Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Aging, Psychotic Symptoms, Medication, and Brain-Derived Neurotrophic Factor on Cognitive Impairment in Japanese Chronic Schizophrenia Patients

Background: Cognitive impairment in schizophrenia can result in considerable difficulty in performing functions of daily life or social rehabilitation. Cognitive impairment in schizophrenia is related to various factors, such as the psychotic severity, aging, medication, and brain-derived neurotrophic factor (BDNF). To date, however, no studies investigating the impact of these factors on cognitive functioning in chronic schizophrenia patients have been performed. Objective: The aim of this study is to identify those factors that influence the cognitive functioning in patients with chronic schizophrenia. Methods: Sixty-five of 116 long-term hospitalized chronic schizophrenia patients (63.8 ± 12.1 years old, M/F = 29/36) were enrolled this cross-sectional study. We investigated the relationship among the patients' age, psychotic severity, treatment medication, serum BDNF levels, and cognitive functioning (measured by the Japanese-language version of the Brief Assessment of Cognition in Schizophrenia; BACS-J). Additionally, we performed a multivariable linear regression analysis. Results: According to the partial correlation analysis, certain parameters [i.e., age, chlorpromazine (CP) equivalent, biperiden (BP) equivalent, and serum BDNF] were significantly correlated with cognitive functioning, including working memory (WM), motor function (MF), attention and processing speed (AP), and executive function (EF). For the multivariate analysis, the MF component, which had the highest correlation, was selected as the dependent variable, and the independent variables included age, Manchester Scale for chronic psychosis (ManS) total score, CP equivalent, BP equivalent, serum BDNF, estimated full scale IQ, and years of education. According to the multiple regression analysis of this model, R (multiple regression coefficient) was 0.542, the adjusted R2 (coefficient of determination) was 0.201, and only BP equivalent (β = −0.305, p = 0.030), but not age, ManS score, CP equivalent, or serum BDNF, could significantly explain MF at the 5% significant level. Conclusion: In conclusion, aging, medication (administering more antipsychotics or anticholinergics), and serum BDNF concentration are significantly correlated with cognitive dysfunction in chronic schizophrenia patients but not with the severity of psychotic symptoms. Furthermore, only the anticholinergic dosage had a significant causal relationship with MF. Thus, the use of anticholinergics in chronic schizophrenia patients with deteriorating cognitive functioning must be reconsidered.
Direct medical costs of COPD diagnosis and treatment, Eastern vs Western European country – examples of Serbia and Belgium

OBJECTIVE: Comparison of COPD financial burden and underlying factors, between Eastern upper middle income and a Western European high income, healthcare settings. METHODS: The patient sample was 433 in Belgium and 322 in Serbia, age ≥ 40, with spirometry and clinically confirmed COPD diagnosis. Belgian trial followed patients prospectively during 2006, using structured survey of clinicians in charge. Serbian trial conducted in 2008, retrieved data from clinical invoice database. Time horizon was one year and perspective of third party payers was taken into account for both studies. Clinical outcomes of interest were disease exacerbation, hospital admission and death. Economic inputs referred to COPD-attributable medical services consumption value during observed period of time. RESULTS: Average annual cost was 1,812.84 € for the Serbian patients and 1,738.13 €/year for the Belgian patients (not including the value of laboratory diagnostics or imaging techniques). Severity grade and duration of hospital admissions significantly directly correlated with overall cost in both populations. Pattern of diagnostic procedures requested and ATC classes of drug consumed to treat COPD remains similar and comparable in both countries. GDP per capita ratio in respective years (10.4: 37.4), exhibits the paradox of patient being much less affordable to treat in a less developed society. CONCLUSIONS: Burden of COPD in Europe is huge and, due to contemporary life style expected to grow further. We compared cost of illness structures between two societies with different macroeconomic past in healthcare financing and management. According to our findings, direct medical costs were driven by exacerbations and hospital admissions. Significantly cheaper human labor caused higher relative relevance of drug acquisition expenses in the East and higher portion of hospital admission costs in the West. More in-depth research of indirect COPD attributable costs (e.g. lost productivity, absenteeism, premature death etc) will be needed in future. It implies serious health policy necessities to provide accessibility of care.
Comparison of Absolute and Relative Pointing Effectiveness using Leap Motion

