Miracle-dz/UniFAR-FTUs huggingface dataset:
Tyrosinase Magnetic Cross-Linked Enzyme Aggregates: Biocatalytic Study in Deep Eutectic Solvent Aqueous Solutions

In the field of biocatalysis, the implementation of sustainable processes such as enzyme immobilization or employment of environmentally friendly solvents, like Deep Eutectic Solvents (DESs) are of paramount importance. In this work, tyrosinase was extracted from fresh mushrooms and used in a carrier-free immobilization towards the preparation of both non-magnetic and magnetic cross-linked enzyme aggregates (CLEAs). The prepared biocatalyst was characterized and the biocatalytic and structural traits of free tyrosinase and tyrosinase magnetic CLEAs (mCLEAs) were evaluated in numerous DES aqueous solutions. The results showed that the nature and the concentration of the DESs used as co-solvents significantly affected the catalytic activity and stability of tyrosinase, while the immobilization enhanced the activity of the enzyme in comparison with the non-immobilized enzyme up to 3.6-fold. The biocatalyst retained the 100% of its initial activity after storage at −20 °C for 1 year and the 90% of its activity after 5 repeated cycles. Tyrosinase mCLEAs were further applied in the homogeneous modification of chitosan with caffeic acid in the presence of DES. The biocatalyst demonstrated great ability in the functionalization of chitosan with caffeic acid in the presence of 10% v/v DES [Bet:Gly (1:3)], enhancing the antioxidant activity of the films.
Effect of chip temperature during bonding on particleboard properties

In the production of particleboard, the chips emerging from the drying oven usually pass into the bonding process without sufficiently cooling down. Moreover, along with the effect of friction during the bonding process, the increased chip temperature boosts the consumption of resin/adhesive and affects the properties of the board. This study investigated the effect of chip temperature during the bonding process on the properties of particleboard. With this aim, the effects were determined for six different temperatures (25 °C, 30 °C, 35 °C, 40 °C, 50 °C, 55 °C) measured during the bonding of the chips. According to the results, optimum board properties were obtained from the groups in which the chip temperature measured during the bonding process was 30 °C - 40 °C. Furthermore, it was determined that chip temperatures of above 40 °C during the bonding process significantly reduced the mechanical properties .
THE DARBOUX TRANSFORMATION AND HIGHER-ORDER ROGUE WAVE MODES FOR A DERIVATIVE NONLINEAR SCHRÖDINGER EQUATION

We derive the n-th order solution of the mixed Chen-Lee-Liu derivative nonlinear Schrödinger equation (CLL-NLS) by applying the Darboux transformation (DT). Such solutions together with the n-fold DT, represented by Tn, are given in terms of determinant representation, whose entries are expressed by eigenfunctions associated with the initial “seed” solutions. This kind of DT technique is not common, since Tn is related to an overall factor expressed by integrals of previous potentials in the procedure of iteration. As next step, we annihilate these integrals in the overall factor of Tn, except the only one depending on the initial “seed” solution, which can be easily calculated under the reduction condition. Furthermore, the formulae for higher-order rogue wave solutions of the CLL-NLS are obtained according to the Taylor expansion, evaluated at a specific eigenvalue. As possible applications, the expressions and figures of non-vanishing boundary solitons, breathers and a hierarchy of rogue wave solutions are presented. In addition, we discuss the localization characters of rogue wave by defining their length and width. In particular, we show that these localization characters of the first-order rogue wave can be changed by the self-steepening effect in the CLL-NLS by use of an analytical and a graphical method.
Temozolomide Resistance in Glioblastoma by NRF2: Protecting the Evil

