Miracle-dz/UniFAR-FTUs huggingface dataset:
Mystery Case: Syndrome of bilateral basal ganglia lesions in uremic encephalopathy

A 38-year-old patient with chronic kidney disease on regular hemodialysis was investigated for complaints of headache and excessive drowsiness. Significant fluctuation of blood glucose levels (predominantly hyperglycemia) along with deranged creatinine levels was reported over the preceding week with no accompanying history of respiratory tract infection, fever, liver disease, hypoxia, or toxic fume exposure.1 Spot blood urea nitrogen, serum creatinine, sodium, potassium, and blood sugar levels were within normal range. Brain MRI revealed symmetrical T2/fluid-attenuated inversion recovery (FLAIR) hyperintense nonhemorrhagic bilateral basal ganglia lesions showing mild diffusion restriction (figure). Findings were attributed to a combined effect of uremic toxins and metabolic acidosis and a diagnosis of syndrome of bilateral basal ganglia lesions was made in a setting of uremic encephalopathy.2
Multimorbidity and neuroimaging biomarkers among cognitively normal persons

Objective: To assess the cross-sectional association between multimorbidity and imaging biomarkers of brain pathology in the population-based Mayo Clinic Study of Aging (MCSA). Methods: The study consisted of 1,449 MCSA participants who were cognitively normal at the time of MRI. A subset of the participants also had 11C-Pittsburgh compound B (n = 689) and 18fluorodeoxyglucose (n = 688) PET scans available. Information on multimorbidity (defined as ≥2 chronic conditions) in the 5 years prior to the first imaging study was captured from the medical record using ICD-9 codes for chronic conditions and the Rochester Epidemiology Project medical records linkage system. The cross-sectional association of multimorbidity and imaging biomarkers was examined using logistic and linear regression models. Results: Among 1,449 cognitively normal participants (mean age 79 years; 50.9% men), 85.4% had multimorbidity (≥2 chronic conditions). Multimorbidity and severe multimorbidity (≥4 chronic conditions) were associated with abnormal Alzheimer disease (AD) signature meta–region of interest (meta-ROI) 18F-FDG hypometabolism (odds ratio [OR] 2.03; 95% confidence interval [CI] 1.10–3.77 and OR 2.22; 95% CI 1.18–4.16, respectively), and with abnormal AD signature MRI cortical thickness (OR 1.53; 95% CI 1.09–2.16 and OR 1.76; 95% CI 1.24–2.51, respectively), but was not associated with amyloid accumulation. Conclusions: Multimorbidity was associated with brain pathology through mechanisms independent of amyloid deposition and such neuronal injury and pathology was present before any symptomatic evidence of cognitive impairment. Longitudinal follow-up will provide insights into potential causal associations of multimorbidity with changes in brain pathology.
Voltage-gated potassium channel antibodies

A radioimmunoassay (RIA) to detect antibodies against what was initially believed to be voltage-gated potassium channels (VGKC) in patients with neuromyotonia was established 20 years ago.1 The rationale for this test came from previous RIA assays that detected antibodies against acetylcholine receptors or voltage-gated calcium channels in which the antigens were labeled with 125I-specific neurotoxins and precipitated with patients' antibodies.1 It was soon clear that the results of the VGKC RIA were very different from those expected based on the achievements of the RIA for the antibodies associated with myasthenia gravis and the Lambert-Eaton syndrome. First, only a minority of patients with neuromyotonia, the initial disease target of the VGKC RIA, were positive. Second, high levels of VGKC antibodies were found in a subset of patients with nonparaneoplastic limbic encephalitis and good response to immunotherapy.2 Third, it was known by 2004 that low levels of VGKC antibodies occurred in 5% of subjects without neurologic disorders.2 However, no recommendations on the clinical value, if any, of these low-positive VGKC antibody levels were provided until a decade later.3,4 Finally, as the VGKC RIA test became more widely available, the type of clinical syndromes reportedly associated with these antibodies increased exponentially in both adults and children.3–5
Anwendung einer binären Verweiskettenmethode beim Aufbau von Listen / Use of a binary tree structure for processing files

