Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of substrate type and thickness influence on wettability of Nb2O5 thin films

For the purpose of this paper Nb2O5 thin films were manufactured by microwave-assisted reactive magnetron sputtering. Nb2O5 thin films with different thickness were deposited on standard microscope slides, SiO2 and silicon substrates. Wettability and optical properties of manufactured coatings were investigated. Knowledge of the macroscopic contact angle for materials allows to predict whether a liquid droplet will bead up on or spread out over a solid surface. In this paper contact angle, critical surface tension and surface free energy of Nb2O5 thin films with thickness of 565, 300, 200, 100 and 50 nm were investigated. Measurements of surface free energy and contact angle was carried out with a computer controlled goniometer system with water, ethylene glycol and diiodomethane. Contact angle measurements were performed according to the sessile drop method. The results have shown that all manufactured Nb2O5 thin films had the water contact angle of about 90 degrees. There was no difference in wettability for thin films with different thickness and deposited on different substrates. Also optical properties of deposited thin films were compared. Transmittance spectra of Nb2O5 thin films were measured using Hitachi U-3501 spectrophotometer. Based on transmittance and reflectance spectra, measured with the aid of Aquila nkd-8000 instrumentation, thickness, refractive index and extinction coefficient of Nb2O5 thin films were calculated using Drude - Lorentz model. Transparency in visible light range of deposited thin films varied from about 70 % up to 80 %. Refractive index and extinction coefficient were 2.32 and 4.55×10-5, respectively.
Fusobacterium nucleatum induces chemoresistance in colorectal cancer by inhibiting pyroptosis via the Hippo pathway

ABSTRACT Chemotherapy resistance is one of the main reasons for the poor prognosis of colorectal cancer (CRC). Moreover, dysbiosis of gut bacteria was found to be a specific environmental risk factor. In this study, enrichment of F. nucleatum was elucidated to be significantly associated with CRC recurrence after chemotherapy. Functional experiments showed that F. nucleatum could inhibit pyroptosis induced by chemotherapy drugs, thereby inducing chemoresistance. Furthermore, mechanistic investigation demonstrated that F. nucleatum could regulate the Hippo pathway and promote the expression of BCL2, thereby inhibiting the Caspase-3/GSDME pyroptosis-related pathway induced by chemotherapy drugs and mediating CRC cell chemoresistance. Taken together, these results validated the significant roles of F. nucleatum in CRC chemoresistance, which provided an innovative theoretical basis for the clinical diagnosis and therapy of CRC.
Deep Learning-Based Prediction Model for Gait Recovery after a Spinal Cord Injury

Predicting gait recovery after a spinal cord injury (SCI) during an acute rehabilitation phase is important for planning rehabilitation strategies. However, few studies have been conducted on this topic to date. In this study, we developed a deep learning-based prediction model for gait recovery after SCI upon discharge from an acute rehabilitation facility. Data were collected from 405 patients with acute SCI admitted to the acute rehabilitation facility of Korea University Anam Hospital between June 2008 and December 2022. The dependent variable was Functional Ambulation Category at the time of discharge (FAC-DC). Seventy-one independent variables were selected from the existing literature: basic information, International Standards for Neurological Classification of SCI scores, neurogenic bladders, initial FAC, and somatosensory-evoked potentials of the lower extremity. Recurrent neural network (RNN), linear regression (LR), Ridge, and Lasso methods were compared for FAC-DC prediction in terms of the root-mean-squared error (RMSE). RNN variable importance, which is the RMSE gap between a complete RNN model and an RNN model excluding a certain variable, was used to evaluate the contribution of this variable. Based on the results of this study, the performance of the RNN was far better than that of LR, Ridge, and Lasso. The respective RMSEs were 0.3738, 2.2831, 1.3161, and 1.0246 for all the participants; 0.3727, 1.7176, 1.3914, and 1.3524 for those with trauma; and 0.3728, 1.7516, 1.1012, and 0.8889 for those without trauma. In terms of RNN variable importance, lower-extremity motor strength (right and left ankle dorsiflexors, right knee extensors, and left long toe extensors) and the neurological level of injury were ranked among the top five across the boards. Therefore, initial FAC was the seventh, third, and ninth most important predictor for all participants, those with trauma, and those without trauma, respectively. In conclusion, this study developed a deep learning-based prediction model with excellent performance for gait recovery after SCI at the time of discharge from an acute rehabilitation facility. This study also demonstrated the strength of deep learning as an explainable artificial intelligence method for identifying the most important predictors.
Differential expression of serum TM, PAF, and CD62P in patients with autologous arteriovenous fistula and the correlation with vascular access function

