Miracle-dz/UniFAR-FTUs huggingface dataset:
Circular Economy Approach in Treatment of Galvanic Wastewater Employing Membrane Processes

According to the idea of sustainable development, humanity should make every effort to care for the natural environment along with economic development. Decreasing water resources in the world makes it necessary to take action to reduce the consumption of this resource. This article presents the results of research conducted to improve the use of recyclable materials in line with the circular economy model. The research focused on the development of a technological solution for the recovery of raw materials from galvanic wastewater. The concept of a galvanic wastewater treatment system presented in the article includes wastewater pre-treatment in the ultrafiltration (UF) process and water recovery in the reverse osmosis (RO) process. In addition, the purpose of the work was to manage post-filtration waste (RO retentate) containing high concentrations of zinc in the process of galvanizing metal details. The obtained results indicate that it is possible to reduce the amount of sewage from the galvanizing industry by reusing the recovered water as technical water in the process line. The carried-out model tests of galvanizing confirmed the possibility of using RO retentate for the production of metal parts. The achieved results are a proposal to solve the problem of reducing the impact of galvanic wastewater on the environment and to improve the profitability of existing galvanizing technologies by reducing the consumption of water and raw materials.
Iterated Function Systems

In the early 1980's, Michael Barnsley introduced the idea of synthesizing a predetermined image as the attractor of a chaotic process. Other researchers had previously shown that chaotic systems were capable of producing fascinating images known as strange attractors. Barnsley, however, was the first to take a step toward solving the inverse problem: Given a specified image, can one come up with a chaotic system that has the given image as its strange attractor? Barnsley used a particular system of mappings which he called an iterated function system (IFS). IFS's are, at best, only a crude form of image compression. It should be stressed that IFS's in their original form, and as they are presented in this chapter, are not the basis of current approaches to fractal image compression (a misconception held by some of the detractors of fractal image compression). However, IFS's were the inspiration for fractal approaches to image compression. And while IFS's are not viable themselves as complete image compression systems, an understanding of IFS theory is essential to understanding how fractal image compression works. In this chapter, we will develop the mathematical background of IFS theory and see how to implement such a system on a computer.
Principally Quasi-Baer Skew Power Series Modules

A module M R is called principally quasi-Baer (or simply p.q.-Baer) if the annihilator of every cyclic submodule of M R is generated by an idempotent, as a right ideal. Let α be an automorphism of R and M R be an α-compatible module and every countable subset of right semicentral idempotents in R has a generalized countable join or R satisfies the ACC on left annihilator ideals. It is shown that M R is p.q. -Baer if and only if M[[x]] R[[x; α]] is p.q. -Baer if and only if M[[x, x −1]] R[[x, x −1; α]] is p.q. -Baer. As a consequence, we unify and extend nontrivially many of the previously known results such as [11, 15, 20]. Examples to illustrate and delimit the theory are provided.
Risk Genetic Variants (IL-10) for Osteoporosis in Han Population from Northwest China

Background Osteoporosis (OP) is a common metabolic bone disease characterized by loss of bone mass. IL-10 is considered to be a powerful immune and inflammatory suppressor. This study aimed to assess association between genetic loci in IL-10 and susceptibility to OP. Methods Association analysis between IL-10 genetic loci and OP risk through SNPStats online software. FPRP analysis (false-positive report probability) verified whether the positive results were noteworthy findings. Linkage disequilibrium (LD) and haplotype analysis were completed by Haploview 4.2 and SNPStats. Multi-factor dimensionality reduction (MDR) was used to assess interaction of SNP–SNP in susceptibility to OP. Results Allele “G” of IL-10-rs1554286 (OR = 1.21, p = 0.013), allele “C” of IL-10-rs1518111 (OR = 1.22, p = 0.011), allele “C” of IL-10-rs3024490 (OR = 1.20, p = 0.018), and allele “G” of IL-10-rs1800871 (OR = 1.21, p = 0.015) were risk factors for OP. In females, smoking, drinking, or aging ≤60 years old participants, the above genetic loci are also significantly associated with the increased risk of OP. FPRP analysis showed that all positive results are noteworthy findings. There are significant differences in serum levels of uric acid, mean hemoglobin concentration, or mean hemoglobin among different genotypes of IL-10 gene loci. MDR showed that four loci model composed rs1554286, rs1518111, rs3021094, and rs1800871 is the best model for predicting OP risk. Conclusion IL-10-rs1554286, -rs1518111, -rs3021094, and -rs1800871 are risk factors for susceptibility to OP.
Graph Metrics Based Brain Hypergraph Learning in Schizophrenia Patients

