Miracle-dz/UniFAR-FTUs huggingface dataset:
Capturing human category representations by sampling in deep feature spaces

Understanding how people represent categories is a core problem in cognitive science. Decades of research have yielded a variety of formal theories of categories, but validating them with naturalistic stimuli is difficult. The challenge is that human category representations cannot be directly observed and running informative experiments with naturalistic stimuli such as images requires a workable representation of these stimuli. Deep neural networks have recently been successful in solving a range of computer vision tasks and provide a way to compactly represent image features. Here, we introduce a method to estimate the structure of human categories that combines ideas from cognitive science and machine learning, blending human-based algorithms with state-of-the-art deep image generators. We provide qualitative and quantitative results as a proof-of-concept for the method's feasibility. Samples drawn from human distributions rival those from state-of-the-art generative models in quality and outperform alternative methods for estimating the structure of human categories.
True polyploid meiosis in the human male

Abstract Polyploidy does not usually occur in germinal cells of mammals and other higher vertebrates. We describe a unique example of mosaic autotetraploidy in the meiosis of a human male. Although the original observations were made in the late 1960s, we did not publish them at that time, because we expected to detect further examples that could be described together. However, this did not occur and we have now decided to make the observations available to demonstrate that polyploidy in mammalian male meiosis can arise at a higher frequency than expected by random polyploidization of individual meiotic cells, by either DNA duplication or cell fusion prior to synapsis. This is the first description of a population of primary spermatocytes exhibiting multivalent formation at leptotene /diakinesis in human spermatogenesis, with ring, chain, frying pan and other types of quadrivalents, typical of autotetraploidy. As many of the polyploid configurations showed apoptotic breakdown, it is likely that diploid and/or aneuploid spermatozoa would have rarely or never resulted from this mosaic autotetraploid meiosis.
Learning Hierarchical Visual Representations in Deep Neural Networks Using Hierarchical Linguistic Labels

Modern convolutional neural networks (CNNs) are able to achieve human-level object classification accuracy on specific tasks, and currently outperform competing models in explaining complex human visual representations. However, the categorization problem is posed differently for these networks than for humans: the accuracy of these networks is evaluated by their ability to identify single labels assigned to each image. These labels often cut arbitrarily across natural psychological taxonomies (e.g., dogs are separated into breeds, but never jointly categorized as "dogs"), and bias the resulting representations. By contrast, it is common for children to hear both "dog" and "Dalmatian" to describe the same stimulus, helping to group perceptually disparate objects (e.g., breeds) into a common mental class. In this work, we train CNN classifiers with multiple labels for each image that correspond to different levels of abstraction, and use this framework to reproduce classic patterns that appear in human generalization behavior.
Molecular Targets of Active Anticancer Compounds Derived from Marine Sources

Over the past decades, a number of novel compounds, which are produced in the marine environment, have been found to exhibit the anticancer effects. This review focuses on molecular targets of marine-derived anticancer candidates in clinical and preclinical studies. They are kinases, transcription factors, histone deacetylase, the ubiquitin-proteasome system, and so on. Specific emphasis of this review paper is to provide information on the optimization of new target compounds for future research and development of anticancer drugs, based on the identification of structures of these target molecules and parallel compounds.
Validation environment for AIPS/ALS: Implementation and results

The work is presented which was performed in porting the Fault Injection-based Automated Testing (FIAT) and Programming and Instrumentation Environments (PIE) validation tools, to the Advanced Information Processing System (AIPS) in the context of the Ada Language System (ALS) application, as well as an initial fault free validation of the available AIPS system. The PIE components implemented on AIPS provide the monitoring mechanisms required for validation. These mechanisms represent a substantial portion of the FIAT system. Moreover, these are required for the implementation of the FIAT environment on AIPS. Using these components, an initial fault free validation of the AIPS system was performed. The implementation is described of the FIAT/PIE system, configured for fault free validation of the AIPS fault tolerant computer system. The PIE components were modified to support the Ada language. A special purpose AIPS/Ada runtime monitoring and data collection was implemented. A number of initial Ada programs running on the PIE/AIPS system were implemented. The instrumentation of the Ada programs was accomplished automatically inside the PIE programming environment. PIE's on-line graphical views show vividly and accurately the performance characteristics of Ada programs, AIPS kernel and the application's interaction with the AIPS kernel. The data collection mechanisms were written in a high level language, Ada, and provide a high degree of flexibility for implementation under various system conditions.
Estimation of bone mineral density and breaking strength of laying hens based on scans of computed tomography for body composition analysis