This project shows an application that can be used as a research tool to compare the ease of use between absolute pointing and relative pointing using Leap Motion Controller. It captures the quantifiable data in order to assess the effectiveness of different pointing techniques using a Leap Motion Controller. The application consists of four colored circles and four target circles. The user needs to select the colored circles one at a time and drag it to the respective target circles. The same task has to be done for both the pointing modes. For comparing the ease of use, we display the time a single user takes to complete the whole task, in each pointing mode.
Multi-Valued Quantization Neural Networks toward Hardware Implementation

This paper proposes a Multi-Valued Quantization (MVQ) method of connecting weight for efficient hardware implementation of Convolutional Neural Networks (CNNs). The proposed method multiplies an input value by a multi-valued quantized weight during the forward and backward propagations, while retaining precision of the stored weights for the update process. In the both propagation processes, multipliers can be replaced with adders and shifters by setting appropriate quantized weights. We train twoto six-valued quantization CNNs with MNIST and CIFAR10 dataset to compare the performance of them with a 32-bit floating point CNN. In the four-valued quantization, random noise is added to the quantized weight to improve the performance of generalization ability. In addition, the robustness of MVQ CNN to noise is evaluated. Experimental results show that the MVQ CNNs achieve better learning accuracy than the floating point CNN and the four-valued CNN is highly robust to the noise.
A systematic review of human and animal leptospirosis in the Pacific Islands reveals pathogen and reservoir diversity

Background The Pacific Islands have environmental conditions highly favourable for transmission of leptospirosis, a neglected zoonosis with highest incidence in the tropics, and Oceania in particular. Recent reports confirm the emergence and outbreaks of leptospirosis in the Pacific Islands, but the epidemiology and drivers of transmission of human and animal leptospirosis are poorly documented, especially in the more isolated and less developed islands. Methodology/Principal findings We conducted a systematic review of human and animal leptospirosis within 25 Pacific Islands (PIs) in Polynesia, Melanesia, Micronesia, as well as Easter Island and Hawaii. We performed a literature search using four international databases for articles published between January 1947 and June 2017. We further included grey literature available on the internet. We identified 148 studies describing leptospirosis epidemiology, but the number of studies varied significantly between PIs. No data were available from four PIs. Human leptospirosis has been reported from 13 PIs, with 63% of all studies conducted in Hawaii, French Polynesia and New Caledonia. Animal leptospirosis has been investigated in 19 PIs and from 14 host species, mainly pigs (18% of studies), cattle (16%) and dogs (11%). Only 13 studies provided information on both human and animal leptospirosis from the same location. Serology results were highly diverse in the region, both in humans and animals. Conclusions/Significance Our study suggests that, as in other tropical regions, leptospirosis is widespread in the PIs while showing some epidemiological heterogeneity. Data are scarce or absent from many PIs. Rodents, cattle, pigs and dogs are all likely to be important carriers, but the relative importance of each animal species in human infection needs to be clarified. Epidemiological surveys with appropriate sampling design, pathogen typing and data analysis are needed to improve our understanding of transmission patterns and to develop effective intervention strategies.
A Novel Approach to 3-D Change Detection in Multitemporal LiDAR Data Acquired in Forest Areas