Hypergraphs have been widely used in the analysis of brain network because of its ability to capture high order interaction among multiple brain regions. Most of the recent work is based on sparse representation to construct hypergraph, in which vertices represent brain regions. This kind of approaches is at the subject-level and does not take account of topological properties. To overcome this limitation, we propose a new method to identify biomarkers helpful to the diagnosis of brain disease. Firstly, we construct a graph-based network for each subject and derive graph metrics. Then we construct a group-level hypergraph based on similarities of topological properties. Graph metrics are introduced to guide the construction of hypergraph. We obtain the weights of each hyperedges by hypergraph learning. We evaluate our framework on the COBRE dataset and achieve good classification accuracy by merely selecting a small amount of features. Moreover, we find that the hyperedges with larger weights and smaller weights show good discriminability. Our method extends the framework of hypergraph learning and reveals the differences caused by the disease at the group-level.
Performance and Agreement When Annotating Chest X-ray Text Reports—A Preliminary Step in the Development of a Deep Learning-Based Prioritization and Detection System

A chest X-ray report is a communicative tool and can be used as data for developing artificial intelligence-based decision support systems. For both, consistent understanding and labeling is important. Our aim was to investigate how readers would comprehend and annotate 200 chest X-ray reports. Reports written between 1 January 2015 and 11 March 2022 were selected based on search words. Annotators included three board-certified radiologists, two trained radiologists (physicians), two radiographers (radiological technicians), a non-radiological physician, and a medical student. Consensus labels by two or more of the experienced radiologists were considered “gold standard”. Matthew’s correlation coefficient (MCC) was calculated to assess annotation performance, and descriptive statistics were used to assess agreement between individual annotators and labels. The intermediate radiologist had the best correlation to “gold standard” (MCC 0.77). This was followed by the novice radiologist and medical student (MCC 0.71 for both), the novice radiographer (MCC 0.65), non-radiological physician (MCC 0.64), and experienced radiographer (MCC 0.57). Our findings showed that for developing an artificial intelligence-based support system, if trained radiologists are not available, annotations from non-radiological annotators with basic and general knowledge may be more aligned with radiologists compared to annotations from sub-specialized medical staff, if their sub-specialization is outside of diagnostic radiology.
Impact of the Fukushima Accident on 3H and 14C Environmental Levels: A Review of Ten Years of Investigation

The investigation of the impact of the Fukushima accident is still going on although more than ten years have passed since the disaster. The main goal of this paper was to summarize the results of tritium and radiocarbon determinations in different environmental samples, possibly connected with the Fukushima Dai-ichi Nuclear Power Plant (FDNPP) accident. A document containing compiled data may serve as a solid basis for further research in the selected fields. To accomplish such effort, we went through dozens of relevant published papers, reporting 3H and 14C activity concentrations in precipitations, groundwater, seawater, river systems, tree rings, and, in some more extraordinary samples, such as herbaceous plants or debris from the damaged reactor buildings. As the referenced results would not be obtainable without adequate analytical techniques, the most common methods for routine measurement of tritium and radiocarbon concentrations are discussed as well. We believe that the correct identification of the affected environmental compartments could help quantify the released 3H and 14C activities and track their following fate, which could be especially important for plans to discharge contaminated water from the FDNPP in the upcoming years.
Extension of rough set under incomplete information systems

The classical rough set theory is based on complete information systems. It classifies objects using upper-approximation and lower-approximation defined on an indiscernibility relation that is a kind of equivalent relation. In order to process incomplete information systems, the classical rough set theory needs to be extended, especially, the indiscernibility relation needs to be extended to some inequivalent relation. There are several extensions for the indiscernibility relation at present, such as tolerance relation, non-symmetric similarity relation, and valued tolerance relation. Unfortunately, these extensions have their own limitation. We develop a new extension of rough set theory that is based on a limited tolerance relation.
Harvest weed seed control in soybean with an impact mill