Die in dieser Schrift beschriebene Methode beruht auf der Untersuchung und Auswertung bestimmter Bits, die den Namen der einzelnen Eintragungen entnommen werden. Diese Bits bestimmen die Anordnung der Eintragungen in der Verweiskette und sind daher maßgeblich für Suche und Listenerweiterung. Diese Methode bietet folgende Vorteile: Der Aufbau einer oder mehrerer Listen geht ohne zeitaufwendige Verschiebungen vor sich. Die Anzahl der nötigen Suchschritte ist klein. Wie in dieser Schrift gezeigt wird, weicht die mittlere Anzahl der nötigen Suchschritte, ausgedrückt als Funktion der mit Ν bezeichneten Anzahl der Eintragungen, nur wenig von log2N ab.
The Measurement of Balance Post-Stroke. Part 3: Instrumented Measurement Tools

Abstract The restoration of balance skills is an important aspect of stroke physiotherapy, but the lack of appropriate outcome measures has been identified as a factor hampering development of the evidence base. In recent years instrumented measurement tools such as those measuring postural sway have become popular for research and clinical use. A systematic review of ways to measure balance using instrumented measurement tools was undertaken. CINAHL, MEDLINE, and EMBASE databases were searched for tests which measured balance post-stroke and could be used in clinical settings. They were assessed for reliability, validity, sensitivity to change, suitability for use in clinical settings and with a wide range of stroke severity. Forty-three papers were identified. For clarity and ease of presentation, these were divided into tests of postural sway, weight distribution, and responses to external perturbations. All had some information about their psychometric properties but none had been comprehensively tested and none fulfilled the criteria for an outcome measure for stroke physiotherapy interventions. Platform measures of postural sway had limited reliability and validity as a measure of balance disability, while responses to external perturbations had been insufficiently tested. Measurement of weight distribution showed more promise however. Here, there was reasonable evidence of reliability and validity, the equipment was simple to use although it could be expensive and difficult to move, but simple 'low-tech' methods (for standing balance) have been suggested which merit further investigation.
Pediatric multiple sclerosis

Many disease-modifying therapies are currently available for adults with relapsing-remitting multiple sclerosis (MS) but none of them has been tested in pediatric MS in randomized placebo-controlled trials. At present, as suggested by observational studies and experts' guidelines, interferon-β and glatiramer acetate continue to be the standard first-line treatments for pediatric MS. Observational studies and some controlled unblinded trials have shown a positive effect of these meditations in reducing relapse rate and delaying disease progression, with an acceptable safety profile. The goal of this article is to provide an overview of current knowledge with regard to safety, tolerability, and efficacy of first-line treatment options for MS in the pediatric age group, with the aim of providing guidance for planning first-line treatment of MS in children and adolescents.
11β‐Hydroxysteroid dehydrogenase: implications for clinical medicine

Perhaps one of the most rewarding aspects of endocrinology is the ability to apply a basic science approach to a clinical problem and see it come to fruition. In the mid 1980s in Edinburgh we described a rare case of mineralocorticoid hypertension, the so-called syndrome of apparent mineralocorticoid excess (AME) (Edwards et al., 1985). Almost 10 years later the molecular basis for AME has been explained as a defect in the gene encoding 11 -hydroxysteroid dehydrogenase (11 -HSD), a microsomal enzyme responsible for the interconversion of active glucocorticoids, cortisol and corticosterone, to their hormonally inactive metabolites, cortisone and 11-dehydrocorticosterone. However, our further understanding of the pathogenesis of AME, and studies on the enzymology of 11 -HSD in the interim, have yielded considerable insight into the mechanisms of corticosteroid hormone action in normal physiology and in disease states.
The Intrinsic Organization of the Cochlear Nuclei in the Cat

In the cochlear nuclei nine different cell types are distinguished on the basis of Nissl preparations. Only three of these cell types are presented here. The large and small spherical cells are innervated from the ascending cochlear branches by means of typical bulbs of Held. The former cell group is apparently supplied only from the apical and middle part of the cochlea and projects bilaterally on the medial superior olive, while the latter group seems to be supplied from the entire cochlea and projects on the lateral superior olive on the same side. The octopus cells are innervated from the descending cochlear branches by means of small ring-shaped boutons. The axons of these cells run in the intermediate acoustic stria and terminate probably in the retroolivary and medial preolivary nuclei on both sides. The function of the three types of cells is discussed.
Online and Semi-Online Scheduling on capacitated Two-Parallel Machines

