Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of the Atlantic Meridional Overturning Circulation on atmospheric p CO 2 variations

Proxy records show large variability of atmospheric pCO2 on different timescales. Most often such variations are attributed to a forced response of the carbon cycle to changes in external conditions. Here, we address the problem of internally generated variations in pCO2 due to pure carbon cycle dynamics. We focus on the effect of the strength of Atlantic Meridional Overturning Circulation (AMOC) on such internal variability. Using the Simple Carbon Project Model v1.0 (SCP-M), which we have extended to represent a suite of nonlinear carbon cycle feedbacks, we efficiently explore the multi-dimensional parameter space to address the AMOC– pCO2 relationship. We find that climatic boundary conditions and the representation of biological production in the model are most important for this relationship. When climate sensitivity in our model is increased, we find intrinsic oscillations due to Hopf bifurcations with multi-millennial periods. The mechanism behind these oscillations is clarified and related to the coupling of atmospheric pCO2 and the alkalinity cycle, via the river influx and the sediment outflux. This mechanism is thought to be relevant for explaining atmospheric pCO2 variability during glacial cycles.
Forensic Identification of ornate flying snake (Chrysopelea ornata ) through COX2

: Wildlife forensics deals with the identification of the animals and animal products that are confiscated during smuggling, trading, and illegal possession of the animals. Though identification of species can be done physically, it is not be possible at all times. However, identification at molecular level is one of the fail proof method to make sure of the animal in possession. Chrysopelea ornata also known as gliding snake, golden tree snake and ornate flying snake is unique in reptiles, as it is the only snake species from Colubridae family that can modify its body to glide from one tree to another. This makes the snake one of the exotic pet in trade. Over the years, researchers have standardised the identification of any animal species and its by-products with the help of DNA barcoding. Animal by products that are caught during smuggling or possession of those by products that are illegal to possess with oneself are at times hard to identify from the fake ones. Among the genes that are used to identify the animal are COX1 or COI, CYT-B, 12s and 16s. Along with the above-mentioned genes, it has proven that COX2 gene can also be used to identify the species. This research for the first time has isolated COX2 region of Chrysopelea ornate and has submitted it to NCBI. Which will be helpful in identification of Chrysopelea ornata.
Identification ofMolecularMechanismofOSAwithHypertension Based on Multiple Microarray Analysis

Purpose. OSA is closely associated with hypertension, and both epidemiological and experimental studies have conrmed that OSA is one of the most important independent risk factors for hypertension. e pathological mechanisms by which OSA causes hypertension are not well understood, and in this paper, we explored the molecular mechanisms by which OSA may mediate hypertension at the bioinformatics level. Materials and Methods. We downloaded disease-related datasets from the GEO public database, calculated the dierential genes between the two groups of patients by the limma package, and then further constructed the WGCNA network based on the clinical characteristics of patients to explore the important regulatory genes in the disease. Subsequently, ssGSEA was used to explore the potential molecular mechanisms of disease progression and GSVA was applied to analyze the specic signaling pathways. Finally, we performed real-time quantitative PCR (qRT-PCR) to validate these pivotal genes. Results. ree genes were selected as target genes, namely, GPR179, RNF150, and JPH4. e results showed they were strongly correlated with immune cell content that high expression of the three core genes was associated with myogenesis, angiogenesis, oxidation, metabolism, and PI3K/AKT/mTOR pathways. qRT-PCR validated that all three genes have statistically signicant dierences between the OSA group and OSA combined with hypertension group. Conclusion. Our study provides new evidence for the potential molecular mechanisms of OSA combined with hypertensive disease as well as diagnosis and treatment.
CANTALOUPE SEEDS: ACTIVITIES AND BENEFITS A COMPLETE GUIDE

: - Melon (Cucumis melo L.) has a high economic value, and its production has increased in recent years; however, a portion of the fruit is wasted. During processing and consumption, inedible parts such as peel and seeds are typically discarded. Melon residue extracts were studied and their phenolic compounds, antioxidants, and antiproliferative activities were investigated. Melon, due to its pleasant taste and diverse chemical composition, is an excellent source of biologically active compounds for humans. Melon contains glucose, fructose, vitamin A, D, C, K, E, and some vitamins from group B. Total phenolic compounds were discovered in hydroethanolic, hydromethanolic, and aqueous extracts, particularly melon peel (1.016 mg gallic acid equivalent/100 g). The total flavonoid content of melon peel aqueous extract was found to be 262 mg of catechin equivalent (CA)/100 g. Significant amounts of gallic acid, catechin, and eugenol were found in all melon peel extracts. Total antioxidant capacity, expressed as ascorbic acid equivalent, was 89, 74, and 83 mg/g for hydroethanolic and hydromethanolic extracts in peels and hydromethanolic extracts in seeds, respectively. Cold pressing was used to extract the oil from the seeds, which was then tested for parameters such as iodine value, saponification value, and fatty acid profile. The findings revealed a high iodine value as well as the presence of polyunsaturated fatty acids like omega-6 (linoleic acid) and monounsaturated fatty acids like omega-9 (oleic acid). It also contains saturated fatty acids like palmitic and stearic acid. The seeds offer potential for development as value-added products, dietary supplements, and medicines.
Evaluation of a Tutoring and Mentoring Model in Distance Higher Education