Abstract The distribution of herbicide-resistant weeds such as waterhemp has resulted in a greater need for a more integrated approach to weed management, especially in U.S. soybean production systems. Previous research has shown harvest weed seed control (HWSC) to be an effective method of reducing the amount of weed seed returning to the soil. One form of HWSC is the use of impact mills to destroy weed seed exiting the combine during harvest. In 2019 and 2020, we investigated the efficacy and operating costs of the Seed TerminatorTM impact mill in five Missouri soybean fields that contained significant waterhemp infestations. Results indicated that 22% to 40% of the available waterhemp seed in the field at harvest drops to the soil surface because of shatter whenever the combine reel contacts waterhemp plants. Across all locations, an average of 94% of waterhemp seed exiting the Seed Terminator™ was substantially damaged and considered nonviable. Consecutive seasons of use of the Seed TerminatorTM on the same field in two of the locations resulted in a 96% to 97% reduction of waterhemp in the soil seed bank the spring following the second harvest. The estimated increased operating cost of using a Seed Terminator™ was $14.18 ha–1 compared to harvesting with a conventional combine alone. Engine load increased by 12.5%, fuel consumption was 11.3 L h–1 and 1 L ha–1 greater with the Seed Terminator™, but there was no reduction in productivity when harvesting with a combine equipped with a Seed TerminatorTM compared to a conventional combine. The use of impact mills could play a significant role in reducing soil weed seed banks in soybean production systems in at least the Midwest region of the United States in the future. Nomenclature: Waterhemp, Amaranthus tuberculatus (Moq.) J.D. Sauer; soybean, Glycine max (L.) Merr.
First O-band silicon coherent transmitter with integrated hybrid tunable laser and SOAs

Scaling data centers to 200 Gbps/lane with direct detection may not provide sufficient link budget for optical switches. Analog coherent detection leverages phase and polarization of optical signals to scale efficiently without requiring digital signal processing and employs integrated lasers to maximize link budgets for optical switches. We report the first O-band silicon photonics coherent transmitter integrated with hybrid semiconductor optical amplifiers and tunable lasers. The laser demonstrated <6 dBm output power with ∼700 kHz linewidths across its 14 nm tuning spectrum. 64 Gbaud QPSK transmission was demonstrated with BER ∼4e-4 and ∼6.6 pJ/bit energy-efficiency when utilizing SiGe BiCMOS drivers.
Stereochemical Properties of Two Schiff-Base Transition Metal Complexes and Their Ligand by Using Multiple Chiroptical Spectroscopic Tools and DFT Calculations

Two transition metal complexes were synthesized with Ni(II) and Cu(II) using a tetradentate Schiff-base ligand, (R,R) and (S,S)-N,N′-Bis(3,5-di-tert-butylsalicylidene)-1,2-cyclohexanediamine. The stereochemical properties of the ligand and the metal complexes were investigated using a combined experimental and theoretical approach. Multiple spectroscopic techniques, which include IR, vibrational circular dichroism (VCD), UV-Vis and electronic circular dichroism (ECD), as well as Raman and the newly discovered ECD-circularly polarized Raman (i.e., eCP-Raman) spectroscopies were utilized. The good agreement achieved between the experimental and simulated IR, VCD, UV-Vis and ECD spectra of the ligand allowed one to identify the presence of three main ligand conformers in solution, thanks, especially to the high VCD sensitivity to the conformations associated with the tertbutyl groups. The helicity of the metal complexes was identified to be M and P for those with the (R,R) and (S,S) ligands, respectively. Furthermore, eCP-Raman measurements were carried out for the two metal complexes under (near) resonance. Their induced solvent chiral Raman features were explained, and the potential application of eCP-Raman was discussed.
“You Enjoy Talking about It More than Doing It”: Fake Narratives in Disdainful Relationships