The transcription factor NRF2 is constitutively active in glioblastoma, a highly aggressive brain tumor subtype with poor prognosis. Temozolomide (TMZ) is the primary chemotherapeutic agent for this type of tumor treatment, but resistance to this drug is often observed. This review highlights the research that is demonstrating how NRF2 hyperactivation creates an environment that favors the survival of malignant cells and protects against oxidative stress and TMZ. Mechanistically, NRF2 increases drug detoxification, autophagy, DNA repair, and decreases drug accumulation and apoptotic signaling. Our review also presents potential strategies for targeting NRF2 as an adjuvant therapy to overcome TMZ chemoresistance in glioblastoma. Specific molecular pathways, including MAPKs, GSK3β, βTRCP, PI3K, AKT, and GBP, that modulate NRF2 expression leading to TMZ resistance are discussed, along with the importance of identifying NRF2 modulators to reverse TMZ resistance and develop new therapeutic targets. Despite the significant progress in understanding the role of NRF2 in GBM, there are still unanswered questions regarding its regulation and downstream effects. Future research should focus on elucidating the precise mechanisms by which NRF2 mediates resistance to TMZ, and identifying potential novel targets for therapeutic intervention.
Evaluation of Optimised Centres of Rotation Skinning

In this paper we evaluate the real-time skeletal skinning technique Optimised Centres of Rotation Skinning (CRS) in terms of animation quality and efficiency. Skeletal animation rigidly deforms static meshes, letting them perform rigid movements without requiring additional geometry and make it a core part of movies and video games. Linear Blend Skinning (LBS) is the simplest and most intuitive implementation for appropriate vertex transformation. The popular extension Dual Quaternion Skinning (DQS) resolves the volume loss of LBS but introduces new artefacts. These are addressed by the recent CRS showing promising results. Our source code for LBS, DQS and especially CRS will be made public on our website.
Research on Fault Diagnosis of Highway Bi-LSTM Based on Attention Mechanism

Deep groove ball bearings are widely used in rotary machinery. Accurate for bearing faults diagnosis is essential for equipment maintenance. For common depth learning methods, the feature extraction of inverse time domain signal direction and the attention to key features are usually ignored. Based on the long short term memory(LSTM) network, this study proposes an attention-based highway bidirectional long short term memory (AHBi-LSTM) network for fault diagnosis based on the raw vibration signal. By increasing the Attention mechanism and Highway, the ability of the network to extract features is increased. The bidirectional LSTM network simultaneously extracts the raw vibration signal in positive and inverse time-domains to better extract the fault features. Six deep groove ball bearings with different health conditions were used to validate the AHBi-LSTM method in an experiment. The results showed that the accuracy of the proposed method for bearing fault diagnosis was over 98%, which was 8.66% higher than that of the LSTM model. The AHBi-LSTM model is also better than other relevant models for bearing fault diagnosis.
Optical insight into riverine influences on dissolved and particulate organic carbon in a coastal Arctic lagoon system

Optical properties of seawater can provide valuable insight into distributions of dissolved organic carbon (DOC) and particulate organic carbon (POC), provided that their interrelationships are well understood. We examined relationships between DOC and POC, and absorption, backscatter, and ﬂuorescence in a river-fed lagoon system in the coastal Alaskan Arctic during late summer of 2018 and 2019. Over both years analytically measured DOC levels were inversely correlated with salinity (r2 = 0.97) and DOC was positively correlated with dissolved organic material ﬂuorescence (fDOM; r2 = 0.67). However, DOC showed strong correlation with the absorption coeﬃcient at 440 nm (ag(440)) only in 2018 (r2 = 0.95 versus r2 = 0.00056 in 2019). Vertical structure of fDOM in our study area corresponded with density proﬁles more strongly in 2018 than in 2019, but higher levels of fDOM, ag(440), and backscatter near the bottom in 2019 suggest prior wind-driven mixing or bottom resuspension events. In 2018 and 2019, the spectral slope of the absorption coeﬃcient between 412 and 550 nm was strongly correlated with DOC concentration (r2 = 0.70), and spectral backscattering coeﬃcients were well correlated with POC concentration (r2 = 0.90, 0.71, and 0.59 for 470, 532, and 660 nm respectively). These interannual patterns in the distribution of DOC and POC and their respective relationships with optical proxies likely reﬂect regional climatological factors such as precipitation over the adjacent watersheds, wind patterns, and residual sea ice in late summer.
Sonographic Diagnosis and Management With Delayed Hysterectomy of Two Cesarean Scar Pregnancies That Developed Into Placenta Percreta: Two Case Reports