This paper reports a model of tutorial guidance and mentoring in college that has been implemented at the Spanish National University for Distance Education for two academic years, in order to welcome new students and provide them with orientation, thus enhancing the quality of their academic transition and early adjustment. Designed with the distance methodology, the model incorporates the role of the advisor (played by a faculty mentor) and peer mentors (senior students) and combines the use of e-mentoring with face-to-face mentoring. This guidance intervention is organised around the Tutorial Guidance Plan, starting with web-based specific training for those involved. Thus, new students can receive guidance and advice from a personal advisor and a peer mentor for at least their first year at university. The programme was validated using a complex research design to assess the process and product. Data were collected using ad-hoc questionnaires, interviews, diaries, records and discussion groups. The results corroborate the benefits participants gained from this mode of guidance. The evaluations describe students' orientation needs, the evolution of the helping relationship, the points it addressed and the means of communication used. A general assessment of the programme and the satisfaction of participants' expectations is also given. From the assessment of benefits, it is concluded that the model is viable and applicable in distance higher education. Also, the model makes it possible to demonstrate the suitability of this methodology for achieving a flexible mentoring relationship tailored to the needs of each student.
Broadening Access to Text Analysis by Describing Uncertainty: Preliminary White Paper

—We describe work in progress on a project that aims to quantify the distortion introduced into real research questions by two kinds of noise: 1) OCR error and 2) inclusion of paratext that isn’t actually in the target genre. Data for the project has been organized, and initial experiments on all questions have been run, but ﬁnal conclusions are still being drawn.
A comprehensive evaluation of the use of Lagrangian particle dispersion models for inverse modeling of greenhouse gas emissions

Abstract. Using the example of sulfur hexafluoride (SF6), we investigate the use of Lagrangian particle dispersion models (LPDMs) for inverse modeling of greenhouse gas (GHG) emissions and explore the limitations of this approach. We put the main focus on the impacts of baseline methods and the LPDM backward simulation period on the a posteriori emissions determined by the inversion. We consider baseline methods that are based on a statistical selection of observations at individual measurement sites and a global-distribution-based (GDB) approach, where global mixing ratio fields are coupled to the LPDM back-trajectories at their termination points. We show that purely statistical baseline methods can cause large systematic errors, which lead to inversion results that are sensitive to the LPDM backward simulation period and can generate unrealistic global total a posteriori emissions. The GDB method produces a posteriori emissions that are far less sensitive to the backward simulation period and that show a better agreement with recognized global total emissions. Our results show that longer backward simulation periods, beyond the often used 5 to 10 d, reduce the mean squared error and increase the correlation between a priori modeled and observed mixing ratios. Also, the inversion becomes less sensitive to biases in the a priori emissions and the global mixing ratio fields for longer backward simulation periods. Further, longer periods might help to better constrain emissions in regions poorly covered by the global SF6 monitoring network. We find that the inclusion of existing flask measurements in the inversion helps to further close these gaps and suggest that a few additional and well-placed flask sampling sites would have great value for improving global a posteriori emission fields.
Running head: K + transporters in roots of higher plants

