Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation of soluble amyloid‐β precursor protein assays as diagnostic CSF biomarkers for neurodegenerative diseases

Analytical validation of a biomarker assay is essential before implementation in clinical practice can occur. In this study, we analytically validated the performance of assays detecting soluble amyloid‐β precursor protein (sAPP) α and β in CSF in two laboratories according to previously standard operating procedures serving this goal. sAPPα and sAPPβ ELISA assays from two vendors (IBL‐international, Meso Scale Diagnostics) were validated. The performance parameters included precision, sensitivity, dilutional linearity, recovery, and parallelism. Inter‐laboratory variation, biomarker comparison (sAPPα vs. sAPPβ) and clinical performance was determined in three laboratories using 60 samples of patients with subjective memory complaints, Alzheimer's disease, or frontotemporal dementia. All performance parameters of the assays were similar between labs and within predefined acceptance criteria. The only exceptions were minor out‐of‐range results for recovery at low concentrations and, despite being within predefined acceptance criteria, non‐comparability of the results for evaluation of the dilutional linearity and hook‐effect. Based on the inter‐laboratory correlation between Lab #1 and Lab #2, the IBL‐international assays were more robust (sAPPα: r2 = 0.92, sAPPβ: r2 = 0.94) than the Meso Scale Diagnostics (MSD) assay (sAPPα: r2 = 0.70, sAPPβ: r2 = 0.80). Specificity of assays was confirmed using assay‐specific peptide competitors. Clinical validation showed consistent results across the clinical groups in the different laboratories for all assays. The validated sAPP assays appear to be of sufficient technical quality and perform well. Moreover, the study shows that the newly developed standard operating procedures provide highly useful tools for the validation of new biomarker assays. A recommendation was made for renewed instructions to evaluate the dilutional linearity and hook‐effect.
Discriminant functions and decision tree induction techniques for antenatal fetal risk assessment

This study concentrates on the comparison of the discriminant functions and the decision tree induction techniques in antepartum fetal evaluation. These classification techniques are applied to antenatal fetal risk assessment problem and the performances, the computational complexities and the importance of each technique in terms of diagnostic clues are observed. The task is to investigate the Doppler ultrasound measurements of umbilical artery (UA) to relate the health conditions of fetuses using discriminant functions such as linear discriminant functions (LDF), multilayer perceptron (MLP), decision trees (C4.5, CART) and neural trees. We use the following UA blood flow velocity waveforms: pulsatility index (PI), resistance index (RI) and systolic/diastolic ratio (S/D) in terms of weeks (week index: WI as a normalized value) to decide if there is any hypoxia suspicion. It is observed that the performances of MLP and CART are better but C4.5 defines understandable diagnostic clues. On the other hand, the time complexity of LDF and C4.5 are become favorable. Experiments support that C4.5, MLP, CART and neural trees are favorable medical aids to physicians during intensive surveillance of fetuses. With the limited number of indices, we obtain a specificity and sensitivity of 100% and 93% with these decision techniques.
Brain Stem Response Evoked by Electrical Stimulation of the round Window of the Guinea Pig

The wave that is believed to correspond to wave V in man is an appropriate indicator of auditory nerve excitability because it is not contaminated by nonauditory neurogenic responses to electrical stimulation. The responses to direct electrical stimulation of the auditory nerve could be distinguished from the electrophonic response by the steep input-output function and constant latency of the former. Myogenic responses are prominent unless a muscle relaxant is administered.
Habits without Values

Habits form a crucial component of behavior. In recent years, key computational models have conceptualized habits as arising from model-free reinforcement learning (RL) mechanisms, which typically select between available actions based on the future value expected to result from each. Traditionally, however, habits have been understood as behaviors that can be triggered directly by a stimulus, without requiring the animal to evaluate expected outcomes. Here, we develop a computational model instantiating this traditional view, in which habits develop through the direct strengthening of recently taken actions rather than through the encoding of outcomes. We demonstrate that this model accounts for key behavioral manifestations of habits, including insensitivity to outcome devaluation and contingency degradation, as well as the effects of reinforcement schedule on the rate of habit formation. The model also explains the prevalent observation of perseveration in repeated-choice tasks as an additional behavioral manifestation of the habit system. We suggest that mapping habitual behaviors onto value-free mechanisms provides a parsimonious account of existing behavioral and neural data. This mapping may provide a new foundation for building robust and comprehensive models of the interaction of habits with other, more goal-directed types of behaviors and help to better guide research into the neural mechanisms underlying control of instrumental behavior more generally.
Probabilistic non-negative tensor factorization using Markov chain Monte Carlo