Research has found that the coercive dominant discourse (CDD) can have a negative impact on girls’ sexual pleasure. In this vein, a previous study found that girls who described relationships under the CDD as exciting also recognized a lack of sexual pleasure in these. One of the elements underlying this apparent contradiction was an identified mismatch between what the participants had experienced in such relationships, characterized for being disdainful, and what they had told their friends. Nonetheless, more research is needed in order to better understand how girls’ narratives about their sexual-affective relationships differ from the ways in which they experienced them. The current study aims at identifying and analysing the presence of fake narratives in the interactions girls have with their peers regarding sexual-affective relationships. To this end, 10 communicative interviews were conducted with girls between 18 and 21 years of age. Results show that while participants recognize feeling a lack of pleasure in those disdainful relationships, they portrayed these as exciting when telling their peers about them, suppressing the negative feelings around them. These findings corroborate the presence of fake narratives in relation to disdainful relationships and bring new insights into the aspects these fabricated stories are built around.
SIRT6 ameliorates LPS-induced apoptosis and tight junction injury in ARDS through the ERK1/2 pathway and autophagy

Sirtuin6 (SIRT6) has been demonstrated to be involved in a range of physiological processes and diseases, while its role in acute respiratory distress syndrome (ARDS) remains unclear. Therefore, this study focused on the role and underlying mechanism of SIRT6 in ARDS with the aim of identifying potential therapeutic targets. In this study, we found that SIRT6 was significantly decreased in lipopolysaccharide (LPS)-induced A549 cells and a murine model. In vitro overexpression of SIRT6 restored the expression of tight junction proteins (ZO-1 and occludin) and alleviated cell apoptosis and inflammation, while knockdown of SIRT6 aggravated the loss of tight junction proteins (ZO-1 and occludin) and promoted cell apoptosis and inflammation in LPS-induced A549 cells. Furthermore, the overexpression of SIRT6 enhanced autophagy and inhibited the ERK1/2 pathway, while the knockdown of SIRT6 inhibited autophagy and activated the ERK1/2 pathway. The autophagy activator rapamycin and the ERK1/2 inhibitor PD98059 rescued the effects of SIRT6 knockdown on tight junction proteins, apoptosis, and inflammation. Mechanistically, SIRT6 deacetylated histone 3 at Lys9 to negatively regulate the ERK1/2 pathway. In vivo, the SIRT6-specific inhibitor OSS_128167 also significantly accelerated LPS-induced loss of tight junction proteins, lung inflammation, and apoptosis. Meanwhile, the SIRT6-specific inhibitor OSS_128167 also activated the ERK1/2 pathway and inhibited lung autophagy. These results suggested that SIRT6 could ameliorate the loss of tight junction proteins, inflammation, and apoptosis in LPS-induced ARDS by inhibiting the ERK1/ 2 pathway and enhancing autophagy, indicating that SIRT6 plays a beneficial role in ARDS and might be a potential therapeutic target for ARDS.
Artificial intelligence-based 68Ga-DOTATOC PET denoising for optimizing 68Ge/68Ga generator use throughout its lifetime

