Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of DNA Extraction Methods for Reliable Quantification of Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa

Detection and quantification of DNA biomarkers relies heavily on the yield and quality of DNA obtained by extraction from different matrices. Although a large number of studies have compared the yields of different extraction methods, the repeatability and intermediate precision of these methods have been largely overlooked. In the present study, five extraction methods were evaluated, using digital PCR, to determine their efficiency in extracting DNA from three different Gram-negative bacteria in sputum samples. The performance of two automated methods (GXT NA and QuickPick genomic DNA extraction kit, using Arrow and KingFisher Duo automated systems, respectively), two manual kit-based methods (QIAamp DNA mini kit; DNeasy UltraClean microbial kit), and one manual non-kit method (CTAB), was assessed. While GXT NA extraction kit and the CTAB method have the highest DNA yield, they did not meet the strict criteria for repeatability, intermediate precision, and measurement uncertainty for all three studied bacteria. However, due to limited clinical samples, a compromise is necessary, and the GXT NA extraction kit was found to be the method of choice. The study also showed that dPCR allowed for accurate determination of extraction method repeatability, which can help standardize molecular diagnostic approaches. Additionally, the determination of absolute copy numbers facilitated the calculation of measurement uncertainty, which was found to be influenced by the DNA extraction method used.
Multiplex RT Real-Time PCR Based on Target Failure to Detect and Identify Different Variants of SARS-CoV-2: A Feasible Method That Can Be Applied in Clinical Laboratories

Shortly after its emergence, Omicron and its sub-variants have quickly replaced the Delta variant during the current COVID-19 outbreaks in Vietnam and around the world. To enable the rapid and timely detection of existing and future variants for epidemiological surveillance and diagnostic applications, a robust, economical real-time PCR method that can specifically and sensitively detect and identify multiple different circulating variants is needed. The principle of target- failure (TF) real-time PCR is simple. If a target contains a deletion mutation, then there is a mismatch with the primer or probe, and the real-time PCR will fail to amplify the target. In this study, we designed and evaluated a novel multiplex RT real-time PCR (MPL RT-rPCR) based on the principle of target failure to detect and identify different variants of SARS-CoV-2 directly from the nasopharyngeal swabs collected from COVID-19 suspected cases. The primers and probes were designed based on the specific deletion mutations of current circulating variants. To evaluate the results from the MPL RT-rPCR, this study also designed nine pairs of primers for amplifying and sequencing of nine fragments from the S gene containing mutations of known variants. We demonstrated that (i) our MPL RT-rPCR was able to accurately detect multiple variants that existed in a single sample; (ii) the limit of detection of the MPL RT-rPCR in the detection of the variants ranged from 1 to 10 copies for Omicron BA.2 and BA.5, and from 10 to 100 copies for Delta, Omicron BA.1, recombination of BA.1 and BA.2, and BA.4; (iii) between January and September 2022, Omicron BA.1 emerged and co-existed with the Delta variant during the early period, both of which were rapidly replaced by Omicron BA.2, and this was followed by Omicron BA.5 as the dominant variant toward the later period. Our results showed that SARS-CoV-2 variants rapidly evolved within a short period of time, proving the importance of a robust, economical, and easy-to-access method not just for epidemiological surveillance but also for diagnoses around the world where SARS-CoV-2 variants remain the WHO’s highest health concern. Our highly sensitive and specific MPL RT-rPCR is considered suitable for further implementation in many laboratories, especially in developing countries.
Deep learning for differentiating benign from malignant tumors on breast-specific gamma image