ABSTRACT 1. The objective of this study was to evaluate the prediction potential of a computer tomography (CT) data collection protocol for determining total body composition used for analysis of tibiotarsal bone quality features. 2. The CT image acquisition was performed on 54 healthy TETRA SL genotype laying hens at 90 weeks of age as well as in the 69th week of the egg production period in vivo and their tibiotarsal bones, ex vivo. 3. Breaking strengths and ash content of the tibiotarsal bones were estimated based on the calculated mineral density of skeletal and tibiotarsal bones by means of CT with an estimation accuracy R2 0.963 and 0.975, respectively. 4. In conclusion, the current investigation demonstrated that the acquisition protocol of CT for total-body composition analysis has a good potential for measuring the mineral status and breaking strength of the reference bone in laying hen.
Management of pleural infections

ABSTRACT Introduction: The management of infected pleural effusion is complex. Therapeutic resolution requires determining the following: appropriate antibiotic regimen, the need for pleural drainage, the optimal drainage tube size, and the need for intrapleural therapy or surgery. Areas covered: An updating of the latest advances in the management of parapneumonic pleural effusion based on the best evidence available is provided. Expert commentary: The correct management of parapneumonic pleural effusion is based on selecting an antibiotic regimen according to the origin of the pleural infection (community-acquired or nosocomial). If pleural drainage is indicated, a small-bore chest tube is appropriate. Although the administration of fibrinolytics is not required in all cases, when necessary, recombinant t-PA in combination with deoxyribonuclease is the preferred therapy. If surgery is indicated, video-assisted thoracoscopic surgery is as effective – if not superior – as open decortication. All these therapies should be complemented with appropriate nutritional support. Further clinical trials are needed to confirm whether new therapeutic strategies such as a pleural cavity saline wash are more effective in the management of this disease.
Hybrid Multiple-Input Multiple-Output OFDM Index Modulation for 5G Wireless System

: Multiple-input multiple-output (MIMO) based index modulation has the advantage of high data rate and low complexity transmission and has great attention now a days. At the same time due to invention of digital video broadcasting 16-QAM and 64-QAM schemes are widely used in wireless systems. In this paper we introduce a novel low-complexity signal detector enabled multiple-input multiple-output (MIMO) detector with IM systems, suitable for efficient low complexity system with tolerable error rate. The actual IM methods has no diversity gain which causes a significant reduction in the system performance. In this paper to eliminate the bad effects of the channel assignment of the IM, novel ML based MIMO systems with index modulation technique (ML-MIMO-IM) is proposed. Here the efficient hybrid ML sub detector system is used to achieve superior performance compared to the conventional MIMO detectors. The performance of the proposed design is close to the existing MIMO scheme, while resulting in a significantly lower complexity. The efficiency of MIMO over high order constellations are verified through MATLAB BER simulation and complexity reduction is also proved to be an efficient one.
Unsupervised Cross-Modal Alignment of Speech and Text Embedding Spaces

