Miracle-dz/UniFAR-FTUs huggingface dataset:
Taxonomy and Phylogeny of the Fomitopsis pinicola Complex With Descriptions of Six New Species From East Asia

Fomitopsis pinicola is a common brown-rot fungal species found in northern hemisphere. It grows on many different gymnosperm and angiosperm trees. Recent studies show that it is a species complex; three species from North America and one species from Europe have been recognized in this complex. In the current study, six new species in the Fomitopsis pinicola complex were discovered from East Asia, based on morphological characters and phylogenetic analyses inferred from the sequence data of the internal transcribed spacer (ITS) regions, the second subunit of RNA polymerase II (RPB2), and the translation elongation factor 1-α gene (TEF). Detailed descriptions of the six new species are provided. Our results also indicates that species of the F. pinicola complex from East Asia usually have limited distribution areas and host specialization.
Achieving cost efficiency through increased inventory leanness: Evidence from manufacturing industry

Abstract Inventory management’s fundamental problem starts with maintaining equilibrium among the operating efficiency, cost of investment, and other allied costs with extensive inventories to keep the actual conflicts at the minimum while optimizing the inventory holding levels. But, inventory management practices have not been well exploited in various manufacturing industries yet. In this study, inventory management tools, i.e., ABC and VED analysis, have been applied in the manufacturing industry, considering 146 items as raw material for an assembly. A total of 15 items under ‘AV’ class have been identified that consume 82.05 % of the total cost, and these items need strict control and frequent ordering. Sigma level of suppliers is also calculated, which comes out to be 2.36, and it must be improved to reduce the overall inventory cost.
Identification of PCBP1 as a Novel Modulator of Mammalian Circadian Clock

The circadian clock governs our daily cycle of behavior and physiology. Previous studies have identified a handful of core clock components and hundreds of circadian modifiers. Here, we report the discovery that poly(C)-binding protein 1 (PCBP1), displaying a circadian expression pattern, was a novel circadian clock regulator. We found that knocking down PCBP1 resulted in period shortening in human U2OS cells, and that manipulations of PCBP1 expression altered the activity of CLOCK/BMAL1 in an E-box-based reporter assay. Further mechanistic study demonstrated that this clock function of PCBP1 appears to work by enhancing the association of Cryptochrome 1 (CRY1) with the CLOCK/BMAL1 complex, thereby negatively regulating the latter’s activation. Co-immunoprecipitation of PCBP1 and core clock molecules confirmed the interactions between PCBP1 and CRY1, and a time-course qPCR assay revealed the rhythmic expression of PCBP1 in mouse hearts in vivo. Given that the RNA interference of mushroom-body expressed (mub), the poly(rC) binding protein (PCBP) homolog of Drosophila, in the clock neurons also led to a circadian phenotype in the locomotor assay, our study deemed PCBP1 a novel clock modifier whose circadian regulatory mechanism is conserved during evolution.
Metaproteomics Reveals Similar Vertical Distribution of Microbial Transport Proteins in Particulate Organic Matter Throughout the Water Column in the Northwest Pacific Ocean

Solubilized particulate organic matter (POM) rather than dissolved organic matter (DOM) has been speculated to be the major carbon and energy sources for heterotrophic prokaryotes in the ocean. However, the direct evidence is still lack. Here we characterized microbial transport proteins of POM collected from both euphotic (75 m, deep chlorophyll maximum DCM, and 100 m) and upper-twilight (200 m and 500 m) zones in three contrasting environments in the northwest Pacific Ocean using a metaproteomic approach. The proportion of transport proteins was relatively high at the bottom of the euphotic zone (200 m), indicating that this layer was the most active area of microbe-driven POM remineralization in the water column. In the upper-twilight zone, the predicted substrates of the identified transporters indicated that amino acids, carbohydrates, taurine, inorganic nutrients, urea, biopolymers, and cobalamin were essential substrates for the microbial community. SAR11, Rhodobacterales, Alteromonadales, and Enterobacteriales were the key contributors with the highest expression of transporters. Interestingly, both the taxonomy and function of the microbial communities varied among water layers and sites with different environments; however, the distribution of transporter types and their relevant organic substrates were similar among samples, suggesting that microbial communities took up similar compounds and were functionally redundant in organic matter utilization throughout the water column. The similar vertical distribution of transport proteins from the euphotic zone to the upper twilight zone among the contrasting environments indicated that solubilized POM rather than DOM was the preferable carbon and energy sources for the microbial communities.
Scale-up of Circulating Fluidized Bed Combustion

