Miracle-dz/UniFAR-FTUs huggingface dataset:
A general model of multivalent binding with ligands of heterotypic subunits and multiple surface receptors

Multivalent cell surface receptor binding is a ubiquitous biological phenomenon with functional and therapeutic significance. Predicting the amount of ligand binding for a cell remains an important question in computational biology as it can provide great insight into cell-to-cell communication and rational drug design toward specific targets. In this study, we extend a mechanistic, two-step multivalent binding model. This model predicts the behavior of a mixture of different multivalent ligand complexes binding to cells expressing various types of receptors. It accounts for the combinatorially large number of interactions between multiple ligands and receptors, optionally allowing a mixture of complexes with different valencies and complexes that contain heterogeneous ligand units. We derive the macroscopic predictions and demonstrate how this model enables large-scale predictions on mixture binding and the binding space of a ligand. This model thus provides an elegant and computationally efficient framework for analyzing multivalent binding.
The Crystal Structure of Bannisterite

The crystal structure of bannisterite, a modulated, mica-like mineral species, of general composition Ca0.5(K,Na)0.5(Mn,Fe,Mg,Zn)10(Si,Al)16O38(OH)8·nH2O, has been solved and refined for specimens from Franklin Furnace, New Jersey (FF), and Broken Hill, Australia (BH). The crystals are mono-clinic in space group A2/a, with (for FF) a = 22.265(1) Å, b = 16.368(1) Å, c = 24.668(2) Å = 94.285(5)°; and (for BH) a = 22.286(1) Å, b = 16.386(1) Å, c = 24.575(2) Å, α = 94.355(7)°; Z = 8. Refinement with anisotropic thermal factors reached Rw = 0.034 (FF) and 0.039 (BH). Like stilpnomelane and ganophyllite, bannisterite has a modified 2:1 trioctahedral layer structure in which some of the tetrahedra are inverted towards the interlayer region and linked to inverted tetrahedra in the opposite layer. The octahedral sheet is strongly corrugated along b. The tetrahedral sheet consists of 5-, 6-, and 7-fold rings, and bond distance calculations indicate that Al is concentrated into two of the four inverted tetrahedra. The interlayer Ca, K, and H2O species are highly disordered, as indicated by anomalously large temperature factors and partial occupancies. Localized differences in the Al/Si arrangements in the inverted tetrahedra induce disorder among the interlayer cations.
Longer study length, standardized sampling techniques, and broader geographic scope leads to higher likelihood of detecting stable abundance patterns in long term black-legged tick studies

Background Understanding how study design and monitoring strategies shape inference within, and synthesis across, studies is critical across biological disciplines. Many biological and field studies are short term and limited in scope. Monitoring studies are critical for informing public health about potential vectors of concern, such as Ixodes scapularis (black-legged ticks). Black-legged ticks are a taxon of ecological and human health concern due to their status as primary vectors of Borrelia burgdorferi, which causes Lyme disease. However, variation in black-legged tick monitoring, and gaps in data, are currently considered major barriers to understanding population trends and in turn, predicting Lyme disease risk. To understand how variable methodology in black-legged tick studies may influence which population patterns researchers find, we conducted a data synthesis experiment. Materials and Methods We searched for publicly available black-legged tick abundance datasets that had at least 9 years of data, using keywords about ticks in internet search engines, literature databases, data repositories and public health websites. Our analysis included 289 datasets from 7 surveys from locations throughout the US, ranging in length from 9 to 24 years. We used a moving window analysis, which is a kind of non-random resampling approach, to investigate the temporal stability of black-legged tick population trajectories across the US. We then used t-tests to assess differences in stability time across different study parameters. Results All of our sampled datasets required 4 or more years to reach stability. We also found that several study factors can have an impact on the likelihood of a study reaching stability and of data resulting in misleading results if the study does not reach stability. Specifically, datasets collected via dragging reached stability significantly faster than data collected via opportunistic sampling. Datasets that sampled larva reached stability significantly later than those that sampled adults or nymphs. Additionally, datasets collected at the broadest spatial scale (county) reached stability fastest. Conclusion We used 289 datasets from 7 long term black-legged tick studies to conduct a non-random data resampling experiment, revealing that sampling design does shape inferences in black-legged tick population trajectories and how many years it takes to find stable patterns. Specifically, our results show the importance of study length, sampling technique, life stage, and geographic scope in understanding black-legged tick populations, in the absence of standardized surveillance methods. Current public health efforts based on existing black-legged tick datasets must take monitoring study parameters into account, to better understand if and how to use monitoring data to inform decision making. We also recommend that potential forecasting initiatives consider these parameters when projecting black-legged tick population trends.
Über die Oxydation von Ascorbinsäure durch salpetrige Säure Teil IV: Die Reaktion nullter Ordnung. 16. Mitteilung über Reduktone und Tricarbonylverbindungen