Recent research has shown that word embedding spaces learned from text corpora of different languages can be aligned without any parallel data supervision. Inspired by the success in unsupervised cross-lingual word embeddings, in this paper we target learning a cross-modal alignment between the embedding spaces of speech and text learned from corpora of their respective modalities in an unsupervised fashion. The proposed framework learns the individual speech and text embedding spaces, and attempts to align the two spaces via adversarial training, followed by a refinement procedure. We show how our framework could be used to perform spoken word classification and translation, and the results on these two tasks demonstrate that the performance of our unsupervised alignment approach is comparable to its supervised counterpart. Our framework is especially useful for developing automatic speech recognition (ASR) and speech-to-text translation systems for low- or zero-resource languages, which have little parallel audio-text data for training modern supervised ASR and speech-to-text translation models, but account for the majority of the languages spoken across the world.
Quercetin improves metabolic sequels and placental morphology in streptozotocin-induced diabetic rats

Objective: Quercetin (QE) is a flavonoid widely distributed in nature. This experimental study was designed to evaluate the effect of QE on the placenta in streptozotocin-induced diabetic rats. Methods: Thirty virgin female Wistar rats (200–250 g) were mated with 15 males for at least 12 h. From the onset of pregnancy, the rats were divided equally into three experimental groups including control, streptozotocin (STZ)-treated, and STZ+QE-treated. Pregnant rats were sacrificed on day 21 of pregnancy and the placental tissue was harvested. Placental tissues and blood samples in all groups were processed for biochemical and histological analysis. Results: QE treatment gave rise a sharp decrease in the elevated serum glucose levels and an increased in the lowered serum insulin concentrations in STZ-induced diabetic rats (p<0.05). Placental malondialdehyde (MDA) level was considerably reduced in rats treated with QE when compared to untreated group (p<0.05). QE treatment produced a significant increase superoxide dismutase (SOD) and glutathione peroxidase (GPx) activities compared with the diabetic untreated group (p<0.05). On the diabetic group, proliferating cell nuclear antigen (PCNA) immunolabeling intensities decreased and TUNEL positive cells in the placenta of rats was found to increased. Conclusion: Quercetin has a protective effect in diabetes by decreasing oxidative stress and apoptosis, and by preservation of plasental morphology. QE gives hope to improve treatment diabetes mellitus in pregnancy.
Bidirectional Learning for Robust Neural Networks

A multilayer perceptron can behave as a generative classifier by applying bidirectional learning (BL). It consists of training an undirected neural network to map input to output and vice-versa; therefore it can produce a classifier in one direction, and a generator in the opposite direction for the same data. The learning process of BL tries to reproduce the neuroplasticity stated in Hebbian theory using only backward propagation of errors. In this paper, two learning techniques are independently introduced which use BL for improving robustness to white noise static and adversarial examples. The first method is bidirectional propagation of errors, which the error propagation occurs in backward and forward directions. Motivated by the fact that its generative model receives as input a constant vector per class, we introduce as a second method the novel hybrid adversarial networks (HAN). Its generative model receives a random vector as input and its training is based on generative adversarial networks (GAN). To assess the performance of BL, we perform experiments using several architectures with fully and convolutional layers, with and without bias. Experimental results show that both methods improve robustness to white noise static and adversarial examples, and even increase accuracy, but have different behavior depending on the architecture and task, being more beneficial to use the one or the other. Nevertheless, HAN using a convolutional architecture with batch normalization presents outstanding robustness, reaching state-of-the-art accuracy on adversarial examples of hand-written digits.
A new unsteady mixing model to predict NO(x) production during rapid mixing in a dual-stage combustor

An advanced gas turbine engine to power supersonic transport aircraft is currently under study. In addition to high combustion efficiency requirements, environmental concerns have placed stringent restrictions on the pollutant emissions from these engines. A combustor design with the potential for minimizing pollutants such as NO(x) emissions is undergoing experimental evaluation. A major technical issue in the design of this combustor is how to rapidly mix the hot, fuel-rich primary zone product with the secondary diluent air to obtain a fuel-lean mixture for combustion in the second stage. Numerical predictions using steady-state methods cannot account for the unsteady phenomena in the mixing region. Therefore, to evaluate the effect of unsteady mixing and combustion processes, a novel unsteady mixing model is demonstrated here. This model has been used to study multispecies mixing as well as propane-air and hydrogen-air jet nonpremixed flames, and has been used to predict NO(x) production in the mixing region. Comparison with available experimental data show good agreement, thereby providing validation of the mixing model. With this demonstration, this mixing model is ready to be implemented in conjunction with steady-state prediction methods and provide an improved engineering design analysis tool.
Evaluation of the Factors Affecting Concerns and Expectations of Patients Undergoing Total Knee Arthroplasty in China