Tests on large circulating fluidized bed boilers are extremely expensive and computer modeling is not yet reliable. The paper tries to answer the question: Can tests on laboratory-scale equipment be scaled to satisfy the need for information? Criteria for combustion scaling are defined in the form of two Damkohler numbers: one for processes in the vertical direction and one for the horizontal direction. Examples are given to show the outcome of combustion modeling. It is concluded that it is possible to reasonably well model the combustion process in the vertical direction by providing sufficient residence time in the riser, but in a laboratory device it is not possible to model the horizontal combustion processes, except in special cases.
Effects of Boron Fertilizer on Tomato, Pepper, and Cucumber Yields and Chemical Composition

In many parts of the world, boron (B) levels are insufficient for potential production. Boron deficiency is also widespread in the Anatolia region of Turkey. Boron deficiency could impact production and quality of tomatoes (Lycopersicon esculentum L.), pepper (Capsicum annum L.), and cucumber (Cucumis sativus L.). A two-year greenhouse experiment was conducted to study yield and quality response of three vegetables to B addition (0, 1, 2, 3, and 4 kg B ha−1). The optimum economic B rates (OEBR) were 2.3, 2.6, 2.4 kg B ha−1, resulting in soil B concentrations of 0.33, 0.34 and 0.42 mg kg−1. Independent of plant species, B application decreased tissue nitrogen (N), calcium (Ca), and magnesium (Mg) but increased tissue phosphorus (P), potassium (K), iron (Fe), manganese (Mn), zinc (Zn), and copper (Cu) concentrations. We conclude that a B addition of 2.5 kg ha−1 is sufficient to elevate soil B levels to nondeficient levels. Similar studies with different soils and initial soil-test B levels are needed to conclude if these critical soil test values and OEBR can be applied across the region.
Analysis of polybrominated diphenyl ethers in textiles treated by brominated flame retardants

Brominated flame retardants (BFRs) have been widely used as additives or as chemical reactants in polymers and textiles. The aim of this study was to develop methods for the analysis of synthesized polybrominated diphenyl ethers (PBDEs) in textiles. Analytical methods for the determination of PBDEs in textile samples were performed, including gas chromatography/mass spectrometry (GC/MS), thermal desorption (TD)-GC/MS, and high-resolution gas chromatography/high-resolution mass spectrometry (HRGC/HRMS). The experiments consisted of three different sub-experiments that centered on detecting the presence of deca-BDE in textiles by (1) GC/MS, (2) TD-GC/MS, and by (3) target molecule analysis of 27 PBDE congeners by HRGC/HRMS. Results indicated that deca-BDE detection by TD-GCMS was the most precise methodology and did not require extraction or cleanup procedures. The analyses of the 27 PBDE congeners were used for the HRGC-isotope dilution HRMS by EPA method 1614. TD-GC/MS with pyrolysis was the most effective method for monitoring of deca-BDE in textiles because of its simplicity. HRGC/HRMS analysis was the most appropriate method for determination of low concentrations of deca-BDE in textiles compared with the other analytical methods. GC/MS analysis may also be used but high-concentration samples are needed for detection. BDE-28, -66, -100, -119, -153, -197, -206, and -209 were detected in all textile samples by the HRGC/HRMS method, of which the concentration of BDE-209 was the highest. BDE-3, -7, -47, -49, -71, -99, -126, and -156 were not detected in any textile samples.
Named Entity Recognition from Synthesis Procedural Text in Materials Science Domain with Attention-Based Approach