At pH ca. 4 the rate of oxidation of ascorbic acid and of phenylhydroxytetronic acid by nitrous acid in the presence of excess nitrite ions is found to be independent of reductone concentration. The rate law is k2 was evaluated both in water and in aqueous dioxan. Under the same conditions the two reductones gave the same value of K2.
New Synthesis of Single‐Crystalline InVO4 Nanorods Using an Ionic Liquid

In this work, single-crystalline InVO4 nanorods were first prepared by a solution-phase approach in the presence of an ionic liquid 1-n-butyl-3-methylimidazolium tetrafluoroborate ([BMIM] [BF4]), which could act as a cosolvent and a structure-directing agent in the system. The diameters could be varied easily by subjecting the mixed precursor to different heat treatment temperatures or different durations of time in an oven. Unlike other nanorods synthesized by the microwave-assisted method, the InVO4 nanorods were stable under electron beam irradiation.
Stability of N-channel polysilicon thin-film transistors with ECR plasma thermal gate oxide

The effects of electrical stress on n-channel polysilicon thin-film transistors (poly-Si TFTs) with electron cyclotron resonance (ECR) plasma gate oxide have been investigated. The plasma-hydrogenerated low-temperature (/spl les/600/spl deg/C) TFT's exhibited very a small increase of threshold voltage (/spl Delta/V/sub th/<0.3 V) under the stress conditions (V/sub gs/=15 V, V/sub ds/=0 V /spl sim/15 V, and stress time=5/spl times/10/sup 4/ s). The /spl Delta/V/sub t/h was larger for the stress in the linear region than in the saturation region. It was found that the device degradation for the stress in the saturation region was caused by the hot-carriers. Increase of OFF current was maximum for the stress at V/sub gs/=V/sub ds/ while for the stress at V/sub gs/
A review of factors affecting traceability in agrifood supply chain

The efficiency of a traceability system lies on the ability to collect information related to product quality and consumer safety. There is a wide range of traceability systems currently used in food chains; from paper-based to IT enabled. In this paper, the different approaches given in literature on the requirements of a successful traceability support system are reviewed, and the factors that influence the effectiveness of traceability in the agrifood sector are identified. Moreover, the objectives of such system were determined as well as its individual operations, the needs and the attitude of agrifood industry toward such systems.
Basics of M‐theory

This is a review article of eleven dimensional supergravity in which we present all necessary calculations, namely the Noether procedure, the equations of motion (without neglecting the fermions), the Killing spinor equation, as well as some simple and less simple supersymmetric solutions to this theory. All calculations are printed in much detail and with explicit comments as to how they were done. Also contained is a simple approach to Clifford algebras to prepare the grounds for the harder calculations in spin space and Fierz identities.
Biosurfactants: Properties and Applications