We present a probabilistic model for learning non-negative tensor factorizations (NTF), in which the tensor factors are latent variables associated with each data dimension. The non-negativity constraint for the latent factors is handled by choosing priors with support on the non-negative numbers. Two Bayesian inference procedures based on Markov chain Monte Carlo sampling are described: Gibbs sampling and Hamiltonian Markov chain Monte Carlo. We evaluate the model on two food science data sets, and show that the probabilistic NTF model leads to better predictions and avoids overfitting compared to existing NTF approaches.
Quality of Life and Subjective Well-Being

Abstract There is a propensity in the social work profession to base programmatic theories on knowledge derived from other disciplines. A term that has found wide acceptance in the profession of social work is the concept of quality of life (QOL). Over the last two decades QOL has emerged as an organizing framework for assessing health indices within the medical and mental health fields. In relation to QOL, there is a need for a comprehensive understanding of the concept in order to ascertain its congruence with, and potential shaping of, the values and ethos of the profession. The paper gives a clear and straightforward introduction to a range of work. The main objective is to examine the individual work of certain researchers and thinkers in their independent search for the methods of measuring subjective states. A review of these separate efforts will reveal an internal coherence and overlap of work that is responsible for the way QOL is presently conceptualized.
Differential capacity of left and right hemispheric areas for compensation of poststroke aphasia

As previous functional neuroimaging studies could not settle the controversy regarding the contribution of dominant and subdominant hemisphere to recovery from poststroke aphasia, language performance was related to H215O‐positron emission tomographic activation patterns in 23 right‐handed aphasic patients 2 and 8 weeks after stroke. In patients classified according to the site of lesion (frontal, n = 7; subcortical, n = 9; temporal, n = 7) and in 11 control subjects, flow changes caused by a word repetition task were calculated in 14 regions representing eloquent and contralateral homotopic areas. These areas were defined on coregistered magnetic resonance imaging scans and tested for significance (Bonferroni corrected t test, α = 0.0036). At baseline, differences in test performance were only found between the subcortical and temporal group. The extent of recovery, however, differed and was reflected in the activation. The subcortical and frontal groups improved substantially; they activated the right inferior frontal gyrus and the right superior temporal gyrus (STG) at baseline and regained left STG activation at follow‐up. The temporal group improved only in word comprehension; it activated the left Broca area and supplementary motor areas at baseline and the precentral gyrus bilaterally as well as the right STG at follow‐up, but could not reactivate the left STG. These differential activation patterns suggest a hierarchy within the language‐related network regarding effectiveness for improvement of aphasia; ie, right hemispheric areas contribute, if left hemispheric regions are destroyed. Efficient restoration of language is usually only achieved if left temporal areas are preserved and can be reintegrated into the functional network. Ann Neurol 1999;45:430–438
Construction of a space of motion labels from their mapping to full-body motion symbols

Language is an indispensable for humanoid robot to be integrated into daily life. This paper proposes a novel approach to construct a space of motion labels from their mapping to human whole body motions. The motions are abstracted by Hidden Markov Models, which are referred to as motion symbols. The human motions are automatically partitioned into motion segments, and recognized as sequences of the motion symbols. Sequences of motion labels are also assigned to these motions. The referential relationship between the motion symbols and the motion labels is extracted by stochastic translation model, and distances among the labels are calculated from the association probability of the motion symbols being generated by the labels. The labels are located in a multidimensional space so that the distances are satisfied, and it results in a label space. The label space encapsulates relations among the motion labels such as their similarities. The label space also allows motion recognition. The validity of the constructed label space is demonstrated on a motion capture data-set. Graphical Abstract
Induction and persistence of radiation-induced DNA damage is more pronounced in young animals than in old animals

Younger individuals are more prone to develop cancer upon ionizing radiation (IR) exposure. Radiation-induced tumors are associated with inefficient repair of IR-induced DNA damage and genome instability. Phosphorylation of histone H2AX (γ-H2AX) is the initial event in repair of IR-induced DNA damage on the chromatin flanking the DNA strand breaks. This step is crucially important for the repair of DNA strand breaks and for the maintenance of genome stability. We studied the molecular underpinnings of the age-related IR effects using an animal model. By assaying for IR-induced γ-H2AX foci we analyzed the induction and repair of the DNA strand breaks in spleen, thymus, liver, lung, kidney, cerebellum, hippocampus, frontal cortex and olfactory bulb of 7, 14, 24, 30 and 45 days old male and female mice as a function of age. We demonstrate that tissues of younger animals are much more susceptible to IR-induced DNA damage. Younger animals exhibited higher levels of γ-H2AX formation which partially correlated with cellular proliferation and expression of DNA repair proteins. Induction and persistence of γ-H2AX foci was the highest in lymphoid organs (thymus and spleen) of 7 and 14 day old mice. The lowest focal induction was seen in lung and brain of young animals. The mechanisms of cell and tissue-specificity of in vivo IR responses need to be further dissected. This study provides a roadmap for the future analyses of DNA damage and repair induction in young individuals.
Toward a Synthetic Evaluation of the Attention Distribution Ability of Drivers