Background The aim of this study was to assess the level of concern and expectations of patients and their families of total knee arthroplasty (TKA), peri-operative procedures, postoperative rehabilitation, and outcome in a Chinese population. Material/Methods The study recruited 133 patients with osteoarthritis, scheduled to undergo primary elective TKA. Before surgery, the surgeon completed the Hospital for Special Surgery (HSS) Knee Score questionnaire on pain, function, range of motion (ROM), and muscle strength. There were 128 patients and 127 family members (spouses, sons, or daughters) who completed the 24-item Western Ontario and McMaster University Osteoarthritis Index (WOMAC) questionnaire on pain, stiffness, and physical function, and also a 61-item questionnaire that included direct questions on their concerns and expectations on TKA and its outcome, using scores of: 1, not concerned; 2, somewhat concerned; 3, very concerned; and 4, extremely concerned. Results The five greatest pre-operative concerns for patients included the degree of postoperative mobility; the experience and expertise of their surgeon; the risk of failure of TKA; the duration of the joint implant; and their expected degree of postoperative independence. Scores for Chinese patients indicated a higher level of concern compared with Western patients. Family members were significantly more concerned than patients regarding the postoperative restoration of knee function and alleviation of pain (p=0.001), the ability to squat (p=0.049) and to kneel (p=0.039). Conclusions Communicating pre-operative information on TKA might result in realistic expectations for patients and their families, alleviate concerns, and improve relationships between doctors and patients.
Heterogeneous Multi-output Gaussian Process Prediction

We present a novel extension of multi-output Gaussian processes for handling heterogeneous outputs. We assume that each output has its own likelihood function and use a vector-valued Gaussian process prior to jointly model the parameters in all likelihoods as latent functions. Our multi-output Gaussian process uses a covariance function with a linear model of coregionalisation form. Assuming conditional independence across the underlying latent functions together with an inducing variable framework, we are able to obtain tractable variational bounds amenable to stochastic variational inference. We illustrate the performance of the model on synthetic data and two real datasets: a human behavioral study and a demographic high-dimensional dataset.
Decreased plasma prorenin levels in primary aldosteronism: potential diagnostic implications

Aim: Primary aldosteronism could exert a negative feedback on prorenin secretion, of possibly different magnitude, whether it is related to an aldosterone-producing adenoma (APA) or an idiopathic hyperaldosteronism (IHA). The objectives of this study were to evaluate the level of prorenin in three subgroups: APA, IHA, and essential hypertension; and the performance of the aldosterone-to-prorenin ratio (APR) for the diagnosis of an APA. Methods: Seven hundred and forty-six hypertensive patients with a standardized work-up, including a prorenin measurement, were considered. Ninety-six patients without neutral treatment and 38 patients with other forms of secondary hypertension were excluded. APA and IHA were categorized according to computed tomography scan, adrenal venous sampling, pathological analysis and improvement of hypertension after surgery. Results: Thirty-five patients had a diagnosis of APA, 57 of IHA and 504 of essential hypertension. Prorenin was lower in APA and IHA than in essential hypertension (32.9, 40.4 and 50.3 pg/ml, respectively; P < 0.001). APR was higher in patients with APA and IHA than in those with essential hypertension (24.0, 11.8, and 4.0 pmol/l per pg/ml, respectively; P < 0.001). The APR was more discriminant than the aldosterone-to-renin ratio to identify APA compared to IHA (area under the receiver operating curve at 0.750 and 0.639, respectively; P = 0.04). The optimal cut-off values were 22 pmol/l per pg/ml for APR (sensitivity 57.0%, specificity 93.0%) and 440 pmol/l per pg/ml for aldosterone-to-renin ratio (sensitivity 54.3%, specificity 82.5%). Conclusion: Primary aldosteronism and particularly its most caricatural form, that is APA, seems associated with a lower level of prorenin than essential hypertension. The APR could be included in the diagnostic strategy of APA.
Organizacinių pokyčių valdymas: teoriniai ir praktiniai aspektai