Biosurfactants are amphiphilic compounds produced on living surfaces, mostly on microbial cell surfaces, or excreted extracellularly and contain hydrophobic and hydrophilic moieties that confer the ability to accumulate between fluid phases, thus reducing surface and interfacial tension at the surface and interface respectively. Biosurfactants have gained importance in the fields of enhanced oil recovery, environmental bioremediation, food processing and pharmaceuticals owing to their unique properties such as higher biodegradability and lower toxicity. Rhamnolipids from Pseudomonas aeruginosa, surfactin from Bacillus subtilis, emulsan from Acinetobacter calcoaceticus and sophorolipids from Candida bombicola are some examples of microbial-derived surfactants. Interest in the production of biosurfactants has steadily increased during the past decade. However, largescale production of these molecules has not been realized because of low yields in production processes and high recovery and purification costs. This article describes some applications and properties of biosurfactants.
Unequal effects of the economic cycle on human capital investment. Evidence from Italian panel data

Human Capital Theory considers individuals' education as an investment in terms of money, time, effort, and the renouncement of income opportunities that they expect will be compensated during their working life. While these benefits are mainly in the long run, direct and indirect costs are conditioned by the present circumstances, and in particular, by the macroeconomic conditions. The literature investigating the influence of the business cycle on enrolment decisions often suggests a counter-cyclical relationship without considering that economic fluctuations can produce heterogeneous effects among households facing different economic situations. Through a fixed effects regression based on panel data from the Italian component of the EU-SILC survey, I find the existence of a counter-cyclical propensity to enrol that is symmetric to the stages of the economic cycle. However, after disaggregating the analysis by household income quartiles, results show that a 1% increase in GDP reduces the probability of the poorest individuals being enrolled in noncompulsory education by 1.2%, while the wealthier portion of the population shows an a-cyclical relationship. The policy implications of these results are particularly important as they suggest that measures directed towards youths from poorer households to promote their enrolment in non-compulsory education should be strengthened when economic conditions improve. Keyword: Economic cycle; Educational economics; Human capital; Rate of return. JEL Classification: A22, E32, I23, I24. * Department of Economics ‘Marco Biagi’, University of Modena and Reggio Emilia, GLO. E-mail: luca.bonacini@unimore.it. Address: Via Jacopo Berengario 51, 41121, Modena, Italy.
A mechanistic study of the oxidation of phenol by OH/NO2/NO3 in aqueous solution

The flash photolysis of nitrate anions at λ = 248 nm and peroxydisulfate anions at λ = 351 nm was used to study the oxidation process of phenol by OH/NO2 and NO3/NO2in aqueous solution under different experimental conditions. Two different mononitrophenols (isomer ortho- and para-) and a dihydroxy derivative (catechol) were identified as the main reaction products by means of HPLC-DAD-ED technique and their yields of formation where directly compared with the initial radical concentrations of OH, NO2 and NO3, respectively. Product yields were determined for different pH and as a function of the number of laser photolysis pulses down to single pulse experiments, where yields of 70 nM o-nitrophenol, 60 nM p-nitrophenol and 10 nM catechol have been obtained starting with [OH]0 = [NO2]0 = 160 nM leading to the formation of 50 nM of NO3 radicals at pH = 0.5 and T = 298 K. From single pulse experiments under varying conditions a mechanism involving (i) initial attack of phenol by OH and (ii) by initial attack of NO3 followed by the reaction of the intermediate with NO2 is suggested. Absolute product yields are determined. For OH/NO2 the o-/p-nitrophenol product ratio is ρ = 1.5 whereas for the NO3/NO2 reaction sequence it is ρ = 1.0. Implications for tropospheric chemistry are discussed.
KRLSMDA: Identifying Human miRNA–Disease Association Based on Similarity and Kronecker Regularized Least Squares Method