In this paper, we investigate the capacitated two-parallel machines scheduling problem, where one machine is only available for a special period of time after which it can no longer process any job while the other machine is continuously available. Our objective is to minimize the completion time of the machine which is continuously available. The offline version of the problem is equivalent to the minimization version of the Subset-Sum problem. We first show the lower bound of the online version is infinite. We also consider the semi-online version with known the total job processing time in advance, for which both lower bound and semi-online algorithms are given.
Heuristic and Exact Solution Method for Convex nonlinear Knapsack Problem

In this paper, we consider a class of convex nonlinear knapsack problems in which all decision variables are integer and the objective and knapsack functions are nonlinear. This generalized problem is characterized by positive marginal cost (PMC) and increasing marginal loss-cost ratio (IMLCR). By analyzing the structural properties of the problem, we develop an efficient heuristic and propose search and branching rules to improve the branch and bound method for solving exact solution. Numerical study is done for showing the effectiveness of the proposed heuristic and the modified branch and bound method.
Chained Reference Address Comparator - ein VLSI-Baustein für die Beobachtung der Kommunikation in speichergekoppelten Multi-Mikrocomputer-Systemen

Ein erster Schritt zur Verbesserung der Leistungsfähigkeit verteilter Systeme ist oft die Beobachtung oder Messung (engl.: das Monitoring) der in ihnen ablaufenden Kommunikationsvorgänge. In diesem Beitrag wird ein VLSI-Baustein vorgestellt, der die Beobachtung von Prozedurund Nachrichten-orientierten Kommunikationsvorgängen in speichergekoppelten Multi-Mikrocomputer-Systemen unterstützt. Dazu verfugt dieser Baustein über die Fähigkeit, den Zugriff von Prozessoren auf die im gemeinsamen Speicher allokierten Datenstrukturen zu verfolgen, über die die einzelnen Mikrocomputer eines Systems miteinander kommunizieren. Durch die Technik des programmgesteuerten geketteten Adreßvergleichs, bei dem die Referenzadressen automatisch aus Adreßelementen generiert werden, die der Baustein dynamisch vom Datenbus des beobachteten Systems liest, ist es dabei auch möglich, Strukturzugriffe auf dynamische Datenstrukturen zu verfolgen, die in speichergekoppelten Systemen eine wichtige Funktion bei der Implementierung von Kommunikationsfunktionen haben. Wegen seines direkten Anschlusses an den Prozessor-Adreß-/Datenbus ist der Baustein speziell auf den Intel Prozessor 8086 ausgerichtet.
Erzeugung realistisch wirkender Computergraphik auf vektoriellen Supercomputern

Strahlverfolgung ist ein Verfahren zur Errechnung realistisch wirkender Bilder, das es ermöglicht, in einfacher Weise verschiedene natürliche Lichteffekte zu simulieren. Der Nachteil dabei ist, daß es bei direkter Anwendung zu sehr hohen Rechenzeiten führt bzw. bei umfangreicheren Szenen außerhalb der Praktikabilität liegt. Es wird gezeigt, wie Supercomputer, die nach dem Vektorprinzip arbeiten, eingesetzt werden können, um diesen Nachteil zu vermindern.
Dental Trauma: Case-Scenario Protocol for Dentists

Dental Trauma: Case-Scenario Protocol for Dentists The prompt and appropriate management of traumatic dental injury is an important determinant of the prognosis of the involved tooth. The lack of knowledge of the appropriate handling sequence often has detrimental effect. Dental injuries can be classified by etiology, anatomy, pathology or therapeutic considerations with extrusion, intrusion and tooth avulsion being the most frequent types of dental trauma that we see in the dental office. The transport and care of the affected tooth, the prompt and adequate treatment in the dental office, as well as the proper follow up are imperative for a successful outcome of these incidents. The goal of present paper is to help develop a case-scenario protocol for dentists which can help deal with everyday teeth trauma in most appropriate way.
Telecoils: Issues and Relevancy

What a hearing aid user hears through a telecoil via inductive coupling is as important as what he or she hears via the microphone, yet many audiologists and the hearing aid industry in general have not put much time and energy into either the advancement of telecoil circuitry or the proper ﬁtting of the circuit. Coupling techniques for telephones as well as for assistive listening devices are discussed in this article. ANSI standard S3.22 (1996) is described and methods for telecoil evaluation are presented. The current status of telecoils for both telephone communication and as assistive listening system receivers is reviewed.
Wissensdarstellung und Kognitionsforschung