Approximately two-thirds of the patients with a cesarean scar pregnancy (CSP) will develop placenta accreta spectrum (PAS). PAS occurs when the placenta attaches too deeply to the uterine wall, and sometimes, the placenta can extend beyond the uterus, invading surrounding organs. PAS is commonly managed with a cesarean hysterectomy, and these deliveries are often complicated by maternal and fetal morbidity and mortality. However, delaying hysterectomy and using chemotherapeutic agents may be a safe and beneficial alternative. We describe the case of a 32 -year-old G3P2002 with a history of two prior cesarean sections (CS) who was referred to our Maternal Fetal Medicine department due to the concern of a gestational sac embedded in the anterior uterine wall in the cesarean scar. Magnetic resonance imaging (MRI) findings at 33 weeks confirmed that the patient had developed placenta percreta extending into the sigmoid colon. We also describe the case of a 30-year-old G6P4104 with a history of four prior CS who was referred to our department for concern of a pregnancy complicated by CSP. This patient had an MRI performed at 23 weeks that showed placenta percreta invading the bladder. Patients one and two were managed with a staged procedure, with CS followed by a delayed laparoscopic and abdominal hysterectomy, respectively, to minimize bowel and bladder injury. After the CS, the patients subsequently received a five-day course of intravenous (IV) etoposide 100mg/m2, and at six weeks postpartum, the patients had a hysterectomy, both showing resolution of the placenta invasion into the surrounding organs on postpartum MRI and confirmed by tissue pathology reports. Our cases present the challenge in diagnosis and management of the most severe presentation of PAS that varies from the generally accepted management recommendations. Delayed hysterectomy with chemotherapy can be a reasonable, conservative surgical approach in the most severe types of PAS. As in our cases, this management could improve maternal and fetal morbidity and mortality.
What predicts skill transfer? An exploratory study of goal orientation, training self-efficacy and organizational supports

Results from a study examining the predictors of skill transfer from an instructional to a work environment are presented. Prior research indicates that skill transfer is a function of both individual and contextual factors. A total of 186 employees from a work organization were surveyed on individual dimensions (goal orientation, training self-efficacy) and contextual factors (supervisor and peer support). Pre-training motivation was proposed as proximal training outcome and further connected to the distal outcome, skill transfer. Analyses with structural equation modeling using EQS indicate that individual dimensions, such as mastery-approach goal orientation and training self-efficacy, are related to pre-training motivation. Also, contextual factors, such as peer support, predicted both pre-training motivation and skill transfer, while supervisor support was unrelated to either pre-training motivation or skill transfer. Pre-training motivation, in turn, was related to skill transfer. Implications for theory and practice are discussed.
Distribution of the busy period in a controllable M/M/2 queue operating under the triadic (0, K, N, M) policy

We consider an M/M/2 queueing system with removable service stations operating under steady-state conditions. We assume that the number of operating service stations can be adjusted at customers' arrival or service completion epochs depending on the number of customers in the system. The objective of this paper is to obtain the distribution of the busy period using the theory of the gambler's ruin problem. As special cases, the distributions of the busy periods for the ordinary M/M/2 queueing system, the M/M/1 queueing system operating under the N policy and the ordinary M/M/1 queueing system are obtained.
Kernel-Trick Regression and Classification

Abstract Support vector machine (SVM) is a well known kernel-trick supervised learning tool. This study proposes aworking scheme for kernel-trick regression and classiﬁcation (KtRC) as a SVM alternative. KtRC ﬁts the modelon a number of random subsamples and selects the best model. Empirical examples and a simulation studyindicate that KtRC’s performance is comparable to SVM.Keywords: Kernel trick, support vector machine, subsampling, cross-validation. 1. Background and Aim Consider (x 1 , y 1 ),. ,(x N , y N ), the p -variate x and numerical y for regression or binary y (= ±1) forclassiﬁcation. We assume that x 1 ,. ,x N are standardized and that y 1 ,. , y N are centered for numer-ical case. Standard linear model can be stated as y = x T β+ϵ,where ϵ is an error with the mean 0 and a ﬁnite variance. Classic kernel-trick regression and classiﬁ-cation can be stated as follows (Scholkopf and Smola, 1998; Hastie¨ et al. , 2009; Fukumizu, 2010). - Transform x 1 ,. ,x N of p -dim Euclidean space to Φ(x
Validating the Usability Evaluation Model for Hearing Impaired Mobile Application

