gebhart/patrepeval huggingface dataset:
Irrigation water saving estimation using soil moisture forecast simulation (2021)

This paper describes a soil moisture forecasting approach for estimation of irrigation water saving in a semi-arid area. The soil moisture forecasting model is based on the vertical water movements between the soil layers. It was created based on measurements of both weather conditions and soil moistures at the field under study. The simulation model predicts the soil moisture development based on weather forecasts. The idea of the model is to use it for controlling the precision irrigation system and to save the irrigation water consumption. The simulations show the potential for saving about 25% of irrigation water without compromising the health of the crop.
Recent advances in miniaturization of portable liquid chromatography with emphasis on detection (2023)

Liquid chromatography is a prominent analytical technique in separation science and chemical analysis, applied across numerous fields of research and within industrial applications. Over the past few decades, there has been a growing interest in the miniaturization of this technique, which has been particularly enabled through new miniature and portable detection technologies for in-field, at-site, and point-of-need (collectively 'out-of-lab') analyses. Accordingly, significant advances have been made in recent years in the development of miniaturized liquid chromatography with photometric, electrochemical, and mass spectrometric detection, enabling the development of field-deployable and portable instruments for various applications. Herein, recent developments in the miniaturization of detection systems for inclusion within, and/or coupling with, portable liquid chromatographic systems, are reviewed in detail together with critical comments and expected future trends in this area.
Bone Anchors or Interference Screws? (2004)

The improved biomechanics of interference screws suggests that these may be more suited to in vivo reconstruction of the anterior talofibular ligament than are bone anchors.
On the passivation of platinum promoted cobalt-based Fischer-Tropsch catalyst (2019)

Passivation of reduced cobalt-based catalysts is required prior to air exposure due to the exothermicity of the Co metal oxidation, which may lead to a significant increase of the temperature of the catalyst resulting in its degradation and in a potential fire hazard. This work shows the results of the passivation process carried out on a Pt-promoted Co-based catalyst supported on stabilized alumina at different space velocities in the range of 5–50 Ncc/min/gcat and constant O2 concentration of 1 vol.%. Increasing the O2 flow fed to the reactor, the specific amount of O2 consumed on the catalyst slightly decreases. Around 30% of Co metal particles are oxidized to CoO species in all the passivation treatments. These species are found to be much more reducible than the Co oxides species present on the calcined catalyst. Indeed, all the passivated catalysts are completely depassivated at a temperature which is significantly lower (300 °C) than that needed to fully reduce the calcined catalyst (400 °C). The temperature of the catalyst almost linearly increases with the increase of the O2 feed flow. Indeed, an abrupt increase of the catalyst temperature is observed for high O2 flows, resulting in a decrease of the Co° dispersion (i.e. increase of the average Co° crystallites size) after depassivation. This result is explained with the onset of sintering phenomena of the CoO species formed during passivation. The passivation treatment is found to be unsuitable for long-term catalyst protection, since a deep re-oxidation of the passivated catalyst is observed after two months of air exposure. The effectiveness of the catalyst passivation is eventually validated by running FT reactivity tests at industrially relevant process conditions. The activity of the calcined catalyst reduced in-situ at 400 °C is compared to that of the same catalyst reduced ex-situ at the same temperature, passivated at low O2 flow and depassivated in-situ at 300 °C. Interestingly, similar stability and reactivity, expressed both in terms of activity and selectivity, are obtained.
On-line coupling of derivatization with pre-concentration to determine trace levels of methotrexate (2012)