Dr. Christian Freksa studierte Computer Science an der University of California, Berkeley (Schwerpunkt: AI). Seit 1986 leitet er die Forschungsgruppe KI / Kognition im Arbeitsbereich Theoretische Informatik und Grundlagen der KI (Prof. Dr. W. Brauer) am Institut für Informatik der TU München. Arbeitsschwerpunkte: Wissensrepräsentationstheorie; Darstellung von unscharfem unpräzisem, unvollständigem und widersprüchlichem Wissen.
New Dynamic Multi-Objective Constrained Optimization Evolutionary Algorithm

For dynamic multi-objective constrained optimization problem (DMCOP), it is important to find a sufficient number of uniformly distributed and representative dynamic Pareto optimal solutions. In this paper, the time period of the DMCOP is first divided into several random subperiods. In each random subperiod, the DMCOP is approximately regarded as a static optimization problem by taking the time subperiod fixed. Then, in order to decrease the amount of computation and improve the effectiveness of the algorithm, the dynamic multi-objective constrained optimization problem is further transformed into a dynamic bi-objective constrained optimization problem based on the dynamic mean rank variance and dynamic mean density variance of the evolution population. The evolution operators and a self-check operator which can automatically checkout the change of time parameter are introduced to solve the optimization problem efficiently. And finally, a dynamic multi-objective constrained optimization evolutionary algorithm is proposed. Also, the convergence analysis for the proposed algorithm is given. The computer simulations are made on four dynamic multi-objective optimization test functions and the results demonstrate that the proposed algorithm can effectively track and find the varying Pareto optimal solutions or the varying Pareto fronts with the change of time.
Unüberwachte Adaption mit dem Kosinus-Klassifikator / Unsupervised Adaption with the Cosine Classifier

Neuronale Netze werden in jüngster Zeit in zunehmendem Maß als Alternative zu regelbasierten Systemen zur Lösung interpolativer oder klassifikatorischer Aufgabenstellungen der Informationsverarbeitung eingesetzt. Hervorragendes Merkmal dieses Verarbeitungsparadigmas ist seine inhärente Adaptionsfähigkeit, die eine mühelose Anpassung eines neuronalen Systems an wechselnde Anwendungsumgebungen erlaubt. Dieser Beitrag beschreibt eine Ausprägung dieser Modellklasse, den Kosinus-Klassifikator, der die Lösung von Klassifikationsaufgaben ohne direkte Überwachung des Adaptionsvorgangs erlaubt. Die Leistungsfähigkeit dieses Klassifikators wird durch die erzielten Simulationsergebnisse bei einer Aufgabenstellung aus dem Bereich der Handschrifterkennung untermauert.
Stochastic Multi-Objectives Supply Chain Optimization with Forecasting Partial Backordering Rate: A Novel Hybrid Method of Meta Goal Programming and Evolutionary Algorithms

This study proposes a model for a multi-objective, multi-buyer, multi-vendor, multi-product and multi-constraint supply chain. The buyers’ demand rates are stochastic variables with known probability distribution functions. The classical (R,Q) inventory control system is used to manage the inventories of all buyers where the lead times are production rate dependent. Shortage is permitted and is partially backordered where the partial back ordering rate is forecasted. The model is considered as a multi-objective integer nonlinear programming problem including cost, service level and lead time objectives and using a novel hybrid method, a hybrid of Meta Goal Programming (MGP) and Firefly Algorithm (FA) are solved. Numerical examples are given to illustrate the proposed method in the study. The results of the study are compared to other hybrid methods of Meta Goal Programming with other evolutionary algorithms such as Bees Algorithms (BA), Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA).
Simple Food Group Diversity as a Proxy Indicator for Iron and Vitamin A Status of Rural Primary School Children in Uganda