Abstract Background End‐stage renal disease (ESRD) is the final stage of chronic kidney disease (CKD). Aims We aimed to analyze the expression differences of serum thrombomodulin (TM), platelet‐activating factor (PAF), and P‐selectin (CD62P) in patients with autologous arteriovenous fistula (AVF) and the correlation with vascular access function. Methods The case data were retrospectively analyzed. Moreover, 160 patients with AVF maintenance hemodialysis were selected as the AVF group, and 150 healthy participants were selected as the healthy control group. According to the function of vascular access, patients in the AVF group were divided into Group A (n = 50, after the first establishment of AVF), Group B (n = 64, normal vascular access function after hemodialysis treatment), and Group C (n = 46, vascular access failure). Pearson analysis was conducted to explore the correlation between serum TM, PAF, CD62P content, and vascular pathological examination indicators, to evaluate the value of TM, PAF, and CD62P levels in predicting vascular access failure in patients with AVF. Results and Discussion The serum levels of TM, PAF, and CD62P were positively correlated with the expressions of CD68 and MCP‐1, respectively (p < .001). Serum TM was positively correlated with the levels of PAF and CD62P (p < .001), and PAF was positively correlated with the levels of CD62P (p < .001), respectively. Serum levels of TM, PAF and CD62P were risk factors for vascular access failure in AVF patients (p < .05). The area under the curve of serum TM, PAF and CD62P levels in predicting vascular access failure in AVF patients was 0.879. Conclusion The serum levels of TM, PAF, and CD62P in AVF patients were correlated with the vascular access function of AVF patients, which was very important for maintaining the stability of vascular access function, and had certain value in predicting vascular access failure/disorder in AVF patients, and could be popularized and applied.
1064 nm-Nd:YAG lasers with different output modes enhancing transdermal delivery: physical and physiological mechanisms

Abstract. Lasers have shown great advantages in enhancing transdermal drug delivery. However, the physical or physiological mechanisms are not clear, which limits the application in clinical medicine. Here, 1064 nm-Nd:YAG lasers with long-pulsed (LP, 15 J/cm2) and Q-switched (QS, 0.5 J/cm2) output modes inducing short- and long-term effects on the stratum corneum (SC) of skin are investigated. Infrared thermography is applied to monitor the dynamical temperature distribution of the skin surface, while histopathological analysis and two-photon fluorescence microscopy are employed to examine changes in the microstructure of skin and molecular constitution of SC, respectively. Results have shown that the LP laser irradiation increases skin temperature evidently and loosens keratin, making corneocytes fragile or exfoliative, whereas the QS laser irradiation disrupts the keratin or corneocytes completely, perforating some micropores on the SC. It can be concluded that the mechanisms of enhancing transdermal delivery caused by lasers depends on the output modes. The LP laser irradiation produces thermal effects on skin, which loosens the SC, while the QS laser induces mechanical effects on skin, which punches micropores on the SC. Moreover, the laser-induced enhancing effects on transdermal glycerol delivery can last for one week to wait for the recovery of SC.
Change detection in urban areas from remote sensing data: a multidimensional classification scheme