Light Detection and Ranging (LiDAR) data have been widely used to characterize the 3-D structure of the forest. However, their use in a multitemporal framework has been quite limited due to the relevant challenges introduced by the comparison of pairs of point clouds. Because of the irregular sampling of the laser scanner and the complex structure of forest areas, it is not possible to perform a point-to-point comparison between the two data. To overcome these challenges, a novel hierarchical approach to the detection of 3-D changes in forest areas is proposed. The method first detects the large changes (e.g., cut trees) by comparing the Canopy Height Models derived from the two LiDAR data. Then, according to an object-based change detection approach, it identifies the single-tree changes by monitoring both the treetop and the crown volume growth. The proposed approach can compare LiDAR data with significantly different pulse densities, thus allowing the use of many data available in real applications. Experimental results pointed out that the method can accurately detect large changes, exhibiting a low rate of false and missed alarms. Moreover, it can detect changes in terms of single-tree growth, which are consistent with the expected growth rates of the considered areas.
Comments to: A Novel Low-Cost Instrumentation System for Measuring the Water Content and Apparent Electrical Conductivity of Soils, Sensors, 15, 25546–25563

The article comments on claims made by Rêgo et al. about the sensor they developed to determine soil water content and its salinity via the admittance measurement of electrodes embedded in the soil. Their sensor is not based on a self-balanced bridge, as stated, but on a more common technique relying on Ohm’s law. A bridge is a zero method of measurement which can provide direct voltages proportional to soil permittivity and conductivity with a high resolution. Thanks to modern electronics the method can be adapted for fast and continuous monitoring in a remote site. Because of this confusion about the different measurement techniques among available admittance or capacitance sensors, we give a succinct review of them and indicate how they compare to the two techniques under discussion. We also question the ability of Rêgo et al.’s current sensor to determine both soil water content and salinity due first to instrument biases and then to the soil complexity as a dielectric medium. In particular, the choice of sensor frequencies is crucial in the two steps. In addition, the procedure to determine and account for temperature influences on readings is not presented clearly enough. It is important to distinguish between the effect resulting from electronics sensitivity, and those that are soil-specific. The comment does not invalidate the design of the sensor, but indicates points, especially parasitic contributions, which must be dealt with to avoid major errors.
Measurement errors should always be incorporated in phylogenetic comparative analysis

The evolution of continuous traits is the central component of comparative analyses in phylogenetics, and the comparison of alternative models of trait evolution has greatly improved our understanding of the mechanisms driving phenotypic differentiation. Several factors influence the comparison of models, and we explore the effects of random errors in trait measurement on the accuracy of model selection. We simulate trait data under a Brownian motion model (BM) and introduce different magnitudes of random measurement error. We then evaluate the resulting statistical support for this model against two alternative models: Ornstein–Uhlenbeck (OU) and accelerating/decelerating rates (ACDC). Our analyses show that even small measurement errors (10%) consistently bias model selection towards erroneous rejection of BM in favour of more parameter‐rich models (most frequently the OU model). Fortunately, methods that explicitly incorporate measurement errors in phylogenetic analyses considerably improve the accuracy of model selection. Our results call for caution in interpreting the results of model selection in comparative analyses, especially when complex models garner only modest additional support. Importantly, as measurement errors occur in most trait data sets, we suggest that estimation of measurement errors should always be performed during comparative analysis to reduce chances of misidentification of evolutionary processes.
MPDCompress - Matrix Permutation Decomposition Algorithm for Deep Neural Network Compression

Deep neural networks (DNNs) have become the state-of-the-art technique for machine learning tasks in various applications. However, due to their size and the computational complexity, large DNNs are not readily deployable on edge devices in real-time. To manage complexity and accelerate computation, network compression techniques based on pruning and quantization have been proposed and shown to be effective in reducing network size. However, such network compression can result in irregular matrix structures that are mismatched with modern hardware-accelerated platforms, such as graphics processing units (GPUs) designed to perform the DNN matrix multiplications in a structured (block-based) way. We propose MPDCompress, a DNN compression algorithm based on matrix permutation decomposition via random mask generation. In-training application of the masks molds the synaptic weight connection matrix to a sub-graph separation format. Aided by the random permutations, a hardware-desirable block matrix is generated, allowing for a more efficient implementation and compression of the network. To show versatility, we empirically verify MPDCompress on several network models, compression rates, and image datasets. On the LeNet 300-100 model (MNIST dataset), Deep MNIST, and CIFAR10, we achieve 10 X network compression with less than 1% accuracy loss compared to non-compressed accuracy performance. On AlexNet for the full ImageNet ILSVRC-2012 dataset, we achieve 8 X network compression with less than 1% accuracy loss, with top-5 and top-1 accuracies of 79.6% and 56.4%, respectively. Finally, we observe that the algorithm can offer inference speedups across various hardware platforms, with 4 X faster operation achieved on several mobile GPUs.
Evidence theory data fusion-based method for cyber-attack detection

