Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrochemical-Based Sensing Platforms for Detection of Glucose and H2O2 by Porous Metal–Organic Frameworks: A Review of Status and Prospects

Establishing enzyme-free sensing assays with great selectivity and sensitivity for glucose and H2O2 detection has been highly required in biological science. In particular, the exploitation of nanomaterials by using noble metals of high conductivity and surface area has been widely investigated to act as selective catalytic agents for molecular recognition in sensing platforms. Several approaches for a straightforward, speedy, selective, and sensitive recognition of glucose and H2O2 were requested. This paper reviews the current progress in electrochemical detection using metal–organic frameworks (MOFs) for H2O2 and glucose recognition. We have reviewed the latest electrochemical sensing assays for in-place detection with priorities including straightforward procedure and manipulation, high sensitivity, varied linear range, and economic prospects. The mentioned sensing assays apply electrochemical systems through a rapid detection time that enables real-time recognition. In profitable fields, the obstacles that have been associated with sample preparation and tool expense can be solved by applying these sensing means. Some parameters, including the impedance, intensity, and potential difference measurement methods have permitted low limit of detections (LODs) and noticeable durations in agricultural, water, and foodstuff samples with high levels of glucose and H2O2.
Surgical Management of Chronic Pancreatitis: A Systemic Review

Chronic pancreatitis is a debilitating disease. It is caused by the progressive destruction of normal pancreatic parenchyma, which is replaced by fibrous tissue causing pain in addition to pancreatic insufficiency. There is no single mechanism of pain in chronic pancreatitis. Several medical, endoscopic, and surgical treatment strategies are available to control this disease. Surgical techniques are divided into resection, drainage, and hybrid procedures. The review aimed to compare various surgical procedures used in the management of chronic pancreatitis. The ideal operation is the one that effectively and persistently relieves the pain and has the least morbidity with favorable pancreatic reserve. All the randomized control trials from inception to January 2023, which fulfilled the inclusion criteria, were extensively searched on PubMed and a systemic review was conducted comparing the surgical outcomes of the variety of operations used in chronic pancreatitis. Duodenum-preserving pancreatic head resection is the common procedure done with favorable outcomes.
Implementation of single-photon creation and annihilation operators: experimental issues in their application to thermal states of light

We have recently realized experimental schemes to implement the action of single-photon creation and annihilation operators onto completely classical and fully incoherent thermal light states (Parigi et al 2007 Science 317 1890). By applying alternated sequences of the creation and annihilation operators we observed that the resulting states depend on the order in which the two quantum operators are applied, thus obtaining the most direct experimental test of non-commutativity. Here we provide an extensive and detailed discussion of the main experimental issues related to the realization of these schemes.
Collaborative Hyperspectral Image Processing Using Satellite Edge Computing

The advancement of nanosatellite techniques has boosted the growth of satellite-originated data and applications. Satellite edge computing (SEC) is envisioned to provide in-orbit processing of the sensed data to save the scarce terrestrial-satellite communication resources and support mission-critical services. While most of the existing SEC studies mainly focus on general computing tasks, we present a two-tier collaborative processing framework for the important and unique hyperspectral image (HSI) processing task. Our framework carefully selects bands out of the collected HSIs and sends them back for further analysis. We first conduct a comprehensive data analysis to reveal the non-trivial relationship between the band selection and the eventual analytic performance. We then formulate the band selection problem in this collaborative setting as a utility maximization problem that jointly considers the analytic, energy, and communication factors. A novel multi-agent reinforcement learning approach, named MaHSI, is proposed to solve it in the dynamic SEC environment. Our multi-agent design judiciously embeds the complex correlations among bands as collaborations among agents and significantly reduces the exploration space. Extensive experiments on real-world HSI datasets prove that our approach not only outperforms the existing classical band selection algorithms in accuracy and inference speed but also brings the highest utility to the satellites.
Does growth in the outdoors stay in the outdoors? The impact of an extended residential and outdoor learning experience on student motivation, engagement and 21st century capabilities

