Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of the Polish Version of the ICF Core Set for the Environment of Older People

Introduction: The percentage of older people in Polish society increases every year. The interaction between the individual health condition and the barriers in the environment of the elderly leads to the development of disability and the limitation of activity and participation in daily activities. Aim: This study was aimed at selecting the category of the International Classification of Functioning, Disability, and Health (ICF) to assess the environment of older adults in Poland in the context of their daily functioning. Materials and methods: The study was designed to develop a user-friendly tool collecting ICF-based data on the living environment of older people, consisting of five phases: (1) the systematic review of the literature, (2) the empirical multicenter study, (3) the qualitative study based on interviews conducted among the elderly, (4) the experts’ study—an assessment of selected codes from the perspective of experts, (5) the consensus conference. Results: Consensus was reached for 20 ICF categories, creating a comprehensive core set for the assessment of the living environment of older people, which included six codes from chapter 1, Products and technology, three codes from chapter 2, Natural environment and human-made changes to the environment, four codes from chapter 3, Support and relationships, four codes from Chapter 4, Attitudes, and three codes from Chapter 5, Services, systems, and policies. Conclusions: The core set for the assessment of the living environment of older people living in Poland is a comprehensive and important set of 20 ICF codes that reflect the most important elements of the environment affecting the health and functioning of the elderly. This set can contribute to the optimal management of care services and support in the area of adapting the environment to the older population. The core set for environmental assessment was developed for use by medical and care facilities, as well as by social workers, who should also pay attention to the elements of the environment that affect the level of functioning of older people. In the future, it may also form the basis of national surveys and screening tests for the assessment of the living environment of older people. Optimizing and enhancing the surrounding environment can contribute to a greater degree of independence, even with existing health problems in the older population.
A Novel Weighted Fusion Based Efficient Clustering for Improved Wi-Fi Fingerprint Indoor Positioning

The <italic>received signal strength</italic> (RSS) based <italic>Wi-Fi</italic> fingerprint technique is not only a cost-effective means for indoor positioning but also provides reliable positioning accuracy in the indoor settings. Thus, such positioning technique has drawn many researchers<inline-formula> <tex-math notation="LaTeX">$'$ </tex-math></inline-formula> attention to address its several limitations like degraded <italic>positioning accuracy</italic> due to continuous changes in surrounding environment, high <italic>positioning overhead</italic>, <italic>storage overhead</italic> etc. To address these issues, we propose a <italic>novel weighted fusion based efficient clustering strategy</italic> (<italic>WF-ECS</italic>) for fingerprint positioning system in this paper. Our proposed technique <italic>WF-ECS</italic> computes a weighted average of the group of <italic>reference points</italic> (RPs) having similar RSS patterns and thus, creates a more perfect match between fused positional co-ordinates and RSS patterns considered for merging to a single entry. Extensive experimentation have been carried out to evaluate and compare the performances of our proposed system <italic>WF-ECS</italic> with the contemporary fingerprint positioning systems including our prior work using the simulation test bed, the dataset collected from our departmental building and also the <italic>benchmark dataset</italic>. The experimental results depict that our newly proposed technique <italic>WF-ECS</italic> can outperform the contemporary techniques in terms of <italic>positioning accuracy</italic> and <italic>positioning overhead</italic> while reducing the <italic>storage overhead</italic> in real indoor settings.
Deep Imaging Surveys of Star-forming Clouds. I. New Herbig-Haro Flows in NGC 2264

We have embarked on a major, imaging survey of nearby star-forming regions using wide-field imaging detectors to identify and characterize the full population of Herbig-Haro flows from newborn stars in each region. In this study we present our survey results for the NGC 2264 region in Monoceros, where we have found a number of new Herbig-Haro objects, HH 571–HH 585, including several giant, parsec-scale flows. We discuss the individual flows and attempt to locate their region of origin. In particular, we identify two quadrupolar HH flows emanating from two cloud cores and associated with major molecular outflows. We also draw attention to what appears to be a region of major blowout of gas from a cloud core rich in young stars.
Gut Microbiota Alterations in Trace Amine-Associated Receptor 9 (TAAR9) Knockout Rats