—Usability is an important element that enables the identification of the efficiency for application or product. However, many applications have been developed for general users’ needs and are unable to provide adequate applications usage for disabled people. This study focuses on the development of usability evaluation model and the validation process on the proposed model through experts. The developed model later evaluated by group of experts through focus group method. Focus group method enables to identify the 13 variables derived to develop the model are appropriately placed and useful in the evaluation process. The results shows that the selected variables are appropriate to identify usability of mobile application for the hearing impairment through three variables tested namely, gain satisfaction with the model, satisfaction with the model presentation, and support for tasks. Conclusively, the developed model can identify usability of mobile applications for hearing impairment and enable in identifying useful criteria to be included during application development process in real life process. As future study, the model can be tested among the hearing impairment people and practitioner to establish the results obtained which contributes to usability practitioners and application developers for the disabled.
Strength development and microstructure properties of slag activated with alkaline earth metal ions: a review study

Abstract This article reviews the microstructure properties and strength development of slag activated with calcium oxide, calcium hydroxide, magnesium oxide, barium hydroxide, carbide slag, and calcined dolomite. X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy, and thermogravimetric/differential thermal analysis were used to evaluate the microstructure characteristics of activated slag. Furthermore, compressive strength test results were studied to evaluate the development of the strength of slag activated with alkaline earth metal ions. The results showed that slag samples activated with carbide slag and barium hydroxide, respectively, produced the lowest and highest compressive strengths. Moreover, among the activators of alkaline earth metal ions studied thus far, barium hydroxide produced the densest microstructure, lowest calcium-to-silicon ratio, and most hydration products. Slag activated with carbide slag produced the lowest calcium–silicate–hydrate (C–S–H) content compared with other activators of alkaline earth metal ions.
Infrared Nonlinear Photomixing Spectroscopy of Graphene Thermal Relaxation

Hot electron effects in graphene are significant because of graphene's small electronic heat capacity and weak electron-phonon coupling, yet the dynamics and cooling mechanisms of hot electrons in graphene are not completely understood. We describe a photocurrent spectroscopy method that uses the mixing of continuous-wave lasers in a graphene photothermal detector to measure the frequency dependence and nonlinearity of hot-electron cooling in graphene as a function of the carrier concentration and temperature. Our measurements reveal that near the charge-neutral-point the electron cooling is well described by disorder-assisted collisions, while at higher carrier concentrations conventional momentum-conserving cooling mechanisms prevail. Furthermore, the method provides a unique frequency-domain measurement of the cooling rate that is not constrained by the width (temporal resolution) and the high intensity of the optical pulse. The photomixing spectroscopy method is well suited to measure the nonlinearity and response time of other photosensitive nanoscale materials and devices.
Content-Based Image Retrieval using Encoder based RGB and Texture Feature Fusion

— Recent development of digital photography and the use of social media using smartphones has boosted the demand for image query by its visual semantics. Content-Based Image Retrieval (CBIR) is a well-identified research area in the domain of image and video data analysis. The major challenges of a CBIR system are (a) to derive the visual semantics of the query image and (b) to find all the similar images from the repository. The objective of this paper is to precisely define the visual semantics using hybrid feature vectors. In this paper, a CBIR system using encoded-based feature fusion is proposed. The CNN encoding features of the RGB channel are fused with the encoded texture features of LBP, CSLBP, and LDP separately. The retrieval performance of the different fused features is tested using three public datasets i.e. Corel-lK, Caltech, and 102flower. The result shows the class properties are better retained using the LDP with RGB encoded features, this helps to enhance the classification and retrieval performance for all three datasets. The average precision of Corel-lK is 94.5% and it is 89.7% for Caltech, and 88.7% for the 102flower. The average f1-score is 89.5% for Caltech, and 88.5% for the 102flower. The improvement in the f1-score value implies the proposed fused feature is more stable to deal the class imbalance problem.
Identification of Potential miRNA-mRNA Regulatory Network Associated with Regulating Immunity and Metabolism in Pigs Induced by ASFV Infection