We applied attention-based deep learning to the task of Named Entity Recognition (NER) from synthesis procedural text of scientiﬁc literature in materials science domain. Unlike conventional machine learning approaches that need hand-crafted features or training with massive data, our attention-based deep learning method enhances contextualized word representations by using a Bidirectional Encoder Representations from Transformers (BERT) pre-trained language model and then associating with Bidirectional Long Short-term Memory (BiLSTM) and Conditional Random Fields (CRF) layer; this is then BERT-BiLSTM-CRF. Our method shows it is feasible to use a limited annotated corpus with a pre-trained language model to extract entities from synthesis procedures in materials science. The experimental result shows that our approach outperforms other baseline models with signiﬁcant improvements based on three corpora.
Photoemission from transition metals and their compounds

Photoemission experiments on 3d transition metals are reviewed. The emphasis is on understanding the results of experiments, not on experimental details and methods. Extensive use is made of simple models. Much of the review pertains to resonances associated with the autoionization 3p53dn+1 →3p63dn−1 +e and their implications for electronic structure. Nonresonant ultraviolet and x‐ray photoemission spectroscopies are also discussed. Photoemission and photoabsorption of transition‐metal atoms are discussed first. Results for Mn are described at length to establish the validity of the autoionization mechanism. The results from atomic spectroscopy are used to interpret experiments on solids. The role of atomiclike excitations in solids is examined. Compounds of transition metals are analyzed in terms of ligand‐field theory, which is shown to be inadequate. Newer theories involving configuration interaction are shown to agree better with experiment. Various mechanisms for the excitation of photoemission satel.
Sequential separation and trace enrichment of thorium(IV) and uranium(VI) on chelating resin Amberlite XAD-2-ortho-vanillinthiosemicarbazone (o-VTSC)

ABSTRACT Polystyrenc-divinylbenzene-based Amberlite XAD-2 was funetionalized with ortho-vanillinthiosemicarbazone and its analytical properties were investigated. The resin was used successfully for the separation and preconcentration of thorium(IV) and uranium(VI) ions prior to their determination by spectrophotometry and by ICAP-AES and GF-AAS, respectively. The influence of several ions as interferents is discussed. The resin exhibits good chemical stability, reuseability, and a faster rate of equilibration for their determination. The proposed method has been applied to sequential chromatographic separation of thorium(IV) and uranium(VI) on river water samples with good analytical reliability such as recovery of 97–98%, relative standard deviation of 2–3%, and a detection limit of 100 ng-mL-1. The present method is also used for their determination in monazite sand and some standard geological materials.
BERTKG-DDI: Towards Incorporating Entity-specific Knowledge Graph Information in Predicting Drug-Drug Interactions

Off-the-shelf biomedical embeddings obtained from the recently released various pre-trained language models (such as BERT, XLNET) have demonstrated state-of-the-art results (in terms of accuracy) for the various natural language understanding tasks (NLU) in the biomedical domain. Relation Classification (RC) falls into one of the most critical tasks. In this paper, we explore how to incorporate domain knowledge of the biomedical entities (such as drug, disease, genes), obtained from Knowledge Graph (KG) Embeddings, for predicting Drug-Drug Interaction from textual corpus. We propose a new method, BERTKG-DDI, to combine drug embeddings obtained from its interaction with other biomedical entities along with domain-specific BioBERT embedding-based RC architecture. Experiments conducted on the DDIExtraction 2013 corpus clearly indicate that this strategy improves other baselines architectures by 4.1% macro F1-score.
The CARE Theory of Dignity Amid Personal Data Digitalization