Trace amine-associated receptors (TAAR1-TAAR9) are a family of G-protein-coupled monoaminergic receptors which might have great pharmacological potential. It has now been well established that TAAR1 plays an important role in the central nervous system. Interestingly, deletion of TAAR9 in rats leads to alterations in the periphery. Previously, we found that knockout of TAAR9 in rats (TAAR9-KO rats) decreased low-density lipoprotein cholesterol levels in the blood. TAAR9 was also identified in intestinal tissues, and it is known that it responds to polyamines. To elucidate the role of TAAR9 in the intestinal epithelium, we analyzed TAAR9-co-expressed gene clusters in public data for cecum samples. As identified by gene ontology enrichment analysis, in the intestine, TAAR9 is co-expressed with genes involved in intestinal mucosa homeostasis and function, including cell organization, differentiation, and death. Additionally, TAAR9 was co-expressed with genes implicated in dopamine signaling, which may suggest a role for this receptor in the regulation of peripheral dopaminergic transmission. To further investigate how TAAR9 might be involved in colonic mucosal homeostasis, we analyzed the fecal microbiome composition in TAAR9-KO rats and their wild-type littermates. We identified a significant difference in the number of observed taxa between the microbiome of TAAR9-KO and wild-type rats. In TAAR9-KO rats, the gut microbial community became more variable compared with the wild-type rats. Furthermore, it was found that the family Saccharimonadaceae, which is one of the top 10 most abundant families in TAAR9-KO rat feces, is almost completely absent in wild-type animal fecal samples. Taken together, these data indicate a role of TAAR9 in intestinal function.
The Quality and Bacterial Community Changes in Freshwater Crawfish Stored at 4 °C in Vacuum Packaging

Crawfish can be easily spoiled due to their rich nutrition and high water content, which is difficult to preserve. In this study, the dominant spoilage organisms in crawfish which were stored at 4 °C in vacuum packaging were identified by high-throughput sequencing technology; after sequencing the full-length 16S rRNA gene, the changes in the bacterial community structure, diversity and quality (texture, flavor, etc.) were analyzed. Our results reflected that the specific spoilage organisms (SSOs) of crawfish were Aeromonas sobria, Shewanella putrefaciens, Trichococcus pasteurii and Enterococcus aquimarinus, since their abundances significantly increased after being stored for 12 days at 4 °C under vacuum conditions. At the same time, the abundance and diversity of the microbial community decreased with storage time, which was related to the rapid growth of the dominant spoilage organisms and the inhibition of other kinds of microorganisms at the end of the spoilage stage. Function prediction results showed that the gene which contributed to metabolism influenced the spoilage process. Moreover, the decline in texture of crawfish was negatively correlated to the richness of SSOs; this may be because SSOs can produce alkaline proteases to degrade the myofibrillar protein. On the contrary, the unpleasant flavor of crawfish, resulting from volatile flavor compounds such as S-containing compounds and APEOs, etc., is negatively correlated to the richness of SSOs, due to the metabolism of SSOs by secondary metabolites such as terpenoids, polyketides and lips, which can lead to decarboxylation, deamination and enzymatic oxidation. These results are very important to achieve the purpose of targeted inhibition of crawfish spoilage at 4 °C in vacuum packaging.
Reduction of Crosstalk Errors in a Surface Encoder Having a Long Z-Directional Measuring Range

A modified two-axis surface encoder is proposed to separately measure both the in-plane displacement and the Z-directional out-of-plane displacement with minor crosstalk errors. The surface encoder is composed of a scale grating and a small-sized sensor head. In the modified surface encoder, the measurement laser beam from the sensor head is designed to be projected onto the scale grating at a right angle. For measurement of the X- and Y-directional in-plane scale displacement, the positive and negative first-order diffracted beams from the scale grating are superimposed on each other in the sensor head, producing interference signals. On the other hand, the Z-directional out-of-plane scale displacement is measured based on the principle of a Michelson-type interferometer. To avoid the influence of reflection from the middle area of the transparent grating, which causes periodic crosstalk errors in the previous research, a specially fabricated transparent grating with a hole in the middle is employed in the newly designed optical system. A prototype sensor head is constructed, and basic performances of the modified surface encoder are tested by experiments.
Double‐RSOA colorless WDM‐PON for 5G fronthaul applications