In order to evaluate the Attention Distribution Ability (ADA) of drivers in a more reliable and applicable way, a synthetic evaluation structure which is composed of multiple indices is developed. 12 male subjects participated in the simulated driving tasks which are designed for ADA evaluation. To evaluate the ADA of the subjects, the performance data (such as the tracking deviation) and the workload data (such as the NASA TLX score) are collected. By employing the Entropy Weight Method and the Experts Grading Method, the multiple indices which are extracted from the experiment data are synthesized, the ADA of the 12 subjects is evaluated. By using the methods we propose, the 12 subjects can be divided into different groups by their ADA scores. The testing tasks and the methods we propose exhibit satisfying sensitivity and applicability in the ADA evaluation.
Machine-vision based preceding vehicle detection algorithm: A review

Onboard vehicle detection system is of great importance to reduce vehicle collision accident and increase the driving safety on road. It aims at detecting vehicles appearing around the ego vehicle using vehicle-mounted camera, so as to alert the driver about driving environments and possible collision with other vehicles. In this paper, we analyze the detail difficulties lying in the problem and review most of the literatures. A typical vehicle detection algorithm includes two steps: hypothesis generation and hypothesis verification. After a vehicle is detected, it's tracked. This paper introduces the principle of typical methods of detection and tracking and analyzes their respective pros and cons. Finally, we propose some research directions in the future.
Social Work Research in Practice: Lessons Learned

ABSTRACT Using data and research to drive and evaluate clinical decision-making continues to slowly gain prominence across social work settings. This article shares insights and recommendations from a novice social work investigator to encourage other social workers to consider the value of researching while in practice. Practitioners new to research need encouragement and support. This article provides ideas for easing the first steps towards research to avoid potentially discouraging pitfalls.
Beacon based indoor positioning system using weighted centroid localization approach

There has been an upward trend in the requirement of indoor positioning systems using bluetooth low energy (BLE), Wi-Fi, and visible light communication. In order to realize the indoor positioning with these communication systems, techniques such as fingerprinting, trilateration, and triangulation have been widely studied. Even though fingerprinting has been chosen as a representative approach in many literatures, it is known as tedious and time consuming method due to the long-time location learning phase. Therefore, the fingerprinting is expected to be integrated with other methods to enhance the location accuracy and reduce the location estimation procedures. In this work, we discuss one of these methods used for indoor positioning, i.e., weighted centroid localization (WCL) using received signal strength indicator (RSSI) observed from neighboring BLE beacons. The WCL is evaluated in our testbed building and analyzed to configure its parameters for indoor positioning.
Transmission power control in MAC protocols for wireless sensor networks

Medium access control (MAC) protocols manage energy consumption on the network element during communication, which is the most energy-consuming event on Wireless Sensor Networks (WSNs). One method to mitigate energy consumption is to adjust transmission power. This paper presents two approaches to adjust transmission power in WSNs. The first approach employs dynamic adjustments by exchange of information among nodes, and the second one calculates the ideal transmission power according to signal attenuation in the link. The proposed algorithms were implemented and evaluated with experiments, comparing their results with B-MAC, the standard MAC protocol in the Mica Motes 2 platform. Results show that transmission power control is an effective method to decrease energy consumption, and incurs in a negligible loss in packet delivery rates. For node distances of 5m, the proposed transmission power control techniques decrease energy consumption by 27% over B-MAC.
Technological Transfers, Limited Commitment and Growth

This paper examines the effect on economic growth and welfare of the access to external financing which results in technological transfers to a developing country from the rest of the world. We consider a two-sector stochastic growth model and compute optimal accumulation mechanisms in the environments which differ in the extent to which the borrowing contracts are enforced. Furthermore, we examine different assumptions concerning the default punishment and their implications for growth, welfare and borrowing patterns. We show that under limited commitment lack of technological transfers may result in scarce capital flows to developing countries and substantially reduce their growth opportunities. Presence of technological transfers in this environment induces a developing country to use foreign capital to both smooth consumption and invest more heavily in all the sectors of the economy including those unaffected by the productivity benefits. Our findings suggest that technological transfers may play a role of an important enforcement mechanism. In addition, our model can account for the rich structure of observed capital flows to low- and middle income countries
A Femtomolar Acting Octapeptide Interacts with Tubulin and Protects Astrocytes against Zinc Intoxication*