BACKGROUND: Breast diseases are a significant health threat for women. With the fast-growing BSGI data, it is becoming increasingly critical for physicians to accurately diagnose benign as well as malignant breast tumors. OBJECTIVE: The purpose of this study is to diagnose benign and malignant breast tumors utilizing the deep learning model, with the input of breast-specific gamma imaging (BSGI). METHODS: A benchmark dataset including 144 patients with benign tumors and 87 patients with malignant tumors was collected and divided into a training dataset and a test dataset according to the ratio of 8:2. The convolutional neural network ResNet18 was employed to develop a new deep learning model. The model proposed was compared with neural network and autoencoder models. Accuracy, specificity, sensitivity and ROC were used to evaluate the performance of different models. RESULTS: The accuracy, specificity and sensitivity of the model proposed are 99.1%, 98.8% and 99.3% respectively, which achieves the best performance among all methods. Additionally, the Grad-CAM method is used to analyze the interpretability of the diagnostic results based on the deep learning model. CONCLUSION: This study demonstrates that the proposed deep learning method could help physicians diagnose benign and malignant breast tumors quickly as well as reliably.
Rhodium-Catalyzed Trans-Bis-Silylation Reactions of 2-Ethynyl-3-pentamethyldisilanylpyridines

Rhodium-catalyzed reactions of 2-ethynyl-3-pentamethyldisilanylpyridine derivatives (1 and 2) are reported. The reactions of compounds 1 and 2 in the presence of catalytic amounts of rhodium complexes at 110 °C gave the corresponding pyridine-fused siloles (3) and (4) through intramolecular trans-bis-silylation cyclization. The reaction of 2-bromo-3-(1,1,2,2,2-pentamethyldisilanyl)pyridine with 3-phenyl-1-propyne in the presence of PdCl2(PPh3)2-CuI catalysts afforded 1:2 bis-silylation adduct 6. DFT calculations were also performed to understand the reaction mechanism for the production of compound 3 from compound 1.
Global Optimisation in PCA Shape Space Using Level Sets

Purpose Statistical shape models have been widely used for image segmentation and shape estimation from sparse sets of landmarks [1,2]. Existing works on optimisation in shape space aim at finding a single instance from the statistical shape model that best approximates the input data, subject to some regularisation constraint. In certain cases, it may be interesting to find all instances of the shape model that meet a certain criterion. For example, one may be interested in estimating which range of population falls within a given anatomical criterion, thus establishing a partition of the shape space into “valid” and “invalid” shapes. In this work, we propose a method for global optimisation of shape constraints that effectively finds all instances in the PCA (principal component analysis) shape space that meet a certain criterion.
Scheduling in a Semi-Ordered Flow-shop Without Intermediate Queues

Abstract The problem of finding a minimum makespan permutation schedule in a deterministic flow-shop without intermediate queues is equivalent to the shortest distance routing traveling salesman problem. If the task system is semi-ordered, the associated distance matrix of the corresponding traveling salesman problem is found to exhibit some peculiar characteristics. Consequently, we are able to derive some important results which help us to eliminate permutations in the search of the minimum makespan permutation schedule. The most important result is that the optimal permutation schedule is pyramidal. An algorithm, having quadratic worst-case complexity in terms of the number of partial schedules explicitly enumerated, has been presented. Some particular cases of the semi-ordered flow-shop are also discussed.
Generating simulated fluorescence images for enhancing proteins from optical microscopy images of cells using massive-training artificial neural networks

Fluorescence imaging is used to visualize biological processes at molecular and cellular level. However, it has several limitations e.g., potential toxicity of fluorescent dyes, photobleaching and sensitivity to the environment. On the contrary, differential interference contrast (DIC) microscopes provide pseudo-3D images by enhancing contrast in unstained specimens and are harmless, and non-invasive compared to fluorescence imaging. This study proposes a massive-training artificial neural network (MTANN) scheme to generate simulated fluorescence images from DIC images. Experimental results showed that the proposed method generated fluorescence images of the proteins (sum of troponin T and vimentin) with SSIM value 0.878 which is close to the corresponding ‘gold standard’ images. Thus, it can be said that the proposed method contributes to harmless cell imaging.
Association between statin use and risk of gallstone disease and cholecystectomy: a meta-analysis of 590,086 patients