Detecting electronic crimes is a big challenge as they are tainted with a large number of imperfections such as imprecision and uncertainty. For this reason, we must choose a perfect tool to detect cybercrime taking place in an uncertain environment. In this paper, we are proposing a high-level data fusion approach based on evidence theory (Dempster-Shafer theory) which aims at improving the reliability of cybercrimes detection process using a more improved decision consisting in merging complementary decisions from two independent classifiers, namely Support Vector Machine (SVM) and Artificial Neural network (ANN) in an uncertain environment. In fact, the retained approach is characterized by its capability to overcome the uncertain data nature.
BDD100K: A Diverse Driving Video Database with Scalable Annotation Tooling

Datasets drive vision progress and autonomous driving is a critical vision application, yet existing driving datasets are impoverished in terms of visual content. Driving imagery is becoming plentiful, but annotation is slow and expensive, as annotation tools have not kept pace with the flood of data. Our first contribution is the design and implementation of a scalable annotation system that can provide a comprehensive set of image labels for large-scale driving datasets. Our second contribution is a new driving dataset, facilitated by our tooling, which is an order of magnitude larger than previous efforts, and is comprised of over 100K videos with diverse kinds of annotations including image level tagging, object bounding boxes, drivable areas, lane markings, and full-frame instance segmentation. The dataset possesses geographic, environmental, and weather diversity, which is useful for training models so that they are less likely to be surprised by new conditions. The dataset can be requested at this http URL
Arg753gln and Arg677 Trp Polymorphisms of Toll-Like Receptor 2 In Acute Apical Abscess

Statement of the Problem: Genetic polymorphisms can alter immunity response against pathogens, which in turn influence individuals’ susceptibility to certain infections. Purpose: Our aim was to determine the association of Arg753Gln (rs5743708) and Arg677Trp (rs12191786) polymorphisms of toll like receptor-2 gene with the two clinical forms of apical periodontitis: acute apical abscess (AAA) and asymptomatic apical periodontitis (AAP). Materials and Method: There were 50 patients with AAA as case group and 50 with AAP as control group. Genotyping was done using Tetra-ARMS (amplification refractory mutation system) PCR. Results: Heterozygous genotype of Arg677Trp polymorphism was associated with risk of AAA (OR=1.9, 95% CI: 0.7-5.5, p= 0.05). Although statistically insignificant, Arg677Trp polymorphism promoted the risk of AAA in dominant model (OR=2.1, 95% CI: 0.7-5.9, p> 0.05). The frequency of mutant allele (T) of Arg677Trp polymorphism was higher in AAA (14%) than AAP (7%) subjects (OR=1.7, 95% CI: 0.6-4.7). For Arg753Gln polymorphism, wild homozygous (GG) represented the dominant genotype in both cases (96%) and controls (100%). Variant allele (A) of Arg753Gln polymorphism was identified in 2% of AAA, while no individual represented with this allele in AAP subjects. Individuals with Arg753Gln; Arg677Trp (GG; TC) combination showed an elevated risk of AAA (OR=1.6, 95% CI: 0.5- 4.2, p> 0.05). Conclusion: Arg677Trp polymorphism of TLR-2 rendered a higher risk for the development of abscesses in apical periodontitis. It is recommended to explore role of this polymorphism in other populations.
Achieving Fine-grained Multi-keyword Ranked Search over Encrypted Cloud Data