Simple Summary In order to understand the complex interactions between ASFV and the host cell, the expression differences and functional analysis of microRNA (miRNA) in porcine peripheral blood lymphocytes of ASFV infected pigs and healthy pigs were compared, and the regulatory network of miRNA-mRNA was drawn. miRNAs in pathways related to disease, inflammation, and lipid metabolism were differentially expressed. ASFV could regulate immunity and metabolism-related pathways in infected pigs by inducing differential expression of miRNAs. This study elucidated the immunity regulation mechanisms of ASFV, which will provide a theoretical basis for the development of good prevention and control strategies. Abstract African swine fever (ASF) is a devastating infectious disease in domestic pigs caused by African swine fever virus (ASFV) with a mortality rate of about 100%. However, the understanding of the interaction between ASFV and host is still not clear. In this study, the expression differences and functional analysis of microRNA (miRNA) in porcine peripheral blood lymphocytes of ASFV infected pigs and healthy pigs were compared based on Illumina high-throughput sequencing, then the GO and KEGG signal pathways were analyzed. The miRNA related to immunity and inflammation were screened, and the regulatory network of miRNA-mRNA was drawn. A total of 70 differentially expressed miRNAs were found (p ≤ 0.05). Of these, 45 were upregulated and 25 were downregulated in ASFV-infected pigs vs. healthy pigs. A total of 8179 mRNA genes targeted by these 70 differentially expressed miRNA were predicted, of which 1447 mRNA genes were targeted by ssc-miR-2320-5p. Five differentially expressed miRNA were validated by RT-qPCR, which were consistent with the RNA-Seq results. The GO analysis revealed that a total of 30 gene functions were significantly enriched, including 7 molecular functions (MF), 13 cellular components (CC), and 10 biological processes (BP). The KEGG enrichment analysis revealed that the differentially expressed genes were significantly enriched in pathways related to immunity, inflammation, and various metabolic processes, in which a total of two downregulated miRNAs after infection and eight upregulated miRNAs related to immunity and inflammation were screened in ASFV-infected pigs vs. healthy pigs. The network of miRNA-mRNA showed that the mRNA target genes were strongly regulated by ssc-miR-214, ssc-miR-199b-3p, and ssc-miR-199a-3p. The mRNA target genes were enriched into the MAPK signaling pathway, Toll-like receptor signaling pathway, TNF signaling pathway, and IL-17 signaling pathway by using a KEGG enrichment analysis. Therefore, ASFV could regulate immunity and metabolism-related pathways in infected pigs by inducing differential expression of miRNAs. These results provided a new basis for further elucidating the interactions between ASFV and the host as well as the immunity regulation mechanisms of ASFV, which will be conducive to better controlling ASF.
NAA10 Hypomethylation is associated with particulate matter exposure and worse prognosis for patients with non-small cell lung cancer

ABSTRACT Airborne particulate matter (PM) is a major health hazard worldwide and is a key factor in lung cancer, which remains the most common type of malignancy and the leading cause of cancer-related deaths. DNA methylation is a critical mechanism underlying the detrimental effects of PM, however, the molecular link between PM exposure and lung cancer remains to be elucidated. N-α-acetyltransferase 10 (NAA10) is involved in the cell cycle, migration, apoptosis, differentiation, and proliferation. In order to investigate the role of NAA10 in PM-induced pathogenesis processes leading to lung cancer, we determined the expression and methylation of NAA10 in normal human bronchial epithelial (NHBE) cells treated with PM10, PM10-polycyclic aromatic hydrocarbons (PAH), and PM2.5 and evaluated the prognostic value of the NAA10 methylation status in lung cancer patients. Exposure to all PM types significantly increased the expression of NAA10 mRNA and decreased the methylation of the NAA10 promoter in NHBE cells compared with the mock-treated control. NAA10 hypomethylation was observed in 9.3% (13/140) of lung cancer tissue samples and correlated with NAA10 transcriptional upregulation. Univariate and multivariate analyses revealed that NAA10 hypomethylation was associated with decreased survival of patients with lung cancer. Therefore, these results suggest that PM-induced hypomethylation of the NAA10 may play an important role in the pathogenesis of lung cancer and may be used as a potential prognostic biomarker for lung cancer progression. Further studies with large numbers of patients are warranted to confirm our findings.