Summary: We demonstrate fundamental differences in steady-state K + uptake mechanisms 13 between NH 4 + -grown barley and Arabidopsis , and show that sudden NH 4 + withdrawal uncovers 14 dramatic capacity and plasticity of K + transport amongst the two model species. ABSTRACT 21 The role of potassium (K + ) transporters in high- and low-affinity K + uptake was examined in 22 roots of intact barley ( Hordeum vulgare L.) and Arabidopsis thaliana L. plants by use of 42 K 23 radiotracing, electrophysiology, pharmacology, and mutant analysis. Comparisons were made 24 between results from barley and five genotypes of Arabidopsis thaliana L. , including single- and 25 double-knock-out mutants for the high-affinity transporter, AtHAK5, and the Shaker-type 26 channel, AtAKT1. In Arabidopsis , steady-state K + influx at low external [K + ] ([K + ] ext = 22.5 27 µM) was predominantly mediated by AtAKT1 when high-affinity transport was inhibited by 28 NH 4+ , while in barley, by contrast, K + channels could not operate below 100 µM. Withdrawal of 29 NH 4 + resulted in an immediate and dramatic stimulation of K + influx in barley, indicating a shift 30 from active to passive K + uptake at low [K + ] ext and yielding fluxes as high as 36 µmol g (root 31 fresh weight) -1 h -1 at 5 mM [K + ] ext – among the highest transporter-mediated K + fluxes hitherto 32 reported. This ammonium-withdrawal effect (AWE) was also established in all Arabidopsis lines 33 (WTs, atakt1 , athak5 , and athak5 atakt1 ), at low [K + ] ext , revealing the concerted involvement of 34 several transport systems. AWE coincided with a suppression of K + efflux and a significant 35 hyperpolarization of the plasma membrane in all genotypes except athak5 atakt1 , could be 36 sustained over 24 h, and resulted in increased tissue K + accumulation. We discuss key 37 differences and similarities in K + acquisition between two important model systems and reveal 38 novel aspects of K + transport in planta .
BROADENING THE UTILIZATION OF CSMIP DATA: DOUBLE CONVOLUTION METHODOLOGY TOWARDS DEVELOPING INPUT MOTIONS FOR SITE RESPONSE AND NONLINEAR DEFORMATION ANALYSES

The double convolution methodology for the development of input motions for site response analyses and nonlinear deformation analyses is presented, and challenges associated with its development and implementation are discussed. This methodology uses deep VS profiles and random vibration theory to modify ground motions recorded on soil sites such that they are compatible with conditions at a selected depth within a deposit. This selected depth is commonly the base of a numerical domain for a 1D or 2D response analysis, i.e. halfspace. Ongoing efforts in the development of this methodology focus on constraining the ground motions’ high-frequency content, where unrealistic amplification may be estimated. Two approaches for addressing this issue are presented using examples in California.
I NVERTIBLE NEURAL NETWORKS FOR E3SM LAND MODEL CALIBRATION AND SIMULATION

We apply an invertible neural network (INN) for E3SM land model (ELM) calibration and simulation with eight parameters at the Missouri Ozark AmeriFlux forest site. INN provides bijective (two-way) mappings between inputs and outputs, thus it can solve probabilistic inverse problems and forward approximations simultaneously. We demonstrate INN’s inverse and forward capability in both synthetic and real-data applications. Results indicate that INN produces accurate parameter posterior distributions similar to Markov Chain Monte Carlo sampling and it generates model outputs close to the ELM simulations. Additionally, both the inverse and forward evaluations in INN are computationally efﬁcient which allows for rapid integration of observations for parameter estimation and fast model predictions.
Thermally Sprayed Hydrodynamic Main Bearings for Wind Turbines

At present, main bearings in wind turbines are equipped with rolling bearings without exception. Sliding bearings instead can offer a number of advantages, including easier maintenance and extended lifetime. While conventional manufacturing processes for large sliding bearings face their limits regarding processable materials, thermal spraying can provide an effective alternative to meet the requirements by applying coating systems on the bearing surfaces. Within this study a wide range of different feedstock materials based on standard bearing materials and common wear and friction reducing coating systems are investigated. The coatings are tested on tribometers based on the load distribution within the main bearing at critical operating conditions of the wind turbine gained from a validated simulation model. A tribological methodology is developed to investigate the application related properties of the thermally sprayed coatings. The effects of load and geometry of the counter body on the friction and wear behavior of the coatings are investigated using a pin-on-disc and a modified high-load ring-on-disc tribometer. The presented results provide a major contribution to the purpose of identifying an appropriate coating system to meet the requirements of slow-moving and highly loaded sliding bearings.
Sensitivity of NEMO4.0-SI3 model parameters on sea ice budgets in the Southern Ocean

Abstract. The seasonally dependent Antarctic sea ice concentration (SIC) budget is well observed and synthesizes many important air–sea–ice interaction processes. However, it is rarely well simulated in Earth system models, and means to tune the former are not well understood. In this study, we investigate the sensitivity of 18 key NEMO4.0-SI3 (Nucleus for European Modelling of the Ocean coupled with the Sea Ice Modelling Integrated Initiative) model parameters on modelled SIC and sea ice volume (SIV) budgets in the Southern Ocean based on a total of 449 model runs and two global sensitivity analysis methods. We found that the simulated SIC and SIV budgets are sensitive to ice strength, the thermal conductivity of snow, the number of ice categories, two parameters related to lateral melting, ice–ocean drag coefficient and air–ice drag coefficient. An optimized ice–ocean drag coefficient and air–ice drag coefficient can reduce the root-mean-square error between simulated and observed SIC budgets by about 10 %. This implies that a more accurate calculation of ice velocity is the key to optimizing the SIC budget simulation, which is unlikely to be achieved perfectly by simply tuning the model parameters in the presence of biased atmospheric forcing. Nevertheless, 10 combinations of NEMO4.0-SI3 model parameters were recommended, as they could yield better sea ice extent and SIC budgets than when using the standard values.
Precoding Design and Sum Rate upper bound of RSMA Using Interference Nulling

