Miracle-dz/UniFAR-FTUs huggingface dataset:
Microheater-integrated zinc oxide nanowire microfluidic device for hybridization-based detection of target single-stranded DNA

Detection of cell-free DNA (cfDNA) has an impact on DNA analysis in liquid biopsies. However, current strategies to detect cfDNA have limitations that should be overcome, such as having low sensitivity and requiring much time and a specialized instrument. Thus, non-invasive and rapid detection tools are needed for disease prevention and early-stage treatment. Here we developed a device having a microheater integrated with zinc oxide nanowires (microheater-ZnO-NWs) to detect target single-stranded DNAs (ssDNAs) based on DNA probe hybridization. We confirmed experimentally that our device realized in-situ annealed DNA probes by which we subsequently detected target ssDNAs. We envision that this device can be utilized for fundamental studies related to nanobiodevice-based DNA detection.
Scaling up private land conservation to meet recovery goals for grassland birds

Long‐term population declines have elevated recovery of grassland avifauna to among the highest conservation priorities in North America. Because most of the Great Plains is privately owned, recovery of grassland bird populations depends on voluntary conservation with strong partnerships between private landowners and resource professionals. Despite large areas enrolled in voluntary practices through U.S. Department of Agriculture's Lesser Prairie‐chicken (Tympanuchus pallidicinctus) Initiative (LPCI), the effectiveness of Farm Bill investments for meeting wildlife conservation goals remains an open question. Our objectives were to evaluate extents to which Conservation Reserve Program (CRP) and LPCI‐grazing practices influence population densities of grassland birds; estimate relative contributions of practices to regional bird populations; and evaluate percentages of populations conserved relative to vulnerability of species. We designed a large‐scale impact‐reference study and used the Integrated Monitoring in Bird Conservation Regions program to evaluate bird population targets of the Playa Lakes Joint Venture. We used point transect distance sampling to estimate density and population size for 35 species of grassland birds on private lands enrolled in native or introduced CRP plantings and LPCI‐prescribed grazing. Treatment effects indicated CRP plantings increased densities of three grassland obligates vulnerable to habitat loss, and LPCI grazing increased densities of four species requiring heterogeneity in dense, tall‐grass structure (α = 0.1). Population estimates in 2016 indicated the practices conserved breeding habitat for 4.5 million birds (90% CI: 4.0–5.1), and increased population sizes of 16 species , totaling 1.8 million birds (CI: 1.4–2.4). Conservation practices on private land benefited the most vulnerable grassland obligate species (AICc weight = 0.53). By addressing habitat loss and degradation in agricultural landscapes, conservation on private land provides a solution to declining avifauna of North America and scales up to meet population recovery goals for the most imperiled grassland birds.
Individualized model for predicting COVID‐19 deterioration in patients with cancer: A multicenter retrospective study

The 2019 novel coronavirus has spread rapidly around the world. Cancer patients seem to be more susceptible to infection and disease deterioration, but the factors affecting the deterioration remain unclear. We aimed to develop an individualized model for prediction of coronavirus disease (COVID‐19) deterioration in cancer patients. The clinical data of 276 cancer patients diagnosed with COVID‐19 in 33 designated hospitals of Hubei, China from December 21, 2019 to March 18, 2020, were collected and randomly divided into a training and a validation cohort by a ratio of 2:1. Cox stepwise regression analysis was carried out to select prognostic factors. The prediction model was developed in the training cohort. The predictive accuracy of the model was quantified by C‐index and time‐dependent area under the receiver operating characteristic curve (t‐AUC). Internal validation was assessed by the validation cohort. Risk stratification based on the model was carried out. Decision curve analysis (DCA) were used to evaluate the clinical usefulness of the model. We found age, cancer type, computed tomography baseline image features (ground glass opacity and consolidation), laboratory findings (lymphocyte count, serum levels of C‐reactive protein, aspartate aminotransferase, direct bilirubin, urea, and d‐dimer) were significantly associated with symptomatic deterioration. The C‐index of the model was 0.755 in the training cohort and 0.779 in the validation cohort. The t‐AUC values were above 0.7 within 8 weeks both in the training and validation cohorts. Patients were divided into two risk groups based on the nomogram: low‐risk (total points ≤ 9.98) and high‐risk (total points > 9.98) group. The Kaplan‐Meier deterioration‐free survival of COVID‐19 curves presented significant discrimination between the two risk groups in both training and validation cohorts. The model indicated good clinical applicability by DCA curves. This study presents an individualized nomogram model to individually predict the possibility of symptomatic deterioration of COVID‐19 in patients with cancer.
LA(NH2SO3)3: EINKRISTALLE EINES WASSERFREIEN AMIDOSULFATES DER SELTEN-ERD-ELEMENTE DURCH SCHONENDE ENTWASSERUNG VON LA(NH2SO3)3.2,5 H2O

