standard diagnoses of delirium in 42% and coma in 27% of all observations. To include only interactive patient evaluations and avoid repeat-observer bias for patients studied on multiple days, we used only the first-alert or lethargic comparison evaluation in each patient. Thirty-three of 38 patients (87%) developed delirium during their intensive care unit stay, mean duration of 4.2 ± 1.7 days. Excluding evaluations of comatose patients because of lack of characteristic delirium features, the two critical care study nurses and intensivist demonstrated high interrater reliability for their CAM-ICU ratings with kappa statistics of 0.84, 0.79, and 0.95, respectively (p < .001). The two nurses’ and intensivist’s sensitivities when using the CAM-ICU compared with the reference standard were 95%, 96%, and 100%, respectively, whereas their specificities were 93%, 93%, and 89%, respectively. ConclusionsThe CAM-ICU demonstrated excellent reliability and validity when used by nurses and physicians to identify delirium in intensive care unit patients. The CAM-ICU may be a useful instrument for both clinical and research purposes to monitor delirium in this challenging patient population.
Anomalous settlement behavior of Ulva linza zoospores on cationic oligopeptide surfaces

Identification of settlement cues for marine fouling organisms opens up new strategies and methods for biofouling prevention, and enables the development of more effective antifouling materials. To this end, the settlement behaviour of zoospores of the green alga Ulva linza onto cationic oligopeptide self-assembled monolayers (SAMs) has been investigated. The spores interact strongly with lysine- and arginine-rich SAMs, and their settlement appears to be stimulated by these surfaces. Of particular interest is an arginine-rich oligopeptide, which is effective in attracting spores to the surface, but in a way which leaves a large fraction of the settled spores attached to the surface in an anomalous fashion. These ‘pseudo-settled’ spores are relatively easily detached from the surface and do not undergo the full range of cellular responses associated with normal commitment to settlement. This is a hitherto undocumented mode of settlement, and surface dilution of the arginine-rich peptide with a neutral triglycine peptide demonstrates that both normal and anomalous settlement is proportional to the surface density of the arginine-rich peptide. The settlement experiments are complemented with physical studies of the oligopeptide SAMs, before and after extended immersion in artificial seawater, using infrared spectroscopy, null ellipsometry and contact angle measurements.
Formal Hierarchical Model of Security of the Upper Level of Instrumentation & Control System of a Nuclear Power Plant

Abstract The present paper considers a formal hierarchical model of the cybersecurity policy of the digital upper unit level system of (UULS) of the nuclear power plant (NPP). The relations and transfer of the access rights between the subjects and objects of the model are analyzed. The standard NPP UULS is characterized by way of example of the UULS developed at the Trapeznikov Institute of Control Sciences (Russian Academy of Sciences) for the NPP's and of its simplified cybersecurity model.