Introduction The yield per elution of a 68Ge/68Ga generator decreases during its lifespan. This affects the number of patients injected per elution or the injected dose per patient, thereby negatively affecting the cost of examinations and the quality of PET images due to increased image noise. We aimed to investigate whether AI-based PET denoising can offset this decrease in image quality parameters. Methods All patients addressed to our PET unit for a 68Ga-DOTATOC PET/CT from April 2020 to February 2021 were enrolled. Forty-four patients underwent their PET scans according to Protocol_FixedDose (150 MBq) and 32 according to Protocol_WeightDose (1.5 MBq/kg). Protocol_WeightDose examinations were processed using the Subtle PET software (Protocol_WeightDoseAI). Liver and vascular SUV mean were recorded as well as SUVmax, SUVmean and metabolic tumour volume (MTV) of the most intense tumoural lesion and its background SUVmean. Liver and vascular coefficients of variation (CV), tumour-to-background and tumour-to-liver ratios were calculated. Results The mean injected dose of 2.1 (0.4) MBq/kg per patient was significantly higher in the Protocol_FixedDose group as compared to 1.5 (0.1) MBq/kg for the Protocol_WeightDose group. Protocol_WeightDose led to noisier images than Protocol_FixedDose with higher CVs for liver (15.57% ± 4.32 vs. 13.04% ± 3.51, p = 0.018) and blood-pool (28.67% ± 8.65 vs. 22.25% ± 10.37, p = 0.0003). Protocol_WeightDoseAI led to less noisy images than Protocol_WeightDose with lower liver CVs (11.42% ± 3.05 vs. 15.57% ± 4.32, p < 0.0001) and vascular CVs (16.62% ± 6.40 vs. 28.67% ± 8.65, p < 0.0001). Tumour-to-background and tumour-to-liver ratios were lower for protocol_WeightDoseAI: 6.78 ± 3.49 vs. 7.57 ± 4.73 (p = 0.01) and 5.96 ± 5.43 vs. 6.77 ± 6.19 (p < 0.0001), respectively. MTVs were higher after denoising whereas tumour SUVmax were lower: the mean% differences in MTV and SUVmax were + 11.14% (95% CI = 4.84–17.43) and −3.92% (95% CI = −6.25 to −1.59). Conclusion The degradation of PET image quality due to a reduction in injected dose at the end of the 68Ge/68Ga generator lifespan can be effectively counterbalanced by using AI-based PET denoising.
Dimension-Invariant Dynamic Term Structures ∗

We develop a class of dynamic term structure models that accommodates arbitrarily many interest-rate factors with very few parameters. The model builds on a short-rate cascade, a parsimonious recursive structure that naturally ranks the latent state variables b y their rates of mean reversion, each revolving around the next lowest-frequency factor. With appropriate assumptions on volatilities and risk premia, the model overcomes the curse of dimensionality associated with general affine models. Using a panel of 15 LIBOR and swap rates, we estimate models using from one to 15 factors and only five parameters. The in-sample fit of high-dimensional specifications is near exact, with absolute pricing errors averaging less than one basis point, permitting yield-curve strippin g in an arbitrage-free, dynamically consistent environment. Cross-maturity correlations accurately reflec t empirical evidence, and out-of-sample interest rate forecasts significantly improve on prior benchmarks.
The Rate of Convergence of the Mean Length of the Longest Common Subsequence

Given two i.i. d. sequences of n letters from a finite alphabet, one can consider the length Ln of the longest sequence which is a subsequence of both the given sequences. It is known that ELn grows like yn for some y E [0, 1]. Here it is shown that yn ? ELn ? yn C(n log n)l/2 for an explicit numerical constant C which does not depend on the distribution of the letters. In simulations with n = 100,000, ELn/n can be determined from k such trials with 95% confidence to within 0.0055/ k, and the results here show that y can then be determined with 95% confidence to within 0.0225 + 0.0055/ k, for an arbitrary letter distribution.
Early diagnosis of neural impairment in seropositive leprosy household contacts: The experience of a reference center in Brazil

Introduction Leprosy is an infectious disease that remains with a high number of new cases in developing countries. Household contacts have a higher risk for the development of the disease, but the neural impairment in this group is not well elucidated yet. Here, we measured the chance of occurrence of peripheral neural impairment in asymptomatic leprosy household. Methods Contacts who present anti-PGL-I IgM seropositivity, through electroneuromyography (ENMG) evaluation. We recruited 361 seropositive contacts (SPC) from 2017 to 2021, who were subjected to an extensive protocol that included clinical, molecular, and electroneuromyographic evaluations. Results Our data revealed a positivity of slit skin smear and skin biopsy qPCR of 35.5% (128/361) and 25.8% (93/361) respectively. The electroneuromyographic evaluation of the SPC showed neural impairment in 23.5% (85/361), with the predominance of a mononeuropathy pattern in 62.3% (53/85). Clinical neural thickening was observed in 17.5% (63/361) of seropositive contacts, but among the individuals with abnormal ENMG, only 25.9% (22/85) presented neural thickening in the clinical exam. Discussion Ours results corroborates the need to make the approach to asymptomatic contacts in endemic countries more timely. Since leprosy in its early stages can present an indolent and subclinical evolution, serological, molecular, and neurophysiological tools are essential to break the disease transmission chain.