Background Statins have been reported to reduce the risk of gallstone disease. However, the impacts of different durations of statin use on gallstone disease have not been clarified. The aim of this study is toperform a systematic review with meta-analysis to update and to elucidate the association between statin use and the risk of gallstone disease and cholecystectomy. Methods Medline, Embase and Cochrane Library were searched from the inception until August 2022 for relevant articles investigating the difference in the risk of gallstone disease between statin users and non-users (PROSPERO, ID: CRD42020182445). Meta-analyses were conducted using odds ratios (ORs) with corresponding 95% confidence intervals (CIs) to compare the risk of gallstone disease and cholecystectomy between statin user and nonusers. Results Eight studies enrolling 590,086 patients were included. Overall, the use of statins was associated with a marginally significant lower risk of gallstone disease than nonusers (OR, 0.91; 95% CI [0.82–1.00]). Further subgroup analysis showed that short-term users, medium-term users, and long-term users were associated with a significantly higher risk (OR, 1.18; 95% CI [1.11–1.25]), comparable risk (OR, 0.93; 95% CI [0.83–1.04]), and significantly lower risk of gallstone diseases (OR, 0.78; 95% CI [0.68–0.90]) respectively, compared to nonusers. Conclusions Patients with medium-term or long-term use of statins without discontinuation are at a lower risk of gallstone disease or cholecystectomy.
Relaxations of Sparse Polynomial Optimization Problems

Sequences of generalized Lagrangian duals and their SOS (sums of squares of polynomials) relaxations for a POP (polynomial optimization problem) are introduced. Sparsity of polynomials in the POP is used to reduce the sizes of the Lagrangian duals and their SOS relaxations. It is proved that the optimal values of the Lagrangian duals in the sequence converge to the optimal value of the POP using a method from the penalty function approaches. The sequence of SOS relaxations is transformed into a sequence of SDP (semidenite program) relaxations of the POP, which correspond to duals of modication and generalization of SDP relaxations given by Lasserre for the POP.
Hamiltonian Cycles in Strong Products of Graphs

Abstract. Let denote the graph (k times) where is the strong product of the two graphs G and H. In this paper we prove the conjecture of J. Zaks [3]: For every connected graph G with at least two vertices there exists an integer k = k(G) for which the graph is hamiltonian.
An Operad Action on Infinite Loop Space Multiplication

It is well-known that an infinite loop space is an H-space whose multiplication enjoys nice properties concerning associativity and commutativity. A practical way of identifying infinite loop spaces is the utilization of May's recognition principle [3; 4]. To apply this principle, one requires an E∞-operad action on a space X; this action gives rise to various multiplications on X. In this note, it is shown that such multiplications enjoy an operad action up to homotopy that encodes the associativity and commutativity information, and that May's delooping theorem may be applied to them. We refer to [3] for the terminology of operads and monads.
BER analysis on different channel based on OFDM and MIMO system

Additive white Gaussian noise (AWGN) is utilized as a variation attribution for various procedures which may be random. It can be added with various noises to make the framework natural. Rayleigh fading is utilized to demonstrate the engendering model which can represent nonlinearity and scrambling. This major combination can be more successful when it can be tried with various adjustments in modulation. It is additionally compelling for the noise reduction. The data transmission with orthogonal frequency division multiplexing (OFDM) and multiple inputs and multiple outputs (MIMO) will be effective in the conjunction of AWGN and Rayleigh fading channel. This paper focuses on various attributes which can reduce the error rates with the help of bit error rate (BER).
Top-gated graphene field-effect transistors by low-temperature synthesized SiNx insulator on SiC substrates

Top-gated devices made from an epitaxial graphene film on a 4H-SiC substrate were fabricated. Atomic force microscopy and Raman spectroscopy results showed that a large-scale highly uniform monolayer graphene film was synthesized on the SiC substrate. A SiNx passivation film was deposited on a SiC graphene device as a top gate insulator by catalytic chemical-vapor deposition (Cat-CVD) below 65 °C. After the top gate electrode was formed on the SiNx film, no leakage current flowed between the gate and source electrodes. The transport characteristics showed clear ambipolar characteristics from 8 to 280 K, and the temperature dependences of the conductance and field-effect mobility of the devices implied that monolayer graphene devices can be successfully fabricated. Moreover, the position of the charge neutrality point after SiNx deposition was around 0 V, indicating p-doping characteristics. These results indicate that SiNx films synthesized by Cat-CVD can be used as gate insulators and that the carrier type may be controlled by adjusting the deposition conditions.
A NOTE ON THE REPRESENTATION OF ORDERED METRIC SCALING