The processes of globalization, new technologies, intense competition and the internal environment of organisations predetermine organisational changes which have the main purpose to adapt to the changing environment. Therefore organisational change management has become the topical issue of today’s business companies. The paper analyses the aspects of organisational change management. The results of a survey of organisational change management are analysed. At the end of the paper the results of the survey are summarized and the conclusions are presented.
An Evidence‐based Forensic Taxonomy of Windows Phone Dating Apps

Advances in technologies including development of smartphone features have contributed to the growth of mobile applications, including dating apps. However, online dating services can be misused. To support law enforcement investigations, a forensic taxonomy that provides a systematic classification of forensic artifacts from Windows Phone 8 (WP8) dating apps is presented in this study. The taxonomy has three categories, namely: Apps Categories, Artifacts Categories, and Data Partition Categories. This taxonomy is built based on the findings from a case study of 28 mobile dating apps, using mobile forensic tools. The dating app taxonomy can be used to inform future studies of dating and related apps, such as those from Android and iOS platforms.
Pilot study of the antifibrotic effects of the multikinase inhibitor pacritinib in a mouse model of liver fibrosis

Background Fibrotic diseases result from an exuberant response to chronic inflammation. Myelofibrosis is the end result of inflammation in bone, caused by an inflammatory process triggered by production of abnormal myeloid cells driven by mutations affecting the JAK–STAT pathway. Inflammatory cytokine overproduction leads to increased mesenchymal cell proliferation, culminating in fibrosis. Although JAK2 inhibitors, such as the JAK1/2 inhibitor ruxolitinib and the JAK2/FLT3/CSF1R/IRAK1 inhibitor pacritinib suppress abnormal clone expansion in myelofibrosis, ruxolitinib does not appear to prevent or reverse bone-marrow fibrosis in most patients. In two Phase III clinical trials, pacritinib, however, demonstrated improvements in platelet counts and hemoglobin and reductions in transfusion burden in some patients with baseline cytopenias, suggesting it may improve bone-marrow function. Unlike ruxolitinib, pacritinib suppresses signaling through IRAK1, a key control point for inflammatory and fibrotic signaling. Purpose To investigate potential antifibrotic effects of pacritinib in an animal model of liver fibrosis relevant to the observed course of human disease. Methods Pacritinib, negative control (vehicle), and positive control (the angiotensin 2-receptor antagonist and PPARγ partial agonist telmisartan) were assessed in the murine Stelic animal model, which mimics the clinically observed progression from hepatic steatosis to nonalcoholic steatohepatitis, liver fibrosis, and hepatocellular carcinoma. Histopathological analysis used hematoxylin and eosin staining. Body and liver weight changes, nonalcoholic fatty-liver disease activity scores, and plasma cytokeratin 18 fragment levels (a biomarker of hepatic necrosis) were measured. Results Pacritinib-treated mice had significantly (P<0.01) reduced fibrotic areas in liver compared to vehicle control and significantly (P<0.05) lower levels of CK18. The antifibrotic effect of pacritinib was comparable to that of telmisartan, but without significant effects on fat accumulation. Conclusion These results, the first to demonstrate hepatic antifibrotic effects for pacritinib in an animal model of liver disease, provide preliminary support for potential clinical applications of pacritinib in fibrotic diseases other than myelofibrosis.