Introduction Student motivation and engagement underpin educational success, and recent research has found they are lowest in middle high school, especially for boys. At the same time, education systems are recognizing that academic performance is necessary but not sufficient to prepare young people for the adult world, and so-called “21st Century skills” (communication, collaboration, critical thinking, and creativity) have been suggested as critical capabilities across all employment sectors in the future. The Glengarry program is a 6-month residential and outdoor learning experience for Year 9 (14–15 years old) boys at an Australian independent school, The Scots College (TSC) Glengarry. Intentionally located during the lowest point of engagement in their adolescent student journey, the Residential and Outdoor Education experience was hypothesized to boost their motivation and engagement and develop 21st Century skills. Methods The Glengarry program involves students living in a boarding-style community for 20 weeks away from their families, participating in classes across all regular school subjects at a bush campus, and undertaking increasingly challenging outdoor education trips each week. The study aimed to measure how these factors transferred into students’ traditional school environment after their Glengarry experience. Year 9 was split into two cohorts who both participated in the study: one of which completed the Glengarry program in the first half of 2019, and the other during the second half of the year. Results Self-reported quantitative and qualitative data supported the hypothesis that the Glengarry program did indeed, boost student motivation and 21st Century skills. While gains in 21st Century skills endured over the next 8–10 months, motivation and some engagement factors decreased upon return to the traditional school environment. Students described key factors in the Glengarry program which facilitated their development, including: an intense residential environment necessitating social growth, a closer connection with teachers in both school and community life, and an appreciation of learning in the natural environment. Recommendations are made for future research to strengthen these findings, and for how these mediating factors could be incorporated into the regular school environment.
In Situ Degradation Kinetics of 25 Feedstuffs and the Selection of Time Points in Mathematical Statistics

Simple Summary In order to further standardize and simplify the operation of the nylon bag method, rumen degradation kinetics of 25 feedstuffs were first determined using in situ nylon bag technique and then the differences of degradation parameters fitted with five or seven time points measuring data were evaluated. Additionally, the goodness of fit (R2) of degradation curves obtained at different time points was compared. In protein feeds, energy feeds and roughages, there were no significant differences in rumen degradation parameters except for several feedstuffs. By comparing the R2, it was found that the R2 of degradation curves which obtained five time points was better than that which obtained seven time points. These results indicate that it is feasible to determine the rumen degradation characteristics of feedstuffs by only setting five measuring time points, and based on the reasonable criteria, where the optimal selection of incubation time points for protein feeds and energy feeds was the set of ② 2, 16, 24, 36, 48 h, and that for roughages was ① 4, 8, 16, 48, 72 h. Abstract Rumen degradation kinetics of 25 feedstuffs (six protein feeds, nine energy feeds and ten roughages) were first determined using the nylon bag technique in situ and the differences of degradation characteristics fitted with five or seven time points measuring data were evaluated with the goodness of fit (R2) of degradation curves. Protein and energy feeds were incubated for 2, 4, 8, 16, 24, 36, 48 h, roughages were incubated for 4, 8, 16, 24, 36, 48, 72 h, where three and six data sets of five time points were screened out, respectively. Only the degradation parameters a (rapidly degraded proportion), b (slowly degraded proportion) and c (degradation rate of slowly degraded proportion) of several feeds at five time points were significantly different from those at seven time points (p < 0.05), and the others were not significant (p > 0.05). The R2 of the degradation curves obtained at five time points was closer to 1, indicating that the fitting obtained at five time points was more accurate in predicting the real-time rumen degradation rate of feed. These results indicate that it is feasible to determine the rumen degradation characteristics of feedstuffs by only setting five measuring time points.
Immune Checkpoint Inhibitors-Associated Thrombosis: Incidence, Risk Factors and Management

Immune checkpoint inhibitors (ICIs) target programmed cell death (PD) 1 receptor and its ligand PD-L1, and have become an integral part of treatment regimens in many cancers including lung cancer, renal cell carcinoma, melanoma, and more. Cancer is associated with a significantly increased risk of venous thromboembolism compared to non-cancer patients, and the risks increase further with anticancer therapies including ICIs. Cancer-associated thrombosis can lead to hospitalizations, delayed cancer treatment, and mortality. While thrombosis was not reported as a major complication in initial clinical trials leading to the approval of ICIs, emerging evidence from post-marketing studies revealed concerning risks of thrombosis in patients receiving ICIs. However, results remained heterogenous given differences in study designs and populations. Recent studies also showed that C-reactive protein dynamics might be an easily accessible biomarker for thrombosis and disease response in this population. In addition, early findings indicated that a commonly used anticoagulant for cancer-associated thrombosis, factor Xa inhibitors, might have potential synergistic antitumor effects when combined with ICIs. Herein we will review the current literature on the incidence, risk factors, and management of thrombosis in patients with cancer receiving ICIs. We aim to provide valuable information for clinicians in managing these patients.
Non-invasive monitoring of microbial triterpenoid production using nonlinear microscopy techniques