Farblose, transparente Einkristalle von La(NH2SO3)3 · 2,5 H2O (monoklin, I2/a, Z = 8, a = 1413,9(3), b = 929,7(1), c = 1910,6(6) pm, b = 105,59(2)°, Rall = 0,0203) bilden sich beim Einengen einer Losung von La2O3 in wasseriger Amidoschwefelsaure. Die Kristallstruktur enthalt La3+-Ionen, die neunfach von Sauerstoffatomen umgeben sind. Letztere gehoren zu sieben NH2SO3–-Gruppen und zwei H2O-Molekulen. Die Polyeder sind zu Schichten verknupft, welche durch Wasserstoffbrucken zusammengehalten werden. Zwischen den Schichten befinden sich auf spezieller Lage zusatzliche H2O-Molekule. Nach DTA-Untersuchungen verliert die Verbindung zwischen 93 und 136 °C in einem Schritt das Kristallwasser. Ab 350° zersetzt sich das Amidosulfat in zwei Stufen, wobei La2(SO4)3 zuruckbleibt. Die DTA-Ergebnisse werden durch temperaturabhangige Pulverdiffraktometrie bestatigt. Durch langsame Dehydratisierung von La(NH2SO3)3 · 2,5 H2O im Argonstrom wurden Einkristalle von La(NH2SO3)3 in Form farbloser, transparenter Saulen erhalten. In der Kristallstruktur (hexagonal, P63/m, Z = 2, a = 983,5(1), c = 588,03(7) pm, Rall = 0,0148) liegen neunfach von Sauerstoffatomen koordinierte La3+-Ionen vor. Die Sauerstoffatome gehoren zu neun NH2SO3–-Ionen, die ihrerseit von drei La3+ umgeben sind. Die NH2-Gruppierung der Ionen weist in Richtung von Kanalen, die entlang [001] gebildet werden. La(NH2SO3)3: Single Crystals of an Amidosulfate of the Rare-Earth Elements by controlled Dehydration of La(NH2SO3)3 · 2.5 H2O Colorless, transparent single crystals of La(NH2SO3)3 · 2.5 H2O (monoclinic, I2/a, Z = 8, a = 1413.9(3), b = 929.7(1), c = 1910.6(6) pm, b = 105.59(2)°, Rall = 0.0203) are obtained by evaporation of a solution of La2O3 in aqueous amidosulfuric acid. The crystal structure contains La3+ ions which are surrounded by nine by oxygen atoms which belong to seven NH2SO3– groups and two H2O molecules, respectively. The polyhedra are connected to sheets which are held together via hydrogen bonds. Between the sheets, additional H2O molecules are located on a special site of this space group. According to DTA investigations the compound dehydrates in the range of 93 and 136 °C in one step. Starting around 350° the amidosulfate decomposes in a two step process yielding La2(SO4)3. The DTA data were confirmed by temperature dependent X-ray powder diffractometry. Single crystals of La(NH2SO3)3 were obtained via slow dehydration of La(NH2SO3)3 · 2.5 H2O under flowing argon as colorless transparent rods. In the crystal structure (hexagonal, P63/m, Z = 2, a = 983.5(1), c = 588.03(7) pm, Rall = 0.0148) La3+ is ninefold coordinate from oxygen atoms of nine NH2SO3 groups which in turn are attached to three La3+ ions. The NH2 groups of the amidosulfate ions point towards channels along [001].
Short-term impact of the COVID-19 pandemic on patients with a chronic pain disorder