A new simple, sensitive and precise green analytical procedure using an automated packed-reactor derivatization technique coupled with on-line solid-phase enrichment (SPEn) has been developed and evaluated to determine trace levels of methotrexate (MTX). The method was based on injection of MTX into a flowing stream of phosphate buffer (0.04 M, pH 3.4), carried through the packed oxidant reactor of Cerium (IV) trihydroxyhydroperoxide for oxidative cleavage of the drug into highly fluorescent product, 2,4-diaminopteridine-6-carboxylic acid, followed by SPEn on a head of short ODS column (10 mm×4.6 mm i.d., 5 μm particle size). The flow rate was 0.25 mL/min and packed reactor temperature was 40 °C. The trapped product was back-flush eluted from the ODS column to the detector by column-switching with an environmentally friendly mobile phase consisting of ethanol and phosphate buffer (0.04 M, pH 3.4) in the ratio of 5:95 (v/v). The eluent was monitored at emission and excitation wavelengths of 460 and 360 nm, respectively. The calibration curve was linear over the concentration range of 1.25-50 ng/mL with a detection limit of 0.08 ng/mL. The method was successfully applied to determine MTX in pharmaceutical formulations with mean percentage recovery ranging from 99.48 to 99.60.
A scalable deep learning platform for identifying geologic features from seismic attributes (2017)

The modern requirement for analyzing and interpreting ever-larger volumes of seismic data to identify prospective hydrocarbon prospects within stringent time deadlines represents an ongoing challenge in petroleum exploration. To provide a computer-based aid in addressing this challenge, we have developed a “big data” platform to facilitate the work of geophysicists in interpreting and analyzing large volumes of seismic data with scalable performance. We have constructed this platform on a modern distributed-memory infrastructure, providing a customized seismic analytics software development toolkit, and a Web-based graphical workflow interface along with a remote 3D visualization capability. These support the management of seismic data volumes, attributes processing, seismic analytics model development, workflow execution, and 3D volume visualization on a scalable, distributed computing platform. Early experiences show that computationally demanding deep learning methods such as convolutional neural networks (CNN) provide improved results over traditional methods such as support vector machines (SVMs) and logistic regression for identifying geologic faults in 3D seismic volumes. Our experiments show encouraging accuracy in identifying faults by combining CNN and traditional machine learning models with a variety of seismic attributes, and the platform is able to deliver scalable performance.
Precision Modeling and Bit-width Optimization of Floating-Point Applications (2003)

We present a floating-point precision modeling methodology that can be used to develop application adaptive arithmetic precision models for variable bit-width floating-point computing. We also developed optimization algorithms that minimize the total bit-width for the application such that the output accuracy meets user-defined requirements. The methodology supports different bit-widths for different variables in the datapath.
iSCAN: An RT-LAMP-coupled CRISPR-Cas12 module for rapid, sensitive detection of SARS-CoV-2 (2020)

The COVID-19 pandemic caused by SARS-CoV-2 affects all aspects of human life. Detection platforms that are efficient, rapid, accurate, specific, sensitive, and user friendly are urgently needed to manage and control the spread of SARS-CoV-2. RT-qPCR based methods are the gold standard for SARS-CoV-2 detection. However, these methods require trained personnel, sophisticated infrastructure, and a long turnaround time, thereby limiting their usefulness. Reverse transcription-loop-mediated isothermal amplification (RT-LAMP), a one-step nucleic acid amplification method conducted at a single temperature, has been used for colorimetric virus detection. CRISPR-Cas12 and CRISPR-Cas13 systems, which possess collateral activity against ssDNA and RNA, respectively, have also been harnessed for virus detection. Here, we built an efficient, rapid, specific, sensitive, user-friendly SARS-CoV-2 detection module that combines the robust virus amplification of RT-LAMP with the specific detection ability of SARS-CoV-2 by CRISPR-Cas12. Furthermore, we combined the RT-LAMP-CRISPR-Cas12 module with lateral flow cells to enable highly efficient point-of-care SARS-CoV-2 detection. Our iSCAN SARS-CoV-2 detection module, which exhibits the critical features of a robust molecular diagnostic device, should facilitate the effective management and control of COVID-19.
What Makes a Scientific Paper be Accepted for Publication? (2021)