ABSTRACT Change detection (CD) from remote sensing data is a very challenging research problem, especially when we analyse an urban scene. Urban scenes are composed of many different types of objects, both natural and man-made. The building class is one of the important and most complex classes to analyse, important because it is useful for so many applications and complex because it exhibits many changes due to human activity and natural catastrophes. For these reasons, we focus our study on building change detection (BCD). In this paper we propose a classification scheme for BCD research according to several important dimensions including objective, input data, temporal resolution, analysis unit, target output unit, building features, processing technique, change categories, and assessment of results. This classification scheme can guide practitioners in choosing appropriate change detection methods to achieve their goals as well as informing new research efforts. Based on this multidimensional characterisation of BCD, we offer a number of suggestions for further work to be done in this field.
Intestinal microbiota modulates neuroinflammatory response and brain injury after neonatal hypoxia-ischemia

ABSTRACT Premature infants lack a normal intestinal microbial community and also at risk of perinatal hypoxic-ischemic (HI) brain injury, which is considered to be one of the major factors for motor, sensory, and cognitive deficits. We hypothesized that neonatal gut microbiota composition modulated the immune reaction and severity of neonatal H-I brain injury. Neonatal C57BL/6J mouse pups were exposed to H-I protocol consisting of permanent left carotid artery ligation, followed by 8% hypoxia for 60 min. Microbial manipulation groups included 1) antibiotic treatment, E18 (maternal) to P5; 2) antibiotic treatment E18 to P5 + E. coli gavage; 3) antibiotic treatment E18 to P5 + B. infantis gavage; and 4) saline to pups with dams getting fresh water. The extent of brain injury and recovery was measured on MRI. Edematous injury volume was significantly higher in E. coli group than that in B. infantis group and in fresh water group. Gene expression in brains of pro-inflammatory cytokines (IL1β, IL6, IL2, TNF-α and toll-like receptors 2–6) were elevated to a greater extent in the E. coli group at P10, no injury, and at P13, 72 hours after H-I relative to sham control and B. infantis groups. Significant effects of microbiome and brain injury and interaction of these factors were found in abundance of major phyla. The neuroinflammatory response and brain injury after neonatal hypoxia-ischemia are affected by intestinal microbiota, providing opportunities for therapeutic intervention through targeting the early colonization and development of the gut microbiota.
Three-Dimensional Printing of Hydrogels for Flexible Sensors: A Review

The remarkable flexibility and heightened sensitivity of flexible sensors have drawn significant attention, setting them apart from traditional sensor technology. Within this domain, hydrogels—3D crosslinked networks of hydrophilic polymers—emerge as a leading material for the new generation of flexible sensors, thanks to their unique material properties. These include structural versatility, which imparts traits like adhesiveness and self-healing capabilities. Traditional templating-based methods fall short of tailor-made applications in crafting flexible sensors. In contrast, 3D printing technology stands out with its superior fabrication precision, cost-effectiveness, and satisfactory production efficiency, making it a more suitable approach than templating-based strategies. This review spotlights the latest hydrogel-based flexible sensors developed through 3D printing. It begins by categorizing hydrogels and outlining various 3D-printing techniques. It then focuses on a range of flexible sensors—including those for strain, pressure, pH, temperature, and biosensors—detailing their fabrication methods and applications. Furthermore, it explores the sensing mechanisms and concludes with an analysis of existing challenges and prospects for future research breakthroughs in this field.
The Self-formation of Collaborative Groups in a Problem Based Learning Environment

The aim of this paper is to present the three steps method of the self-formation of collaborative groups in a problem-based learning environment. The self-formation of collaborative groups is based on sharing of accountability among students for solving instructional problems. The steps of the method are planning collaborative problem solving, self-evaluation of students, and building collaborative groups. The planning comprises determination of the nomenclature of higher order thinking (HOT) skills, defining the instructional problems and their complexity levels, creating problem groups according to the complexity levels, setting the problem-relevant HOT skills, determining the accountability measure and the assessments of accountability for solving the problems. The self-evaluation includes self-detection of personal HOT skills, measurement of the diversity between the personal HOT skills and the problem-relevant skills based on the proposed diversity measure, and self-evaluation of willingness and desire of a student to take accountability for solving the instructional problems. The personal willingness is evaluated by the diversity measure. The desire is guided by the accountability assessments for problem solving. Coordination of the self-evaluation outcomes allows building collaborative groups. A group’s composition is adjusted by the specific requirements of an instructor. Keywords : problem based learning, self-forming collaborative groups
ON REGIONAL ECONOMIC INTEGRATION NO . 11 Inequality and Growth Revisited