Abstract The current Covid-19 pandemic has already had a definite impact on the daily life of many people worldwide. It has been proposed that people with preexisting medical conditions will be harder hit by the pandemic and the subsequent measures to contain the spread of the disease. In this questionnaire-based, observational study, we aimed to assess the impact of the pandemic on patients with a chronic pain disorder, who are treated at a tertiary multidisciplinary pain center. Participants rated the impact of the pandemic on their chronic pain disorder using a self-designed questionnaire. Also, participants filled out the regular follow-up questionnaire to assess a chronic pain disorder measuring among other parameters pain intensity, symptoms of depression, anxiety, stress, and pain-related quality of life. Of 136 eligible patients who presented to our pain center between May 5th and July 17th, 112 agreed to participate in the study (82.4%). Eighty two participants (73.2%) reported a deterioration of the pain disorder using the self-designed questionnaire. The more robust parameters of the regular follow-up questionnaire showed no relevant changes compared to data collected before the pandemic. We were not able to detect any demographic and medical parameters that were clinically relevantly associated with a higher impact of the pandemic. We conclude that a chronic pain disorder is a relatively stable disease that does not change significantly due to external factors, like the Covid-19 pandemic, even if the subjective impact is perceived to be high.
Small-Scale Biogas-SOFC Plant: Technical Analysis and Assessment of Different Fuel Reforming Options

This paper investigates simulation results of the thermodynamic performance of a 25 kWel small-scale solid oxide fuel cell model fuelled with biogas. Hereby, biogas is produced from a predefined group of substrates, namely, livestock effluents, energy crops, agricultural waste, and organic waste. For the analysis, average methane (CH4) content is assumed to lie between 50 and 60 mol % as large seasonal and daily variations are observed which are independent of used matter. The main biogas contaminants are sulfur compounds, mostly in the form of H2S. Sulfur leads to fast catalyst deactivation in the reformer and fuel cell, which is why an effective gas-cleaning system is established. For this, ZnO and activated carbon are the most practical gas-cleaning solutions for small-scale plants. The energy model of the solid oxide fuel cell plant is designed and analyzed through detailed energy and mass balance calculations throughout all system components and streams. The above-mentioned model is set up in in such.
A general statistical mechanical approach for modeling redox thermodynamics: the reaction and reorganization free energies

By using rigorous statistical mechanical derivations we obtain a general theoretical model providing the thermodynamics of redox processes, with a focus on the reaction and reorganization free energies and on the relationship between these key thermodynamic quantities. In particular, we define two distinct reorganization free energies, λP and λR, for the reactants (R) → products (P) reaction and for the inverse process, respectively. We first derive in principle exact relationships, then gradually introduce different levels of approximation to obtain more and more simplified, though less general, working equations. The results of the calculation of thermodynamic properties for two model systems are then used to compare general and more approximated expressions and critically assess their applicability to the description of redox processes. Finally, we obtain specific relationships that can be used as a diagnostic tool to test the actual reliability of the assumption of Gaussian fluctuations, a priori accepted within Marcus theory, for any redox system under investigation. For both benchmark molecules studied in the present paper, the Gaussian approximation turns out to be inappropriate to describe the redox thermodynamics.
Influence of 2-propanol on adsorption equilibria of α-and δ-tocopherol from supercritical carbon dioxide on silica gel

Knowledge of thermodynamic functions describing adsorption isotherms is of much importance for the design and optimization of adsorption processes. This work deals with the investigation of the adsorption behavior under the influence of a modifier. The experimental setup consisted of two supercritical fluid chromatography units. Adsorption isotherms of α- and 6-tocopherol were determined at a pressure of 20 MPa and a temperature of 313 K. The stationary phase was an unmodified silica gel, and supercritical carbon dioxide was used as the mobile phase. The modifier 2-propanol was added to the mobile phase in contents of 4.6, 5.5, and 6.5 % mass fraction. The experimental results of pure substances were described with cubic Hill isotherms. The adsorption equilibria of the mixture were predicted with the ideal adsorbed solution theory and verified with experimentally determined data.
The dynamics of succinonitrile in the plastic phase by subpicosecond time‐resolved optical Kerr effect