Despite peer-reviewing being an essential component of academia since the 1600s, it has repeatedly received criticisms for lack of transparency and consistency. We posit that recent work in machine learning and explainable AI provide tools that enable insights into the decisions from a given peer-review process. We start by simulating the peer-review process using an ML classifier and extracting global explanations in the form of linguistic features that affect the acceptance of a scientific paper for publication on an open peerreview dataset. Second, since such global explanations do not justify causal interpretations, we propose a methodology for detecting confounding effects in natural language and generating explanations, disentangled from textual confounders, in the form of lexicons. Our proposed linguistic explanation methodology indicates the following on a case dataset of ICLR submissions: a) the organising committee follows, for the most part, the recommendations of reviewers, and b) the paper's main characteristics that led to reviewers recommending acceptance for publication are originality, clarity and substance.
A two-base change in a POU factor-binding site switches pituitary-specific to lymphoid-specific gene expression. (1990)

The structurally related POU homeo domain proteins Pit-1 and Oct-2 activate pituitary- and lymphoid-specific transcription, respectively, by binding to similar AT-rich motifs in their target genes. In this study we identify bases critical for recognition and activation by Pit-1 and examine how small differences in Pit-1 and Oct-2-binding sites can impart differential transcriptional responses in pituitary and B-lymphoid cells. Scanning mutagenesis of Pit-1 response elements in both the rat prolactin and growth hormone genes reveals a critical binding motif recognized in an identical manner by the native Pit-1 protein and cloned Pit-1 gene product. This motif, ATTATTCCAT, differs by only two bases from the octamer element, ATTTGCAT, required for Oct-2-dependent activation of immunoglobulin genes. Cross recognition of Pit-1 and Oct-2 sites by both factors can be demonstrated in competitive binding assays, in which an oligometric Pit-1 site from the prolactin gene is converted to an Oct-2 site by a double point mutation. In contrast to the binding data, no cross activation of transcription is detectable in cultured cell lines. When inserted immediately 5' to a prolactin TATA box, the wild-type prolactin element enhances transcription strongly in pituitary cells but is inactive in B cells, whereas the octamer variant of the prolactin site activates expression in B cells but is silent in pituitary lines. Both elements are nonfunctional in heterologous cell lines that lack Pit-1 and Oct-2.(ABSTRACT TRUNCATED AT 250 WORDS)
Characterization of Kisspeptin Neurons in the Human Rostral Hypothalamus (2020)

The identification and positive estrogenic regulation of KP neurons in the human rostral hypothalamus challenge the long-held view that positive estrogen feedback may be restricted to the mediobasal part of the hypothalamus in primates and point to the need of further anatomical, molecular and functional studies of rostral hypothalamic KP neurons.
Abstract: Lifting and Supporting Method of Lower Eyelid Edge by a Bridge-like Thread Spacer (2018)

INTRODUCTION: Because of certain diseases of the periorbital region, there are possible the manifestations of retraction of the lower eyelid edge, its distancing from the eyeball, hypotension, lagophthalmus and ectropion. In these cases, such operations as canthopexy and canthoplasty, transplantation of cartilage or tendons, and also the eyelid edge lifting by plastic spacers, are usually applied. Operations on the lateral canthus and with transplanted tendons are not always predictable, existing plastic and cartilaginous constructions are cumbersome, often contoured and do not give desired aesthetic results. And in respect of this, we were tasked to develop a more delicate and effective intervention method that could be. MATERIALS and METHODS: In 2015, we developed and created a device (spacer) made of prolene thread 2/0, of the bridge-like form, and which is strengthened by several nodular sutures to the costal cartilage of the edge of the upper eyelid and the periosteum of the arcus marginalis, below. Spacer is elastic, light and do a delicate, stable lifting of the edge of the lower eyelid on all along. Production of such spacers is usually done on manufacturing sites, but also it can be manufactured in a clinic space. RESULTS: The application of the proposed method is quite effective: the edge of the lower eyelid strengthens, rises cranially to the required level, its sagging and scleral lumen is eliminated. CONCLUSION: The 2-year experience of using of the bridge-like thread spacers in 22 patients showed that this technique is quite effective to obtain desired aesthetic and therapeutic results. In some cases, it can quite effectively replace the classical methods.
Perspective: Black Resilience - Broadening the Narrative and the Science on Cardiovascular Health and Disease Disparities (2020)