Introduction: Bioproduction of plant-derived triterpenoids in recombinant microbes is receiving great attention to make these biologically active compounds industrially accessible as nutraceuticals, pharmaceutics, and cosmetic ingredients. So far, there is no direct method for detecting triterpenoids under physiological conditions on a cellular level, information yet highly relevant to rationalizing microbial engineering. Methods: Here, we show in a proof-of-concept study, that triterpenoids can be detected and monitored in living yeast cells by combining coherent anti-Stokes Raman scattering (CARS) and second-harmonic-generation (SHG) microscopy techniques. We applied CARS and SHG microscopy measurements, and for comparison classical Nile Red staining, on immobilized and growing triterpenoid-producing, and non-producing reference Saccharomyces cerevisiae strains. Results and Discussion: We found that the SHG signal in triterpenoid-producing strains is significantly higher than in a non-producing reference strain, correlating with lipophile content as determined by Nile red staining. In growing cultures, both CARS and SHG signals showed changes over time, enabling new insights into the dynamics of triterpenoid production and storage inside cells.
Molecular Signatures in Ductal Carcinoma In Situ (DCIS): A Systematic Review and Meta-Analysis

Context: Adjuvant radiotherapy (RT) after breast-conserving surgery (BCS) for ductal carcinoma in situ (DCIS) is debated as benefits are inconstant. Molecular signatures for DCIS have been developed to stratify the risk of local recurrence (LR) and therefore guide the decision of RT. Objective: To evaluate, in women with DCIS treated by BCS, the impact of adjuvant RT on LR according to the molecular signature risk stratification. Methodology: We conducted a systematic review and meta-analysis of five articles including women with DCIS treated by BCS and with a molecular assay performed to stratify the risk, comparing the effect of BCS and RT versus BCS alone on LR including ipsilateral invasive (InvBE) and total breast events (TotBE). Results: The meta-analysis included 3478 women and evaluated two molecular signatures: Oncotype Dx DCIS (prognostic of LR), and DCISionRT (prognostic of LR and predictive of RT benefit). For DCISionRT, in the high-risk group, the pooled hazard ratio of BCS + RT versus BCS was 0.39 (95%CI 0.20–0.77) for InvBE and 0.34 (95%CI 0.22–0.52) for TotBE. In the low-risk group, the pooled hazard ratio of BCS + RT versus BCS was significant for TotBE at 0.62 (95%CI 0.39–0.99); however, it was not significant for InvBE (HR = 0.58 (95%CI 0.25–1.32)), Discussion: Molecular signatures are able to discriminate high- and low-risk women, high-risk ones having a significant benefit of RT in the reduction of invasive and in situ local recurrences, while in low-risk ones RT did not have a benefit for preventing invasive breast recurrence. The risk prediction of molecular signatures is independent of other risk stratification tools developed in DCIS, and have a tendency toward RT de-escalation. Further studies are needed to assess the impact on mortality.
A Precautionary Tale: Individual Decision Making in the Time of COVID-19

Precaution taking is an important part of managing COVID-19 and has been since the start of the pandemic. Guided by the Health Belief Model, two studies conducted during the beginning of the COVID-19 pandemic aimed to identify possible individual difference predictors of precautionary actions. Study 1 was an online, cross-sectional study using 763 adults aged 20–79 years old. Study 2, a 30-day daily diary study, examined daily precautions in 261 persons over the age of 55 years old. Study 1 and Study 2 indicated that COVID-19 knowledge predicted precautionary behaviors. Multilevel models from Study 2 indicated that daily increases in in-person interactions and leaving home were associated with decreases in precautions, but increases in disruption to routine were associated with increases in precautions. In both studies, including concurrent and lagged models in Study 2, significant interactions between information seeking and perceived risk suggested higher information seeking was related to higher precautions for those who consider themselves low risk. Findings highlight the burden of daily precautions and potentially modifiable factors of engagement in precautions.
Challenges in quantifying changes in the global water cycle

AbstractUnderstanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time series over land, but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellit.
Instability of a free-shear layer in the vicinity of a viscosity-stratified layer