This paper updates and extends the work of Barro (2000). International data confirm the presence of the Kuznets curve—an inverse-U shape relationship between income inequality and per capita GDP—that is relatively stable from the 1960s into the 2000s. The direct effect of international openness on income inequality is also found to be positive. On the other hand, a cross-country-growth equation shows a negative effect of income inequality on economic growth, holding fixed a familiar set of other explanatory variables. This effect diminishes as per capita GDP rises and may be positive for the richest countries.
Secure Data and Service Access Model for Peer-to-Peer Systems using Trust Relations

Peer-to-Peer systems are based on collaboration of peers to accomplish tasks. Trust relationship among peers can help to reduce attacks of peers with malicious intent. In this paper we presents algorithms which helps a peer to reason about trustworthiness of other peers based on interactions in the past and recommendations. Peers create trust network using local information and does not need to deal with global information. Service and recommendation metrics describes the trustworthiness of peers in providing services. Recentness, importance and peer satisfaction parameters are considered for evaluating interactions and recommendations. A good peer can isolate malicious peers with the help of trust relationships.
Plasma vitamin A assay by fluorometry and use of a silicic acid column technique.

We investigated a new procedure in which silicic acid column chromatography and fluorometry are used to assay plasma vitamin A. Using tritium-labeled vitamin A acetate and vitamin A alcohol as radioactive standards, we identified two fluorescent components in plasma extracts chromatographed on silicic acid columns. One unidentified fluorescent component was eluted first with hexane or petroleum ether. Vitamin A, the second fluorescent peak, was quantitatively eluted with isopropanol. The isopropanol eluates could be immediately assayed fluorometrically without further treatment. The unidentified compound was sensitive to ultraviolet irradiation, which destroyed it slower than vitamin A is destroyed. Values correlated well for plasma vitamin A concentrations, determined by this procedure and by the Neeld and Pearson modification of the Carr-Price colorimetric method (r = 0.871). By our technique, we found 34 µg of vitamin A per 100 ml of plasma in 778 preschool children.
And Elementary End Extensions of V Κ

In this paper we prove that if κ is a cardinal in L[0]], then there is an inner model M such that M |= (Vκ,∈) has no elementary end extension. In particular if 0] exists, then weak compactness is never downwards absolute. We complement the result with a lemma stating that any cardinal greater than א1 of uncountable cofinality in L[0]] is Mahlo in every strict inner model of L[0]].
Episomal Vectors for Stable Production of Recombinant Proteins and Engineered Antibodies

There is tremendous interest in the production of recombinant proteins, particularly bispecific antibodies and antibody–drug conjugates for research and therapeutic use. Here, we demonstrate a highly versatile plasmid system that allows the rapid generation of stable Expi293 cell pools by episomal retention of transfected DNA. By linking protein expression to puromycin resistance through an attenuated internal ribosome entry site, we achieve stable cell pools producing proteins of interest. In addition, split intein–split puromycin-mediated selection of two separate protein expression cassettes allows the stable production of bispecific antibody-like molecules or antibodies with distinct C-terminal heavy chain modifications, such as an antigen on one chain and a sortase tag on the other chain. We also use this novel expression system to generate stable Expi293 cell pools that secrete sortase A Δ59 variant Srt4M. Using these reagents, we prepared a site-specific drug-to-antibody ratio of 1 antibody–siRNA conjugate. We anticipate the simple, robust, and rapid stable protein expression systems described here being useful for a wide variety of applications.
Land surface temperature downscaling using random forest regression: primary result and sensitivity analysis