Rate-splitting multiple access (RSMA) is a new multiple access technique that improves limitations of conventional multiple access techniques. RSMA manages interference by precoding at the transmitter and successive interference cancellation (SIC) at the receivers. Several precoding design approaches are considered in the literature that propose algorithms to solve a joint optimization problem. In this work, we focus on a special class of RSMA that nulls the interference of streams that must not be decoded, i.e., RSMA with interference nulling (RSMA-IN). We consider a sum rate maximization problem subject to a total power constraint and interference nulling (IN). To address the performance of precoding design algorithms relative to the optimal sum rate of RSMA-IN, we propose a convex upper bound problem for RSMA-IN sum rate and compare its performance with that of the precoding design algorithms. Further, to take advantage of the cases where the upper bound problem achieves the optimal sum rate, we propose an upper bound aided (UBA) algorithm to both enhance the performance and reduce the complexity of existing precoding design algorithms. Simulation results show that the performance of the UBA algorithm is close to the optimal sum rate of RSMA-IN.
Time-division TCP for reconfigurable data center networks

Recent proposals for reconfigurable data center networks have shown that providing multiple time-varying paths can improve network capacity and lower physical latency. However, existing TCP variants are ill-suited to utilize available capacity because their congestion control cannot react quickly enough to drastic variations in bandwidth and latency. We present Time-division TCP (TDTCP), a new TCP variant designed for reconfigurable data center networks. TDTCP recognizes that communication in these fabrics happens over a set of paths, each having its own physical characteristics and cross traffic. TDTCP multiplexes each connection across multiple independent congestion states---one for each distinct path---while managing connection-wide tasks in a shared fashion. It leverages network support to receive timely notification of path changes and promptly matches its local view to the current path. We implement TDTCP in the Linux kernel. Results on an emulated network show that TDTCP improves throughput over both traditional TCP variants, such as DCTCP and CUBIC, and multipath TCP by 24--41% without requiring significant in-network buffering to hide path variations.
LINSCAN - A Linearity Based Clustering Algorithm

DBSCAN is a very powerful algorithm for clustering in domains where few assumptions can be made about the structure of the data. In this paper, we hope to leverage these strengths for more specialized clustering tasks where the standard al-gorithm fails. In particular, by embedding points as normal distributions approximating their local neighborhoods and leveraging a distance function derived from the Kullback Leibler Divergence, we hope to create an algorithm which can distinguish highly linear clusters that are spatially close but have orthogonal covariances. We then apply this to the identiﬁcation of slip faults via measuring seismic activity.
CliSAT : a SAT-based exact algorithm for hard maximum clique problems

Given a graph, the maximum clique problem (MCP) asks for determining a complete subgraph with the largest possible number of vertices. We propose a new exact algorithm, called CliSAT , to solve the MCP to proven optimality. This problem is of fundamental importance in graph theory and combinatorial optimization due to its practical relevance for a wide range of applications. The newly developed exact approach is a combinatorial branch-and-bound algorithm that exploits the state-of-the-art branching scheme enhanced by two new bounding techniques with the goal of reducing the branching tree. The ﬁrst one is based on graph colouring procedures and partial maximum satisﬁability problems arising in the branching scheme. The second one is a ﬁltering phase based on constraint programming and domain propagation techniques. CliSAT is designed for structured MCP instances which are computationally diﬃcult to solve since they are dense and contain many interconnected large cliques. Extensive experiments on hard benchmark instances, as well as new hard instances arising from diﬀerent applications, show that CliSAT outperforms the state-of-the-art MCP algorithms by several orders of magnitude.
Optimization Model of Mathematics Instructional Mode Based on Deep Learning Algorithm

This paper proposes corresponding teaching methods and instructional modes based on predecessors' research on mathematics instructional mode and the current state of mathematics teaching. In addition, this paper constructs a teaching evaluation model based on DL algorithm based on an in-depth study of DL-related theories in order to accurately and scientifically analyze the problems that exist in mathematics teaching. This paper constructs an instructional quality evaluation index system based on rationality and fairness, and uses the BPNN evaluation model to train and study a set of instructional quality data. Finally, the experimental results show that this system has a high level of stability, with a 96.37 percent stability rate and a 95.42 percent evaluation accuracy rate. The results of this paper's evaluation of the mathematical instructional quality model are objective and reasonable. It can accurately assess instructional quality while also assessing problems in the teaching process based on the instructional quality scores and making reasonable recommendations for teaching improvement based on the weak links in the teaching process. It has the potential to provide a workable system for assessing instructional quality.