A growing number of studies have suggested that miRNAs (microRNAs) have associations with human diseases, the design and discovery of drug. But so far, we do not yet fully understand the molecular mechanism of miRNAs in the development of human diseases. Predicting miRNA-disease associations is helpful for understanding the molecular mechanism of miRNAs in the development of human diseases. However, wet-lab experiments are time-consuming and need higher costs to discover miRNA-disease associations. Some computational methods are proposed for predicting miRNA-disease associations, but the prediction performance of these methods needs to be further improved. In this study, we propose a new computational model (KRLSMDA) based on similarity and the Kronecker Regularized Least Squares algorithm. In KRLSMDA, the miRNA functional similarity, the miRNA sequence similarity and the Gaussian Interaction Profile (GIP) kernel similarity are integrated into the comprehensive miRNA similarity. Then we compute the disease semantic similarity, disease functional similarity and the GIP kernel similarity to construct the comprehensive disease similarity based on the disease semantic information, the disease functional information and known miRNA-disease associations, respectively. Finally, the kronecker regularized least squares algorithm is used to predict hidden miRNA-disease associations. The experimental results show that KRLSMDA has achieved the average Area Under the Curve (AUC) values of 0.9181±0.032 and 0.9267±0.022 in 5-fold Cross-Validation (5CV) and 10-fold Cross-Validation (10CV), respectively, which demonstrates KRLSMDA is superior to four competing models. We expect KRLSMDA to be a supplement in the field of biomedical research in the future.
An Alternative Method for Traffic Accident Severity Prediction: Using Deep Forests Algorithm

Traffic safety has always been an important issue in sustainable transportation development, and the prediction of traffic accident severity remains a crucial challenging issue in the domain of traffic safety. A huge variety of forecasting models have been proposed to meet this challenge. These models gradually evolved from linear to nonlinear forms and from traditional statistical regression models to current popular machine learning models. Recently, a machine learning algorithm called Deep Forests based on the decision tree ensemble has aroused widespread concern, which was proposed for the first time by a research team of Nanjing University. This algorithm was proved to be more accurate and robust in comparison with other machine learning algorithms. Motivated by this benefit, this study employs the UK road safety dataset to propose a novel method for predicting the severity of traffic accidents based on the Deep Forests algorithm. To verify the superiority of our proposed method, several other machine learning algorithm-based perdition models were implemented to predict traffic accident severity with the same dataset, and the prediction results show that the Deep Forests algorithm present good stability, fewer hyper-parameters, and the highest accuracy under different level of training data volume. It is expected that the findings from this study would be helpful for the establishment or improvement of effective traffic safety system within a sustainable transportation system, which is of great significance for helping government managers to establish timely proactive strategies in traffic accident prevention and effectively improve road traffic safety.
Letter. The influence of atomic size and charge of dissolved species on the diffusivity and viscosity of silicate melts

Abstract Molecular dynamics simulations are used to determine how a dissolved species alters the transport properties of a silicate melt. To identify the specific factors that affect the transport properties, we examine the effects of generic dissolved species for which the atomic interaction parameters can be systematically varied. We focus on the role of the size and charge of the dissolved species. Our results show that neutral dissolved species have negligible effects on the structure and bonding of the silica network, regardless of the size of the species. These neutral species are decoupled from the network, and can diffuse orders of magnitude faster than the network ions. In contrast, charged species strongly disrupt the silica network, which leads to significant enhancement of the transport properties (e.g., lower viscosity and higher diffusivity of the network ions). The effects of the charged dissolved species are strongly dependent on their size
Towards Revealing Parallel Adversarial Attack on Politician Socialnet of Graph Structure

Socialnet becomes an important component in real life, drawing a lot of study issues of security and safety. Recently, for the features of graph structure in socialnet, adversarial attacks on node classification are exposed, and automatic attack methods such as fast gradient attack (FGA) and NETTACK are developed for per-node attacks, which can be utilized for multinode attacks in a sequential way. However, due to the overlook of perturbation influence between different per-node attacks, the above sequential method does not guarantee a global attack success rate for all target nodes, under a fixed budget of perturbation. In this paper, we propose a parallel adversarial attack framework on node classification. We redesign new loss function and objective function for nonconstraint and constraint perturbations, respectively. /rough constructing intersection and supplement mechanisms of perturbations, we then integrate node filtering-based P-FGA and P-NETTACK in a unified framework, finally realizing parallel adversarial attacks. Experiments on politician socialnet dataset Polblogs with detailed analysis are conducted to show the effectiveness of our approach.
Survey of Centralized and Decentralized Access Control Models in Cloud Computing