Abstract The stability of a mixing layer made up of two miscible fluids, with a viscosity-stratified layer between them, is studied. The two fluids are of the same density. It is shown that unlike other viscosity-stratified shear flows, where species diffusivity is a dominant factor determining stability, species diffusivity variations over orders of magnitude do not change the answer to any noticeable degree in this case. Viscosity stratification, however, does matter, and can stabilize or destabilize the flow, depending on whether the layer of varying velocity is located within the less or more viscous fluid. By making an inviscid model flow with a slope change across the ‘viscosity’ interface, we show that viscous and inviscid results are in qualitative agreement. The absolute instability of the flow can also be significantly altered by viscosity stratification.
Quantitative Analysis of Ras Oncogene Isoforms Using Decision Tree and Support Vector Machine

—Ras isoform plays a significant functional role in cell growth, cell cycle progression, cytoskeletal changes, apoptosis, and senescence. Mutated Ras gene causes cell proliferation. These genes are found in various kinds of cancer, thus it has been considered that mutated Ras is oncogenic. Ras oncogenes have three isoforms, which are K-Ras, N-Ras and H-Ras. For three decades, there has been active research on Ras gene, but quantitative analysis on each isoform is unknown. For the research, our goal is to compare and contrast each Ras isoform for deeper understanding. We seek for any possibilities of relations between the results and functional role of each isoform by using two types of data-mining technologies; Decision tree and Support Vector Machine. The results show that all three Ras isoforms are fairly alike, especially in the case of K-Ras and N-Ras. Decision tree shows that position 2, 3, 9, 10 act as significant parts in each Ras Isoform. We want to point out that this is the first time to conduct quantitative classification of Ras Isoforms. 
Fault Diagnosis of Laminar Cooling Roller Motor Based on Morphological Recognition and Combination Patterns Mining of Multicurrent Signatures

Laminar cooling roller motor (LCRM) is the main driving equipment of laminar cooling Section (LCS) in a steelmaking plant. To promote an intelligent upgrade of the safe management and operation of LCRMs, a novel fault diagnosis method based on the morphological recognition and combination pattern mining of LCRM’s multicurrent signatures is proposed. Six key current signatures closely related to the faults are screened by the correlation analysis empirically in advance. A Bayesian limited-memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) algorithm is proposed to obtain the smooth boundary morphology by the curve fitting of the boundary sequences of the upper and lower quantiles of every windowed current signature. Then, a triplet-CNN-fused k-nearest neighbor (KNN) with gated recurrent unit (GRU) and transformer, termed T-CKGT is proposed, to identify the fault-related abnormal current signature morphology under a constraint of limited samples. Specifically, the CNN and GRU are, respectively, used to mine the spatial and temporal features of the boundary morphology, which are fused to feed into a transformer to learn recognizable features, and then a KNN classifier is employed to identify the abnormal morphological type of each current signature based on the recognizable features. To mine the abnormal morphological combination patterns (AMCPs) of different faults, the AMCPs of six key current signatures are taken as gene fragments of genetic algorithm (GA) to achieve the AMCP library for each fault type, so as to realize the online fault diagnosis efficiently by pattern matching. Extensive confirmatory and comparative experiments were performed for the online fault identification of 39 LCRMs in a real steelmaking plant. Experimental results indicate that the proposed method can achieve a high fault recognition accuracy, generally higher than 96%, which outperforms the state-of-the-art methods apparently. In addition, during the actual application, no critical false negatives and false positives were observed.
Computational Studies of Two-Dimensional Rayleigh-Taylor Driven Mixing for a Tilted-Rig

A time-dependent, incompressible, turbulent mixing problem, referred here to as the “tilted-rig,” is defined, based results from an experiment that involved the introduction of a large-scale overturning motion, with a superposed localized Rayleigh-Taylor (RT) driven mixing. The problem serves to examine the development of RT turbulent mixing while being strained by a large-scale two-dimensional confined motion. Care is taken to define the problem in detail so others might use the definition, and the results, to help develop advanced models of buoyancy driven mixing in complex flows. Aside from a careful definition, the problem has been solved using two different implicit-large-Eddy-simulations (ILES) based codes, and with a direct numerical simulations (DNS) code. Two-dimensional and one-dimensional mix metrics are defined, and then used to examine the development of the mixing region, and the overall evolution of the flow. Comparison of simulations with experiment reveals that large-scale overturning can be well captured in all the simulations, similarly central mix widths, and spike/bubble sidewall penetrations are also in good agreement. A comparison between the different simulation methodologies, ILES and DNS, reveals an overall good agreement between mix metrics such as the amount of molecular mixing. The DNS simulations reveal a dependency on Reynolds number that merits further experimental work.