With the rapidly evolving permeation of digital technologies into everyday human life, we are witnessing an era of personal data digitalization. Personal data digitalization refers to the sociotechnical encounters associated with the digitization of personal data for use in digital technologies. Personal data digitalization is being applied to central attributes of human life—health, cognition, and emotion—with the purported aim of helping individuals live longer, healthier lives endowed with the requisite cognition and emotion for responding to life situations and other people in a manner that enables human flourishing. A concern taking hold in manifold fields ranging from IT, bioethics, and law, to philosophy and religion is that as personal data digitalization permeates ever more areas of human existence, humans risk becoming artifacts of technology production. This concern brings to center stage the very notion of what it means to be human, a notion encapsulated in the term human dignity, which broadly refers to the recognition that human beings possess intrinsic value and, as such, are endowed with certain rights and should be treated with respect. In this paper, we identify, describe, and transform what we know about personal data digitalization into a higher order theoretical structure around the concept of human dignity. The result of our analysis is the CARE (claims, affronts, response, equilibrium) theory of dignity amid personal data digitalization, a theory that explains the relationship of personal data digitalization to human dignity. Building upon the CARE theory as a foundation, researchers in a variety of IS research streams could develop mid-range theories for empirical testing or could use the CARE theory as an overarching lens for interpreting emerging IS phenomena. Practitioners and government agencies can also use the CARE theory to understand the opportunities and risks of personal data digitalization and to develop policies and systems that respect the dignity of employees and citizens.
Precise Minimax Regret for Logistic Regression with Categorical Feature Values

We study logistic regression with binary labels and categorical (discrete) feature values. Our goal is to evaluate precisely the (maximal) minimax regret. We express it as the so called Shtarkov sum known in information theory. To the best of our knowledge such a sum was never computed in the context of logistic regression. To be more precise, the pointwise regret of an online algorithm is deﬁned as the (excess) loss it incurs over some value of a constant comparator (weight vector) that is used for prediction. It depends on the feature values, label sequence, and the learning algorithm. In the maximal minimax scenario we seek the best weights for the worst label sequence over all possible learning algorithms/ distributions, therefore it constitutes a lower bound for the pointwise regret. For ﬁnite dimension d and N distinct feature vectors we show that the maximal minimax regret grows as
Recognizing Figure Labels in Patents

Scientiﬁc documents often contain signiﬁcant information in ﬁgures. The United States Patent and Trademark Ofﬁce (USPTO) awards thousands of patents each week, with each patent containing on the order of a dozen ﬁgures. The information conveyed by these ﬁgures typically include a drawing or diagram, a label, caption and reference text within the document. Yet associating the short bits of text to the ﬁgure is challenging when labels are embedded within the ﬁgure, as they typically are in patents. Using patents as a testbench, this paper highlights an open challenge in analyzing all of the information presented in scientiﬁc/technical documents - namely, there is a technological gap in recognizing characters embedded in drawings, which leads to difﬁculties in processing the text associated with scientiﬁc ﬁgures. We demonstrate that automatically reading the ﬁgure label in patent diagram ﬁgures is an open challenge, as we evaluate several state-of-the-art optical character recognition (OCR) methods on recent patents. Because the visual characteristics of drawings/diagrams are quite similar to that of text (high contrast, width of strokes, etc), separating the diagram from the text is challenging and leads to both (a) false detection of characters from pixels that are not text and (b) missed text that is critical for identifying the ﬁgure number. We develop a method for automatically reading the patent ﬁgure labels by ﬁrst identifying the bounding box containing the label using a novel non-convex hull approach, and then demonstrate the success of OCR when the text is isolated from the diagram.
Design, Physicochemical Characterization and Pharmacokinetic Evaluation of Bilayered Buccal Tablets containing Statin Derivative