A unidimensional ordered metric scaling (Coombs, 1964) of a set of objects is an ordinal scaling of them and also a (partial or complete) ordinal scaling of the distances between them. The problem of representing such a scaling reduces to that of finding the general solution of a system of strict homogeneous linear inequalities. There are two possible approaches to the latter problem. The purely algebraic approach of Fourier (1890), which is a modification of the usual method (systematic elimination) for the solution of systems of linear equations, is computationally simple, but does not give a satisfactory representation of the general solution, only an inconvenient and non-unique set of back substitutions. The coordinate-geometric approach of Minkowski (1896), upon which Stokes' (1931) method of solution is based, gives a matrix representation of the general solution, but is computationally very laborious. However, an unpublished algorithm due to Goode (Coombs, 1964), although incomplete in its original form, turns out, when completed by the application of a theorem of Farkas (1902), to be essentially equivalent to Stokes' method, but computationally very simple, the only (slight) disadvantage being that it may give superfluous solutions, which are easily excluded by a simple check.
Human capital and economic growth in Central Asia

ABSTRACT This study explores the long-term economic performance in former Soviet republics of Central Asia for the last three decades. We look at sources of economic growth based on the extended version of the neoclassical growth model. Our key focus is to see whether human capital in the form of education and health inputs has an impact on growth rates in the region. Results show that over the entire period under study, on average, the growth rates of total factor productivity (TFP) were not remarkable, ranging from 1.4% for Kazakhstan and 0.51% for Tajikistan to −1.13% for the Kyrgyz Republic. Kazakhstan as a frontier economy of the region maintained better economic results in almost all indicators. Since 2000, TFP growth rates were notably stronger in Tajikistan compared to Kazakhstan and the Kyrgyz Republic. However, a reduction in TFP in Tajikistan in the 1990s is attributed to the country’s dire civil war.
Multi-Phase Texture Segmentation Using Gabor Features Histograms Based on Wasserstein Distance

We present a multi-phase image segmentation method based on the histogram of the Gabor feature space, which consists of a set of Gabor-ﬁlter responses with various orientations, scales and frequencies. Our model replaces the error function term in the original fuzzy region competition model with squared 2-Wasserstein distance function, which is a metric to measure the distance of two histograms. The energy functional is minimized by alternative minimization method and the existence of closed-form solutions is guaranteed when the exponent of the fuzzy membership term being 1 or 2. We test our model on both simple synthetic texture images and complex natural images with two or more phases. Experimental results are shown and compared to other recent results.
Ready-to-Eat Innovative Legumes Snack: The Influence of Nutritional Ingredients and Labelling Claims in Italian Consumers’ Choice and Willingness-to-Pay

The global offer of legume-based snacks has sharply increased in recent years. However, to date, few studies have focused on the relationship between product supply and demand concerning the importance of attributes of such innovative foods. In this research, we identified the key internal and external determinants that affect legumes snack (LS) price and choice by Italian industries and consumers, respectively. In parallel, we investigated their preferences and perceptions towards these foods. We used the hedonic price model (HPM) and the discrete choice experiment (DCE) approach for these purposes, respectively. HPM revealed that the monetary value of LS was determined to greater significance by the: (i) size of the package; (ii) presence of rice, presence of lentils; (iii) presence of the nutritional information; and (iv) the discount shops as site of purchase. DCE revealed that the: (i) origin certification, (ii) recyclability of the package, and (iii) use of extra virgin olive oil of LS provided Italian consumers a high utility, for which they were willing to pay an average price premium of EUR 3.85, 3.64, and 1.87, respectively. On the contrary, the sunflower oil induced a decrease in their function utility. As such, this paper contributes to define potent market-segmentation strategies and to deliver effective private and public nutrition interventions for healthy eating.
Spatial Load Forecasting for Distribution Networks Based on Rough Sets and Cellular Automata