The relaxation kinetics of succinonitrile in the plastic crystalline phase has been investigated between 250 and 320 K by transient optical Kerr effect with femtosecond pulses. Three different noninstantaneous contributions to the signal time profile have been identified. The fastest one is a subpicosecond decay, attributed to the relaxation of the damped librational and torsional vibrations of the molecules. The intermediate decay time, ranging from 4 ps at 323 K to 30 ps at 250 K, is interpreted as due to rotations of the trans molecules about the shortest inertia axis which bring the molecule from one cube diagonal to another. The slowest decay time ranges from 28 ps at 323 K to 190 ps at 250 K and agrees very well with previous measurements with different experimental techniques. This decay is interpreted as due mostly to rotational motions of the gauche molecules jumping from one equilibrium position to another in the unit cell. The activation energy for the two processes is 3.7 and 4.3 kcal/mol, res.
Essentializing Language and the Prospects for Ameliorative Projects*

Some language encourages essentialist thinking. While philosophers have largely focused on generics and essentialism, I argue that nouns as a category are poised to refer to kinds and to promote representational essentializing. Our psychological propensity to essentialize when nouns are used reveals a limitation for antiessentialist ameliorative projects. Even ameliorated nouns can continue to underpin essentialist thinking. I conclude by arguing that representational essentialism does not doom antiessentialist ameliorative projects. Rather, it reveals that would-be ameliorators ought to attend to the propensities for our representational devices to essentialize and to the complex relationship between essentialism and prejudice.
Alien and invasive terrestrial vertebrate species on Corfu, Ionian Islands, Greece

Abstract. The Ionian Island of Corfu is rich in both species and habitats, but is also under pressure from heavy tourism, substantial water abstraction, and increased development, all of which have caused both loss and fragmentation of habitats. In addition, invasive alien species (IAS) constitute a global problem and may cause substantial problems for indigenous wildlife, especially on islands. To be able to successfully control IAS it is important to identify them, report their status, and raise awareness as early as possible. Here we present the status of ten alien species reported from Corfu, four of which are considered as invasive, the coypu (Myocastor coypus), the raccoon (Procyon lotor), the Siberian chipmunk (Tamias sibiricus), and the American pond slider (Trachemys scripta). Measures required as outlined by the EU Working Group on Invasive Alien Species are briefly discussed.
Capillary electrophoretic chiral resolution of vicinal diols by complexation with borate and cyclodextrin: Comparative studies on different cyclodextrin derivatives

Capillary electrophoretic enantioseparation of compounds containing vicinal diol groups have been investigated using different b-cyclodextrin (CD) deriva- tives and borate as a background electrolyte. Both native b-CD and several b-CD de- rivatives are examined. Chiral recognition is attributed to both enantioselective inclusion of the analyte into the chiral cavity of the CD and complexation with borate. The influ- ence of concentration of the chiral selector, pH, and organic modifiers on the resolution was studied. Four diols were baseline separated. Chirality 9:153-156, 1997. © 1997 Wiley-Liss, Inc.
A Simple, Language-Independent Approach to Identifying Potentially At-Risk Introductory Programming Students

For decades computing educators have been trying to identify and predict at-risk students, particularly early in the first programming course. These efforts range from the analyzing demographic data that pre-exists undergraduate entrance to using instruments such as concept inventories, to the analysis of data arising during education. Such efforts have had varying degrees of success, have not seen widespread adoption, and have left room for improvement. We analyse results from a two-year study with several hundred students in the first year of programming, comprising majors and non-majors. We find evidence supporting a hypothesis that engagement with extra credit assessment provides an effective method of differentiating students who are not at risk from those who may be. Further, this method can be used to predict risk early in the semester, as any engagement – not necessarily completion – is enough to make this differentiation. Additionally, we show that this approach is not dependent on any one programming language. In fact, the extra credit opportunities need not even involve programming. Our results may be of interest to educators, as well as researchers who may want to replicate these results in other settings.
Advanced bandages for diabetic wound healing