The introduction of 5G mobile systems poses significant challenges to the design of the fronthaul structure. The dense coverage, comprising several small cells operating in the millimeter‐wave range, with an enormous number of antennas, makes conventional digital‐radio‐over‐fiber unfeasible. On the other hand, the centralized architecture of the optical fronthaul is well‐suited for the passive optical network (PON) topology, with WDM‐PON as a strong contender due to its capability to establish logical point‐to‐point optical links to each cell site. However, the large‐scale deployment of WDM‐PON requires the availability of colorless transmitters, where the same hardware is able to generate any wavelength needed by the network. In this context, this paper investigates an analog fronthaul configuration over a colorless WDM‐PON for 5G and beyond, employing the techniques of self‐seeding in the downlink and carrier reuse in the uplink. We numerically evaluated the EVM when transmitting 1.25 Gbps at 3.5 GHz and 10 Gbps at 26 GHz in a 20 km optical link. The results are within the 3GPP requirements, demonstrating the feasibility of the proposed fronthaul.
Efficient Feature Based Melanoma Skin Image Classification Using Machine Learning Approaches

Skin cancer is the most prevalent and deadliest kind of cancer. Melanoma is the most dangerous type of skin cancer, but it can be detected earlier and successfully treated. The dermoscopic image classification using Machine Learning (ML) approaches in identifying melanoma is increased over the last two decades. The proposed classification system involves three stages. Initially, the pre-processing employs the median filter and thresholding approach aids to remove the hairs and unwanted noise. Then, the shape components, Asymmetry, Border Irregularity, Colour and Dermoscopic structure (ABCD) rule, and Grey Level Co-occurrence Matrix (GLCM) features are utilized to extract the skin lesion region. After that, the K-Nearest Neighbor (KNN), Random Forest (RF), and Support Vector Machine (SVM) classifiers are employed to perform melanoma skin classification from the skin lesion. The dermoscopic skin images used in this study are obtained from the PH2 database. Finally, the SVM classifier outperformed the other classifiers in identifying melanoma skin cancer, providing 94.81% efficiency.
Non-Alcoholic Fatty Liver Disease (NAFLD) Pathogenesis and Natural Products for Prevention and Treatment

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease, affecting approximately one-quarter of the global population, and has become a world public health issue. NAFLD is a clinicopathological syndrome characterized by hepatic steatosis, excluding ethanol and other definite liver damage factors. Recent studies have shown that the development of NAFLD is associated with lipid accumulation, oxidative stress, endoplasmic reticulum stress, and lipotoxicity. A range of natural products have been reported as regulators of NAFLD in vivo and in vitro. This paper reviews the pathogenesis of NAFLD and some natural products that have been shown to have therapeutic effects on NAFLD. Our work shows that natural products can be a potential therapeutic option for NAFLD.
Quantitative imaging of inhomogeneities in turbid medium using diffuse optical tomography: a genetic algorithm based approach

We report the use of genetic algorithm-based approach for reconstruction of the optical inhomogeneities embedded in turbid medium using diffuse optical tomography. In the proposed inversion scheme, the task of image reconstruction is formulated as optimization (minimization) problem which is solved using genetic algorithm approach to find the global minimum of the objective function. This approach preserves the full non-linear features of the problem and it can be applied for quantitative reconstruction over a wide range of contrast values where conventional linear and higher order reconstruction approaches show severe limitations. Successful implementation of the proposed scheme has been demonstrated for quantitative reconstruction of absorbing inhomogeneities (single as well as double) embedded in an otherwise homogeneous medium. In order to demonstrate its potential, reconstruction results have been presented for a wide range of parameters including size, location and contrast of the absorbing inhomogeneities embedded in the turbid medium.
Mathematical series for analysis of detuned active mode locked lasers