A new spatial load forecasting(SLF) method for distribution network by using cellular automata(CA) theory to simulate the process of urban land-use dynamic development and forecast future land-use types of each small-area is introduced.The iteration time and adjusting time of transition rules of CA are determined by the practical situation of urban development.In order to eliminate redundancies,overcome faults such as land-use rules which are always static and suffer influence from subjectivity by traditional methods,rough sets(RS) theory is used to carry out step-by-step attribute reduction for potential influencing factors and obtain dynamic transition rules of CA.Finally,the validity of this method is validated by an actual example.
Selection of preferred thermal environment and cold-avoidance responses in rats rely on signals transduced by the dorsal portion of the lateral funiculus of the spinal cord

ABSTRACT Thermoregulatory behaviors are powerful effectors for core body temperature (Tc) regulation. We evaluated the involvement of afferent fibers ascending through the dorsal portion of the lateral funiculus (DLF) of the spinal cord in “spontaneous” thermal preference and thermoregulatory behaviors induced by thermal and pharmacological stimuli in a thermogradient apparatus. In adult Wistar rats, the DLF was surgically severed at the first cervical vertebra bilaterally. The functional effectiveness of funiculotomy was verified by the increased latency of tail-flick responses to noxious cold (−18°C) and heat (50°C). In the thermogradient apparatus, funiculotomized rats showed a higher variability of their preferred ambient temperature (Tpr) and, consequently, increased Tc fluctuations, as compared to sham-operated rats. The cold-avoidance (warmth-seeking) response to moderate cold (whole-body exposure to ~17°C) or epidermal menthol (an agonist of the cold-sensitive TRPM8 channel) was attenuated in funiculotomized rats, as compared to sham-operated rats, and so was the Tc (hyperthermic) response to menthol. In contrast, the warmth-avoidance (cold-seeking) and Tc responses of funiculotomized rats to mild heat (exposure to ~28°C) or intravenous RN-1747 (an agonist of the warmth-sensitive TRPV4; 100 μg/kg) were unaffected. We conclude that DLF-mediated signals contribute to driving spontaneous thermal preference, and that attenuation of these signals is associated with decreased precision of Tc regulation. We further conclude that thermally and pharmacologically induced changes in thermal preference rely on neural, presumably afferent, signals that travel in the spinal cord within the DLF. Signals conveyed by the DLF are important for cold-avoidance behaviors but make little contribution to heat-avoidance responses.
Clinician-interactive AI for RECIST measurements in CT imaging

The RECIST criteria are used in computed tomography (CT) imaging to assess changes in tumour burden induced by cancer therapeutics throughout treatment. One of its requirements is frequent measurement of lesion diameters , which is often time consuming for clinicians. We aimed to study clinician-interactive AI, defined as deep learning models that use image annotations as input to assist in radiological measurements. Two annotation types are compared in their enhancement of predictive capabilities: mouse clicks in the tumour region, and bounding boxes surrounding lesions. The model architectures compared in this study are the U-Net, V-Net, AH-Net, and SegRes-Net. Models were trained and tested using a non-small cell lung cancer dataset from the cancer imaging archive (TCIA) consisting of CT scans and corresponding gold-standard lesion segmentations inferred from PET/CT scans. Mouse clicks and bounding boxes, representing clinician input, were artificially generated. The absolute percent error between predicted and ground truth diameters was computed for each model architecture. Bounding box annotations yielded mean absolute percent errors of 4.9 ± 2.1 %, 7.8 ± 3.4 %, 5.6 ± 2.4 % and 5.6 ± 2.3 %, respectively, whereas models using clicks annotations yielded 17.0 ± 7.9 %, 19.8 ± 9.3 %, 21.4 ± 10.9 % and 18.1 ± 7.9%. The corresponding mean dice scores across all model architectures were 0.883 ± 0.004 and 0.760 ± 0.012 for bounding box and click annotations respectively. Models were then implemented in an AI pipeline for clinical use at the BC cancer agency using the Ascinta software package; click annotations yielded qualitatively better results than bounding box annotations.