With the advancement of Cloud computing, people now store their data on remote Cloud servers for larger computation and storage resources. However, users’ data may contain sensitive information of users and should not be disclosed to the Cloud servers. If users encrypt their data and store the encrypted data in the servers, the search capability supported by the servers will be significantly reduced because the server has no access to the data content. In this paper, we propose a Fine-grained Multi-keyword Ranked Search (FMRS) scheme over encrypted Cloud data. Specifically, we leverage novel techniques to realize multikeyword ranked search, which supports both mixed “AND”, “OR” and “NO” operations of keywords and ranking according to the preference factor and relevance score. Through security analysis, we can prove that the data confidentiality, privacy protection of index and trapdoor, and the unlinkability of trapdoor can be achieved in our FMRS. Besides, Extensive experiments show that the FMRS possesses better performance than existing schemes in terms of functionality and efficiency.
Geodynamic Significance of Seismic Anisotropy of the Upper Mantle: New Insights from Laboratory Studies

Seismic anisotropy is caused mainly by the lattice-preferred orientation of anisotropic minerals. Major breakthroughs have occurred in the study of lattice-preferred orientation in olivine during the past ∼10 years through large-strain, shear deformation experiments at high pressures. The role of water as well as stress, temperature, pressure, and partial melting has been addressed. The influence of water is large, and new results require major modifications to the geodynamic interpretation of seismic anisotropy in tectonically active regions such as subduction zones, asthenosphere, and plumes. The main effect of partial melting on deformation fabrics is through the redistribution of water, not through a change in deformation geometry. A combination of new experimental results with seismological observations provides new insights into the distribution of water associated with plume-asthenosphere interactions, formation of the oceanic lithosphere, and subduction. However, large uncertainties remain regarding the role of pressure and the deformation fabrics at low stress conditions.
Event.Locky: System of Event-Data Extraction from Webpages based on Web Mining

Nearby event data, such as those for exhibitions and sales promotions, may help users spend their free time more efficiently. However, most event data are hidden in millions of webpages, which is very time-consuming for a user to find such data. To address this issue, we use web mining that extracts event data from webpages. In this paper, we propose and discuss the implementation of Event.Locky – a system for extracting event data from webpages in a user-defined area and displaying them to a user in a spatial-temporal structure. Furthermore, we design two core algorithms for event data extraction in Event.Locky: webpage-data-record extraction and event-record classification. The former is used to convert a semi-structural HTML document into processable structured data. The latter filters out non-event data from extracted data records using machine learning. We trained and evaluated Event.Locky with an actual dataset composed by 96 restaurants and shops at Nagoya train station. As a result, our event-classification algorithm achieved an F1 score of 91.61%, an increase of 3.07% from current event-classification algorithms. The combination of our event-classification algorithm and our data-record-extraction algorithm achieved F1 score 83.96% to extract event records from webpages. That increased 1.6% from current algorithm. Finally, we discuss the feasibility of Event.Locky in an actual online environment through the implementation of a demonstration application.
QM/MM Investigation of the Role of a Second Coordination Shell Arginine in [NiFe]-Hydrogenases

[NiFe]-hydrogenases are highly efficient catalysts for the heterolytic splitting of molecular hydrogen (H2). The heterobimetallic cysteine-coordinated active site of these enzymes is covered by a highly conserved arginine residue, whose role in the reaction is not fully resolved yet. The structural and catalytic role of this arginine is investigated here using QM/MM calculations with various exchange-correlation functionals. All of them give a very consistent picture of the thermodynamics of H2 oxidation. The concept of the presence of a neutral arginine and its direct involvement as a Frustrated Lewis Pair (FLP) in the reaction is critically evaluated. The arginine, however, would exist in its standard protonation state and perform a critical role in positioning and slightly polarizing the substrate H2. It is not directly involved in the heterolytic processing of H2 but guides its approach and reduces its flexibility during binding. Upon substitution of the positively charged arginine by a charge-conserving lysine residue, the H2 binding position remains unaffected. However, critical hydrogen bonding interactions with nearby aspartate residues are lost. In addition, the H2 polarization is unfavorable and the reduced side-chain volume may negatively affect the kinetics of the catalytic process.