An octapeptide was previously described that protects neurons against a wide variety of insults directly and indirectly as a result of interactions (at femtomolar concentrations) with supporting glial cells. The current study set out to identify the octapeptide binding molecules so as to understand the high affinity mechanisms of cellular protection. Studies utilizing affinity chromatography of brain extracts identified tubulin, the brain major protein, as the octapeptide-binding ligand. Dot blot analysis with pure tubulin and the biotinylated octapeptide verified this finding. When added to cerebral cortical astrocytes, the octapeptide (10-15–10-10 m) induced a rapid microtubule reorganization into distinct microtubular structures that were stained by monoclonal tubulin antibodies and visualized by confocal microscopy. Fluorescein-labeled octapeptide induced a similar change and was detected in the intracellular milieu, even when cells were incubated at 4 °C or at low pH. In a cell-free system, the octapeptide stimulated tubulin assembly into microtubules. Furthermore, treatment of astrocytes with zinc chloride resulted in microtubule disassembly and cell death that was protected by the octapeptide. In conclusion, the results suggest that the octapeptide crosses the plasma membrane and interacts directly with tubulin, the microtubule subunit, to induce microtubule reorganization and improved survival. Because microtubules are the key component of the neuronal and glial cytoskeleton that regulates cell division, differentiation, and protection, this finding may explain the breadth and efficiency of the cellular protective capacities of the octapeptide.
Context-Aware Mobile Collaborative Systems: Conceptual Modeling and Case Study

A Mobile Collaborative System (MCOS) enable the cooperation of the members of a team to achieve a common goal by using a combination of mobile and fixed technologies. MCOS can be enhanced if the context of the group of users is considered in the execution of activities. This paper proposes a novel model for Context-Aware Mobile COllaborative Systems (CAMCOS) and a functional architecture based on that model. In order to validate both the model and the architecture, a prototype system in the tourism domain was implemented and evaluated.
Multi-robot active sensing of non-stationary gaussian process-based environmental phenomena

A key challenge of environmental sensing and monitoring is that of sensing, modeling, and predicting large-scale, spatially correlated environmental phenomena, especially when they are unknown and non-stationary. This paper presents a decentralized multi-robot active sensing (DEC-MAS) algorithm that can efficiently coordinate the exploration of multiple robots to gather the most informative observations for predicting an unknown, non-stationary phenomenon. By modeling the phenomenon using a Dirichlet process mixture of Gaussian processes (DPM-GPs), our work here is novel in demonstrating how DPM-GPs and its structural properties can be exploited to (a) formalize an active sensing criterion that trades off between gathering the most informative observations for estimating the unknown, non-stationary spatial correlation structure vs. that for predicting the phenomenon given the current, imprecise estimate of the correlation structure, and (b) support efficient decentralized coordination. We also provide a theoretical performance guarantee for DEC-MAS and analyze its time complexity. We empirically demonstrate using two real-world datasets that DEC-MAS outperforms state-of-the-art MAS algorithms.
Simple and Reliable Method to Quantify the Hepatitis B Viral Load and Replicative Capacity in Liver Tissue and Blood Leukocytes

Background A functional cure of chronic hepatitis B (CHB) is feasible, but a clear view of the intrahepatic viral dynamics in each patient is needed. Intrahepatic covalently closed circular DNA (cccDNA) is the stable form of the viral genome in infected cells, and represents the ideal marker of parenchymal colonization. Its relationships with easily accessible peripheral parameters need to be elucidated in order to avoid invasive procedures in patients. Objectives The goal of this study was to design, set up, and validate a reliable and straightforward method for the quantification of the cccDNA and total DNA of the hepatitis B virus (HBV) in a variety of clinical samples. Patients and Methods Clinical samples from a cohort of CHB patients, including liver biopsies in some, were collected for the analysis of intracellular HBV molecular markers using novel molecular assays. Results A plasmid construct, including sequences from the HBV genome and from the human gene hTERT, was generated as an isomolar multi-standard for HBV quantitation and normalization to the cellular contents. The specificity of the real-time assay for the cccDNA was assessed using Dane particles isolated on a density gradient. A comparison of liver tissue from 6 untreated and 6 treated patients showed that the treatment deeply reduced the replicative capacity (total DNA/cccDNA), but had limited impact on the parenchymal colonization. The peripheral blood mononuclear cells (PBMCs) and granulocytes from the treated and untreated patients were also analyzed. Conclusions A straightforward method for the quantification of intracellular HBV molecular parameters in clinical samples was developed and validated. The widespread use of such versatile assays could better define the prognosis of CHB, and allow a more rational approach to time-limited tailored treatment strategies.