We propose a series method to analyze detuned active mode-locked lasers. Using this method, we can analyze not only noiseless lasers but also lasers modelled with amplified spontaneous emission (ASE) noise. Moreover, the method also helps to study the transient evolution of the pulse inside the cavity, which cannot be done using classical analysis.
First Passage Time Distribution of a Two-Dimensional Wiener Process with Drift

The two-dimensional correlated Wiener process (or Brownian motion) with drift is considered. The Fokker-Planck (or Kolmogorov forward) equation for the Wiener process (X1(t), X2(t)) is solved under absorbing boundary conditions on the lines x1= h1 and x2 = h2 and a fixed starting point (x0,1, x0,2). The first passage (or first exit) time when the process leaves the domain G = ( −∞, h1) × ( −∞, h2) is derived.
On Discrete Fourier Spectrum of Randomly Modulated Signals

On Discrete Fourier Spectrum of Randomly Modulated Signals In this work the problem of characterization of Discrete Fourier Transform (DFT) spectrum of an original complex-valued signal modulated by random fluctuations of amplitude and phase is investigated. It is assumed that the amplitude and phase of signal values at discrete time moments of observations are distorted by adding realizations of independent and identically distributed random variables. The obtained results of theoretical analysis of such distorted signal spectra show that only in the case of amplitude modulation the DFT spectrum of the modulated bounded signal can be similar to the original signal spectrum, although there occur random deviations. On the other hand, if phase modulation is present, then the DFT spectrum of the modulated bounded signal not only shows random deviations but also amplitudes of peaks existing in the original spectrum are diminished, and consequently similarity to the original signal spectrum can be significantly blurred.
Design of an optical nanobiosensor for detection of Legionella pneumophila in water samples

Background and Objectives: Legionella spp. is a causative agent of Legionnaires’ disease that creates public health problems. Isolation of these bacteria from water sources is essential to identify outbreak origins and prevent disease. Diagnostic biosensors for water quality control to protect consumers from water-borne infections can predict many outbreaks. Gold nanoparticles conjugated probes are a new generation of diagnostic tools. In this study, an optical nano biosensor was designed and characterized to detect Legionella pneumophila in water samples rapidly. Materials and Methods: Thiolated probes designed for the mip gene were attached to gold nanoparticles and then water samples containing Legionella pneumophila were examined. Results: The limit of detection for PCR and biosensor was 104 and 103 copy numbers/μl, respectively. Biosensor sensitivity and PCR were reported to be 90% (18 out of 20) and 85% (17 out of 20), respectively. Specificity 100% has been reported for both methods. Conclusion: According to the obtained results, this method has the potential to diagnose L. pneumophila with high sensitivity and specificity. This system can be employed as a practical tool for rapid, accurate, high-sensitivity, and acceptable detection of Legionella pneumophila in contaminated water, which is cost-effective in terms of cost and time.
Strong Left-Invertibility and Strong Input-Observability of Nonlinear Time-Delay Systems

In this letter, we study the problem of unknown inputs reconstruction for nonlinear time-delay systems. First we define two notions called strong left-invertibility and strong input-observability and the word “strong” is to address the causality properties of those two notions. Then necessary and sufficient conditions for the strong left-invertibility and the strong input-observability are given under the algebraic framework proposed in (Xia et al., 2002). We find that a sequence of inputs submodules plays an important role for the strong left-invertibility of time-delay systems. A structure algorithm is provided to construct that sequence and to formulate an input reconstructor. At last, several examples are given to illustrate how to check the strong left-invertibility and the strong input-observability by applying the proposed structure algorithm, and to show how to recover the inputs via causal outputs and the initial value functions of states (strong left-invertibility) or only via causal outputs (strong input-observability).
Low-frequency noise measurements on commercial magnetoresistive magnetic field sensors