The health of African Americans has been largely described in terms of deficits, disease and death. Little attention has been historically given to the fact that African Americans as a population show the sustained ability to survive an evolving array of social, economic and environmental adversities that date back to more than a century before the founding of the United States. While these inequities have indeed taken (and continue to take) a devastating toll, there is also wide heterogeneity in outcomes, suggesting the existence of substantial individual and collective resilience among African Americans. This Perspective aims to stimulate discussion and research that explores resilience in a population in which "overcoming" and "bouncing back" from adversities (ranging from minor incidents to legally ordained, chronic and horrific oppression) has been a requirement for survival. Rigorous scientific exploration of Black resilience may yield important insights into the phenomenon of human resilience that transcend race.
Directionality Derived From Differential Sensitivity to Monaural and Binaural Cues in the Cat's Medial Geniculate Body (2000)

Azimuth tuning of high-frequency neurons in the primary auditory cortex (AI) is known to depend on binaural disparity and monaural spectral (pinna) cues present in broadband noise bursts. Single-unit response patterns differ according to binaural interactions, strength of monaural excitatory input from each ear, and azimuth sensitivity to monaural stimulation. The latter characteristic has been used as a gauge of neural sensitivity to monaural spectral directional cues. Azimuth sensitivity may depend predominantly on binaural disparity cues, exclusively on monaural spectral cues, or on both. The primary goal of this study was to determine whether each cortical response pattern corresponds to a similar pattern in the medial geniculate body (MGB) or whether some patterns are unique to the cortex. Single-unit responses were recorded from the ventral nucleus (Vn) and lateral part of the posterior group of thalamic nuclei (Po), tonotopic subdivisions of the MGB. Responses to free-field presentation of noise bursts that varied in azimuth and sound pressure level were obtained using methods identical to those used previously in field AI. Many units were azimuth sensitive, i.e., they responded well at some azimuths, and poorly, if at all, at others. These were studied further by obtaining responses to monaural noise stimulation, approximated by reversible plugging of one ear. Monaural directional (MD) cells were sensitive to the azimuth of monaural noise stimulation, whereas binaural directional (BD) cells were either insensitive to its azimuth or monaurally unresponsive. Thus BD and MD cells show differential sensitivity to monaural spectral cues. Monaural azimuth sensitivity could not be used to interpret the spectral sensitivity of predominantly binaural cells that exhibited strong binaural facilitation because they were either unresponsive or poorly responsive to monaural stimulation. The available evidence suggests that some such cells are sensitive to spectral cues. The results do not indicate the presence of any response types in AI that are not present in the MGB. Vn and Po contain similar classes of MD and BD cells. Because Po neurons project to the anterior auditory field, neurons in this cortical area also are likely to exhibit differential sensitivity to binaural disparity and monaural spectral cues. Comparison of these MGB data with a published report of cochlear nucleus (CN) single-unit azimuth tuning shows that MGB sensitivity to spectral cues is considerably stronger than CN sensitivity.
DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting\n Agents (2017)

We introduce a Deep Stochastic IOC RNN Encoderdecoder framework, DESIRE, for\nthe task of future predictions of multiple interacting agents in dynamic\nscenes. DESIRE effectively predicts future locations of objects in multiple\nscenes by 1) accounting for the multi-modal nature of the future prediction\n(i.e., given the same context, future may vary), 2) foreseeing the potential\nfuture outcomes and make a strategic prediction based on that, and 3) reasoning\nnot only from the past motion history, but also from the scene context as well\nas the interactions among the agents. DESIRE achieves these in a single\nend-to-end trainable neural network model, while being computationally\nefficient. The model first obtains a diverse set of hypothetical future\nprediction samples employing a conditional variational autoencoder, which are\nranked and refined by the following RNN scoring-regression module. Samples are\nscored by accounting for accumulated future rewards, which enables better\nlong-term strategic decisions similar to IOC frameworks. An RNN scene context\nfusion module jointly captures past motion histories, the semantic scene\ncontext and interactions among multiple agents. A feedback mechanism iterates\nover the ranking and refinement to further boost the prediction accuracy. We\nevaluate our model on two publicly available datasets: KITTI and Stanford Drone\nDataset. Our experiments show that the proposed model significantly improves\nthe prediction accuracy compared to other baseline methods.\n
Faithfulness in internet algorithms (2004)