This Perspective discusses recently identified targets to enhance diabetic wound healing and their incorporation into wound dressings. Current treatment options for foot ulcers, a serious and prevalent complication of diabetes, remain nonspecific. In this Perspective, we present recent advances in understanding the pathophysiology of diabetic wound healing and the emergence of previously unidentified targets. We discuss wound dressings tailored to the diabetic wound environment currently under development.
Progress Networks as a Tool for Analysing Student Programming Difficulties

The behavior of students during completion of a learning task can give crucial insights into typical misconceptions as well as issues with the task design. However, analysing the detailed trace of every individual student is time-consuming and infeasible for large-scale classes. In this paper, we propose progress networks as an analytical tool to make sense of student data and demonstrate the technique in large-scale online learning environments for computer programming. These networks, which are easily interpreted by teachers, summarise the progression of a student population through a learning task in a single diagram and, importantly, highlight locations where students fail to make progress. Using data from three different programming courses (N > 4000), we provide instructive examples of how to apply progress networks, including how to zoom in on areas of interest to identify reasons for student difficulty. In addition, we propose a simple technique for comparing progress networks across different cohorts of interest, for instance to analyse learning differences between older and younger students, and to investigate learning retention across tasks on the same programming concept. Finally, we discuss options to improve instructional design based on the insights from progress networks, and show that progress networks can also apply to smaller cohorts.
Identifying Influencers in Thai Internet Forum based on Topic-oriented Gravity Model

The task of identifying influencers provides a lot of benefits for various practical applications such as recommendation systems, viral marketing, and information monitoring. This issue can traditionally be solved via a network structure with several proposed graph algorithms. However, most of them employ a global computation with much time-consuming; some consider only undirected and unweighted networks which may be inconsistent with the nature of data. Inspired by the law of gravity in Physics, we present the Topic-oriented Gravity Model (TopicGM) that investigates a directed and weighted network incorporating users' topical aspects. The key concept is that an individual is first represented as a textual content he created or read. Afterwards, TopicGM simply adopts a topic modeling, i.e., the Hierarchical Dirichlet Process (HDP), to classify topics over those contents. A topical network is then constructed where nodes represent individuals and an edge connects two individuals in the direction from the poster to the reader with a topical confidence weight. Finally, we apply the gravity formula to calculate influence scores and rank individuals. The experimental results, conducted on real-world data gathered from Pantip.com (famous Thai web forum), show that our approach outperforms many state-of-the-art baselines by accurately identifying influencers within the top of rankings.
The Detection and Recognition of Pulmonary Nodules Based on U-net and CNN

In recent years, with the rapid development of deep learning, especially convolutional neural network technology, deep learning technology has been widely used in various image classification and recognition, including the detection and recognition of pulmonary nodules. However, due to the limitation of computer capability, the input image size of convolutional neural network for deep learning is usually fixed, and the image size is usually small. However, the size of CT images used to detect pulmonary nodules is 512×512 and the sample data for training convolutional neural network is relatively small. It is usually difficult for ordinary convolution neural networks to detect directly. As a special full convolution network, U-net can be used directly for large-scale image detection by replacing the full connection layer with the convolution layer. And U-net is suitable for small sample medical image detection. Therefore, the detection of pulmonary nodules with U-net has been tried in this paper. The detection and recognition of pulmonary nodules is divided into two steps. Firstly, a U-net network is used to detect and segment suspicious pulmonary nodules. Secondly, in order to improve the accuracy of pulmonary nodules detection and recognition, a convolution neural network(CNN) is used to classify and identify the pulmonary nodules segmented by U-net detection, so as to remove the false positive pulmonary nodules. The experimental results show that the pulmonary nodules detection and recognition method combined with U-net and CNN is not only suitable for small sample and large size chest CT image detection, but also can remove a large number of false positive pulmonary nodules, effectively improve the accuracy of pulmonary detection, which is of great significance for the classification and recognition of pulmonary nodules using deep learning technology.