Low-frequency noise was measured in the frequency range from 0.1Hzto10kHz on a variety of commercially available magnetic sensors. The types of sensors investigated include anisotropic magnetoresistance (AMR), giant magnetoresistance (GMR), and tunnel magnetoresistance (TMR) effect devices. The 1∕f noise components of electronic and magnetic origin are identified by measuring sensor noise and sensitivity at various applied magnetic fields. Commercial magnetometers typically consist of four elements in a Wheatstone bridge configuration and are biased with either a constant voltage or current. Voltage fluctuations at the sensor output are amplified by a pair of battery powered low-noise preamplifiers and input to a spectrum analyzer. A two-channel cross-correlation technique is used when the performance of a single preamplifier is not sufficient. For the AMR and GMR sensors investigated, both electronic and magnetic components contribute to the overall sensor noise. Maximum noise occurs at the bias field wh.
Morphometric Assessment and Condition Factor of the Mangrove Oyster from a tropical mangrove swamp, off Lagos Lagoon, South-West, Nigeria

The size composition, growth pattern and condition factor of One thousand, two hundred and sixty (1260) mangrove oyster - Crassostrea tulipa (C. tulipa) from the mangrove swamp, Lagos Lagoon were studied using recommended morphometric methods. The total shell length ranged from 1.5cm to 18.4cm, maximum width ranged from 1.5cm â€“ 10.4cm and the total weight was between 1.92g â€“ 132.1g. The oysters showed a unimodal size distribution. Also, there is strong significant correlation between the shell total length and the total flesh weight suggesting that an increase in length gives a corresponding increase in weight of an individual oyster. The total length-total weight and total weight-flesh weight relationships were positively correlated with calculated â€œbâ€ of 0.5826 and 0.5887 for combined sexes respectively. Negative allometric growth observed was verified from the b < 3 value. The condition factor of the oysters ranged between 6.5 and 10.5 for both male and female species indicating that the species are in good condition despite reported contaminations of the lagoon water.Keywords: Bivalve, C. tulipa, Lagos Lagoon, length-weight.
Minimization of an energy function with robust features for image segmentation

In this work, we propose an approach to the model based on Markov random field (MRF) as a systematic way for integrating constraints for robust image segmentation. To do that, robust features and their integration in the energy function, which directs the process, have been defined. The suitability of the method has been verified by comparing classic features with the robust ones. In this approach, the image is first segmented into a set of disjoint regions and the adjacent graph (AG) has been determined. This approach is applied by defining an MRF model on the corresponding AG. Robust features are incorporated to the energy function by means of clique functions, and optimal segmentation is then achieved by finding a labelling configuration, which minimizes the energy function using the simulated annealing.
Probing Interleukin-6 in Stroke Pathology and Neural Stem Cell Transplantation

Stem cell transplantation is historically understood as a powerful preclinical therapeutic following stroke models. Current clinical strategies including clot busting/retrieval are limited by their time windows (tissue plasminogen activator: 3–4 h) and inevitable reperfusion injuries. However, 24+ h post-stroke, stem cells reduce infarction size, improve neurobehavioral performance, and reduce inflammatory agents including interleukins. Typically, interleukin-6 (IL-6) is regarded as proinflammatory, and thus, preclinical studies often discuss it as beneficial for neurological recuperation when stem cells reduce IL-6′s expression. However, some studies have also demonstrated neurological benefit with upregulation of IL-6 or preconditioning of stem cells with IL-6. This review specifically focuses on stem cells and IL-6, and their occasionally disparate, occasionally synergistic roles in the setting of ischemic cerebrovascular insults.
Oriented crystal growth on amorphous substrates using artificial surface‐relief gratings

Oriented crystal growth on an amorphous substrate has been achieved using an artificially created surface‐relief grating. Crystallites of KCl grown from a water solution onto a 320‐nm spatial‐period square‐wave grating in SiO2 nucleated preferentially at vertical steps and grew with 〈100〉 directions parallel to the grating axis. It is proposed that artificially created surface microstructures may provide a new means of manipulating the growth and orientation of crystalline overlayers.