Proving or disproving faithfulness (a property describing robustness to rational manipulation in action as well as information revelation) is an appealing goal when reasoning about distributed systems containing rational participants.Recent work formalizes the notion of faithfulness and its foundation properties, and presents a general proof technique in the course of proving the ex post Nash faithfulness of a theoretical routing problem [11].In this paper, we use a less formal approach and take some first steps in faithfulness analysis for existing algorithms running on the Internet.To this end, we consider the expected faithfulness of BitTorrent, a popular file download system, and show how manual backtracing (similar to the the ideas behind program slicing [22]) can be used to find rational manipulation problems.Although this primitive technique has serious drawbacks, it can be useful in disproving faithfulness.Building provably faithful Internet protocols and their corresponding specifications can be quite difficult depending on the system knowledge assumptions and problem complexity.We present some of the open problems that are associated with these challenges.
Intakes of plant foods, fibre and fat and risk of breast cancer – a prospective study in the Malmö Diet and Cancer cohort (2004)

The objective of this study was to investigate prospectively the associations between intakes of plant foods, fibre and relative fat and risk of breast cancer in a subsample of 11 726 postmenopausal women in the Malmö Diet and Cancer cohort. Data were obtained by an interview-based diet history method, a structured questionnaire, anthropometrical measurements and national and regional cancer registries. During 89 602 person-years of follow-up, 342 incident cases were documented. Cox regression analysis examined breast cancer risks adjusted for potential confounders. High fibre intakes were associated with a lower risk of postmenopausal breast cancer, incidence rate ratio=0.58, 95% CI: 0.40, 0.84, for the highest quintile of fibre intake compared to the lowest quintile. The combination high fibre-low fat had the lowest risk when examining the effect in each cell of cross-classified tertiles of fibre and fat intakes. An interaction (P=0.049) was found between fibre- and fat-tertiles. There was no significant association between breast cancer risk and intakes of any of the plant food subgroups. These findings support the hypothesis that a dietary pattern characterised by high fibre and low fat intakes is associated with a lower risk of postmenopausal breast cancer.
ACTION OF SOAP ON THE SKIN (1947)

IN THE manufacture of soap, fats are chosen which contain either lauric acid or oleic and other unsaturated fatty acids in order that the final soap have satisfactory lathering, cleansing and physical properties. The fatty acid fraction of an average toilet soap usually contains from 11 to 12 per cent lauric acid and 38 to 40 per cent oleic acid and other acids of one double bond.<sup>1</sup>A satisfactory soap may be prepared which has more lauric and less oleic acid, such as coconut oil soap, or one which has less lauric and more oleic acid, such as olive oil soap. Gardiner<sup>2</sup>and Goldman<sup>3</sup>have stated that coconut oil soaps are more irritating to the skin than other soaps, and this is not an uncommon clinical observation. Soaps made from only olive oil have been thought to be relatively nonirritating to the skin. There has been little
A Uniform Approach to Analogies, Synonyms, Antonyms, and Associations (2008)

Recognizing analogies, synonyms, antonyms, and associations appear to be four distinct tasks, requiring distinct NLP algorithms. In the past, the four tasks have been treated independently, using a wide variety of algorithms. These four semantic classes, however, are a tiny sample of the full range of semantic phenomena, and we cannot afford to create ad hoc algorithms for each semantic phenomenon; we need to seek a unified approach. We propose to subsume a broad range of phenomena under analogies. To limit the scope of this paper, we restrict our attention to the subsumption of synonyms, antonyms, and associations. We introduce a supervised corpus-based machine learning algorithm for classifying analogous word pairs, and we show that it can solve multiple-choice SAT analogy questions, TOEFL synonym questions, ESL synonym-antonym questions, and similar-associated-both questions from cognitive psychology.