The objective of this study was to develop an effective Fluvastatin buccal adhesive tablet with excellent bioadhesive force and good drug stability in human saliva. The study also focuses on the mucoadhesive potential of some natural gums like tamrind gum, xanthan gum and gellan gum. Bilayered Buccoadhesive compacts with one layer of drug and mucoadhesive polymer and second non medicated, non permeable layer of ethylcellulose and Mg stearate was prepared using direct compression technique. Physicochemical properties of tablets like bioadhesive strength, swelling rate, surface pH, permeation rate and in vitro drug release rate were studied. As bioadhesive additives for tablets, a mixture of polymers like some natural gums along with chitosan was selected. Release studies revealed that the sustained release of Fluvastatin over several hours may be obtained by combining the chitosan with natural gums. Also the bioavailability studies indicated that bioavailability of Fluvastatin was enhanced using the above mentioned drug delivery system. Thus the potential of above mentioned drug delivery device is promising and may be considered as a novel tool in order to improve the therapeutic efficacy of various drugs with shorter half life and poor bioavailability.
Toward A Robust Method for Understanding the Replicability of Research

The replicability of research is crucial for building trust in the peer review process and transitioning knowledge to real-world applications. While manual peer review excels in some regards, the variability of reviewer expertise, publication requirements, and research domains brings about uncertainty in the process. Replicability, in particular, is not necessarily a priority; this is evidenced by repeated failures in replication attempts such as the Psychology Reproducibility Project, where 61 of 100 replications fail. Improving human comprehension of decisive factors is crucial for integrating automated systems for replicability prediction into the review process. We develop a robust, automated method for semantic parsing, information extraction, and replication prediction that operates directly on PDFs. We introduce features that have not been explored in prior work, construct argument structures to guide understanding, and provide preliminary results for replication prediction.
Influence of Structural Details in Modeling Electrostatically Driven Protein Adsorption

Mechanistic modeling of protein adsorption has evolved to include increasingly detailed descriptions of protein structure in an effort to capture experimentally observed behavior. This has been especially true of electrostatically driven adsorption, for which colloidal models have been used frequently. These efforts have focused on adsorption of proteins to oppositely charged surfaces and often capture the experimental trends even with gross simplification of protein structure. As a more stringent test of model sensitivity to structural details, we have modeled the patch-controlled adsorption of basic proteins on anion-exchange surfaces, where a small number of negative charges on the protein surface lead to a net attraction between the net positively charged protein and the positively charged surface. We account in detail for the protein shape and charge distribution and examine the role of the assumed surface description. A model assuming a uniformly charged surface is unable to predict electrostaticall.
A Semiempirical Approach for Estimating the Water Content of Natural Gases

A semiempirical approach for estimating the equilibrium water content of natural gases in the liquid water−vapor and ice−vapor regions has been developed. This method estimates the water content of natural gases using water/ice vapor pressure and water/ice molar volume as well as pressure and temperature of the system. The approach has been developed using the experimental water content data for methane at a temperature range of 273.15 and 377.59 K and pressures up to 13.81 MPa. Experimental data for the water content of a hydrocarbon gas mixture (94% methane + 4% ethane + 2% n-butane) have been generated at a temperature range of 288.15 to 313.14 K and pressures up to 17.56 MPa using a static-analytic apparatus, taking advantage of a pneumatic capillary sampler for fluid sampling. These independent data have been used in examining the reliability of the semiempirical approach. The predictions of this approach are in good agreement with the experimental data generated in this work and those reported in th.
Customized Cost-Effective Polymethyl-Methacrylate Cranioplasty Implant Using Three-Dimensional Printer

There is no doubt that many synthetic materials used in cranioplasty have given good result regarding patient's calvarial shape. However, the use of these materials is costly to the patient and requires complex intraoperative process. There has been a long history regarding the use of acrylic bone cement called as polymethyl-methacrylate (PMMA) as an implant due to its desirable properties. Here, we present three cases of simple, cost effective manually sculpted calvarial defect using three-dimensional (3D) printer. Sharing the achievement and challenges, we want to focus that the 3D customized implant of PMMA can be used as bone substitute.