The land surface temperature (LST) derived from thermal infrared satellite images is a meaningful variable in many remote sensing applications. However, at present, the spatial resolution of the satellite thermal infrared remote sensing sensor is coarser, which cannot meet the needs. In this study, LST image was downscaled by a random forest model between LST and multiple predictors in an arid region with an oasis-desert ecotone. The proposed downscaling approach was evaluated using LST derived from the MODIS LST product of Zhangye City in Heihe Basin. The primary result of LST downscaling has been shown that the distribution of downscaled LST matched with that of the ecosystem of oasis and desert. By the way of sensitivity analysis, the most sensitive factors to LST downscaling were modified normalized difference water index (MNDWI)/normalized multi-band drought index (NMDI), soil adjusted vegetation index (SAVI)/ shortwave infrared reflectance (SWIR)/normalized difference vegetation index (NDVI), normalized difference building index (NDBI)/SAVI and SWIR/NDBI/MNDWI/NDWI for the region of water, vegetation, building and desert, with LST variation (at most) of 0.20/-0.22 K, 0.92/0.62/0.46 K, 0.28/-0.29 K and 3.87/-1.53/-0.64/-0.25 K in the situation of ±0.02 predictor perturbances, respectively.
Network coding designs suited for the real world: What works, what doesn't, what's promising

Network coding (NC) has attracted tremendous attention from the research community due to its potential to significantly improve networks' throughput, delay, and energy performance as well as a means to simplify protocol design and naturally providing security support. The possibilities in code design have produced a large influx of new ideas and approaches to harness the power of NC. But, which of these designs are truly successful in practice? and which designs will not live up to their promised theoretical gains due to real-world constraints? Without attempting a comprehensive view of all practical pitfalls, this paper seeks to identify key ingredients to a successful design, critical and common limitations to most intra-session NC systems as well as promising techniques and ideas to guide future models and research problems grounded on practical concerns.
A draft fur seal genome provides insights into factors affecting SNP validation and how to mitigate them

Custom genotyping arrays provide a flexible and accurate means of genotyping single nucleotide polymorphisms (SNPs) in a large number of individuals of essentially any organism. However, validation rates, defined as the proportion of putative SNPs that are verified to be polymorphic in a population, are often very low. A number of potential causes of assay failure have been identified, but none have been explored systematically. In particular, as SNPs are often developed from transcriptomes, parameters relating to the genomic context are rarely taken into account. Here, we assembled a draft Antarctic fur seal (Arctocephalus gazella) genome (assembly size: 2.41 Gb; scaffold/contig N50: 3.1 Mb/27.5 kb). We then used this resource to map the probe sequences of 144 putative SNPs genotyped in 480 individuals. The number of probe‐to‐genome mappings and alignment length together explained almost a third of the variation in validation success, indicating that sequence uniqueness and proximity to intron–exon boundaries play an important role. The same pattern was found after mapping the probe sequences to the Walrus and Weddell seal genomes, suggesting that the genomes of species divergent by as much as 23 million years can hold information relevant to SNP validation outcomes. Additionally, reanalysis of genotyping data from seven previous studies found the same two variables to be significantly associated with SNP validation success across a variety of taxa. Finally, our study reveals considerable scope for validation rates to be improved, either by simply filtering for SNPs whose flanking sequences align uniquely and completely to a reference genome, or through predictive modelling.
Comparison of robustness against missing values of alternative decision tree and multiple logistic regression for predicting clinical data in primary breast cancer

Nomogram based on multiple logistic regression (MLR) is a standard technique for predicting diagnostic and treatment outcomes in medical fields. However, the applicability of MLR to data mining of clinical information is limited. To overcome these issues, we have developed prediction models using ensembles of alternative decision trees (ADTree). Here, we compare the performance of MLR and ADTree models in terms of robustness against missing values. As a case study, we employ datasets including pathological complete response (pCR) of neoadjuvant therapy, one of the most important decision-making factors in the diagnosis and treatment of primary breast cancer. Ensembled ADTree models are more robust against missing values than MLR. Sufficient robustness is attained at low boosting and ensemble number, and is compromised as these numbers increase.