Children in resource poor settings are at a high risk of inadequate iron and vitamin A intake when diets lack diversity and are dominated by staple foods. Yet comparative information on diet quality among school children is scarce. The objective of the study was to assess the potential of simple food group diversity to serve as a proxy indicator of iron and vitamin A status among rural school children in Uganda. A cross sectional correlation model of associations between Food Group Diversity (FGD) and iron and vitamin A status was used. We analyzed 8 schools in Kumi District, Uganda, randomly selected from the 34 schools that participated in the main part of the study. Our sample included primary school children, aged between 9 - 15 years (n = 172). Food group diversity and food variety (FV) were calculated from both a food frequency questionnaire (FFQ) and a 24-hour dietary recall. The FGD and FVS were tested against iron (as serum ferritin) and vitamin A (as serum retinol) status. The FGD (based on FFQ data) was 9.6 (±1.9). There was a positive correlation between 24-hour recall and FFQ for consumption of cereals (Corr. Coef = 0.28; p < 0.05), which was also the most highly consumed group (98.9% & 86.9% by FFQ and 24-hour recall; respectively). Consistent with other studies, increase in the number of food groups significantly increased serum ferritin and serum retinol measures (p < 0.001). Presence of at least one food item in the “roots & tubers”; “cereals”; and “pulses/nuts”, significantly increased serum ferritin and serum retinol concentrations (p < 0.01). We speculate that simple food group diversity may reflect intake and serve as a simple indicator of iron and vitamin A status among school children. Strategies aimed at increasing dietary diversity in the community may benefit the families of these children and improve their micronutrient status.
A Combination of Fractal and Wavelet for Feature Extraction

In this paper, a novel approach to feature extraction with wavelet and fractal theories is presented as a powerful technique in pattern recognition. The motivation behind using fractal transformation is to develop a high-speed feature extraction technique. A multiresolution family of the wavelets is also used to compute information conserving micro-features. In this study, a new fractal feature is reported. We employed a central projection method to reduce the dimensionality of the original input pattern, and a wavelet transform technique to convert the derived pattern into a set of subpatterns, from which the fractal dimensions can readily be computed. The new feature is a measurement of the fractal dimension, which is an important characteristic that contains information about the geometrical structure. This new scheme includes utilizing the central projection transformation to describe the shape, the wavelet transformation to aid the boundary identification, and the fractal features to enhance image discrimination. The proposed method reduces the dimensionality of a 2-D pattern by way of a central projection approach, and thereafter, performs Daubechies' wavelet transform on the derived 1-D pattern to generate a set of wavelet transform subpatterns, namely, curves that are non-self-intersecting. Further from the resulting non-self-intersecting curves, the divider dimensions are computed with a modified box-counting approach. These divider dimensions constitute a new feature vector for the original 2-D pattern, defined over the curve's fractal dimensions. We have conducted several experiments in which a set of printed Chinese characters, English letters of varying fonts and other images were classified. Based on the formulation of our new feature vector, the experiments have satisfying results.
MCE-Based Face Recognition

This paper proposes a complete procedure for the extraction and recognition of human faces in complex scenes. The morphology-based face detection algorithm can locate multiple faces oriented in any direction. The recognition algorithm is based on the minimum classification error (MCE) criterion. In our work, the minimum classification error formulation is incorporated into a multilayer perceptron neural network. Experimental results show that our system is robust to noisy images and complex background.
Image Restoration: The Wavelet-Based Approach

Wavelet-based techniques are suitable for recovering a signal corrupted by noise. The time- and frequency-localization capabilities of wavelets provide better noise reduction and less signal distortion than conventional filtering methods. The noise reduction technique used in this paper is based on the hidden Markov model (HMM) structure, which can efficiently shape the statistical characteristics of practical data. As confirmed by numerical results, the HMM based approach provides a significant performance improvement over competing methods.
Document Gray-Scale Reduction Using a Neuro-Fuzzy Technique

This paper proposes a new neuro-fuzzy technique suitable for binarization and gray-scale reduction of digital documents. The proposed approach uses both the image gray-scales and additional local spatial features. Both, gray-scales and local feature values feed a Kohonen Self-Organized Feature Map (SOFM) neural network classifier. After training, the neurons of the output competition layer of the SOFM define two bilevel classes. Using the content of these classes, fuzzy membership functions are obtained that are next used by the fuzzy C-means (FCM) algorithm in order to reduce the character-blurring problem. The method is suitable for improving blurring and badly illuminated documents and can be easily modified to accommodate any type of spatial characteristics.