In recent years, cloud computing has become a popular option for a number of different businesses sectors. It is a paradigm employed to deliver a range of computing services, such as sharing resources via the Internet. Security issues in cloud computing necessitates the need for a mechanism to keep the system safe and reliable. An access control mechanism is one that permits or denies access to cloud services. This paper presents a survey of access control models in Cloud Computing. Several existing surveys on access control mechanisms in cloud computing mainly focused on traditional access control models and encryption-based access control models while the others focused on applying blockchain technology in cloud access control. However, access models possess different characteristics, such as the system’s reliance on a centralized cloud trusted system administrator to manage the access policy or adopting decentralized approach. This paper reviews and analyses existing access control mechanisms in cloud computing, based on centralized and decentralized access control models, provides detailed comparisons on each model’s advantages and limitations, and discusses the challenges of, and future research direction for access control.
1. Navarrete & Vargas ENG VF OK

Given that the democratisation of video games has allowed this industry to appropriate a series of themes traditionally the exclusive preserve of other expressive media, this work analyses the capacity of videoludic expression to elicit emotions and convey the seriousness of cancer by performing a comparative study with literature and cinema. To this end, three works (one per medium) were selected to be respectively read, viewed or played by all the study subjects (n=90). A two-step methodology was employed. Firstly, the concepts of emotion and narrative scheme were defined in the context of disciplines relating to the three media and then shared with the subjects. Secondly, once both variables, i.e. the concepts of emotion and narration, had been controlled, a questionnaire was designed to determine which of the three works comprising the corpus best conveyed the experience of cancer. The results reveal that the sample game, in spite of its shortcomings in character design, was judged to be the one that most poignantly described the development of the disease. Therefore, it is possible to claim that the common belief that video games are trivial devices, solely designed to entertain, contrasts with their true expressive ability to convey dramatic experiences.
A Comparative Study of Phenolic Content in Apple Fruits

The ethanol extracts of apple fruits harvested from the cultivars Aldas, Auksis, Ligol, and Lodel grown in Lithuania were analyzed by the high-performance liquid chromatography method. Chlorogenic acid was found to be a predominant component in the apple fruits of all the cultivars, except the cultivar Ligol. (–)-Epicatechin was the major compound in the ethanol extracts of apple fruits obtained from all the cultivars, while the amount of (+)–catechin was lower. The following quercetin glycosides were identified and quantified: hyperoside, isoquercitrin, avicularin, rutin, and quercitrin. Hyperoside was the major quercetin glycoside in apple fruits.
Heritability of Fiber Strength in Genetically Engineered Cotton

Fiber strength must be increased for cotton to remain competitive as a textile fiber. The findings of a 2-yr study of cotton genetically engineered to express increased fiber strength are reported. Particle bombardment transformation of 'Deltapine 50' was accomplished by Monsanto. In field trials, fiber strength was increased by 25-75% over the non-transformed Deltapine 50. However, inconsistent expression of strength may prevent commercialization of cotton germplasm derived from this transformation. These data may have general implications for transgenic breeding in that transformation events imparting inconsistent expression of the value added trait should be discarded early in the breeding process.
Responsibility Research for Trustworthy Autonomous Systems

To develop and effectively deploy Trustworthy Autonomous Systems (TAS), we face various social, technological, legal, and ethical challenges in which different notions of responsibility can play a key role. In this work, we elaborate on these challenges, discuss research gaps, and show how the multidimensional notion of responsibility can play a role to bridge them. We argue that TAS requires operational tools to represent and reason about responsibilities of humans as well as AI agents. We review major challenges to which responsibility reasoning can contribute, highlight open research problems, and argue for the application of multiagent responsibility models in a variety of TAS domains.