Miracle-dz/UniFAR-FTUs huggingface dataset:
Decreased aspartate aminotransferase ("SGOT") activity in serum of uremic patients.

Aspartate aminotransferase activity in the serum of uremic patients and of normal individuals was analyzed by three different methods: ( a ) a manual ultraviolet method, ( b ) a manual colorimetric method, and ( c ) by continuous flow (SMA 12/60 AutoAnalyzer; Technicon). Both dialyzed and undialyzed uremic patients exhibit low values for serum aspartate aminotransferase activity, regardless of the method used. The SMA 12/60 procedure exaggerates this decrease because of ultraviolet-absorbing materials in uremic serum. The activity of this enzyme did not exceed normal values in one uremic patient after a myocardial infarction and recurrent severe cardiac episodes. Such results suggest that this procedure should be used with great care as an index for diagnosing myocardial infarctions (and perhaps hepatitis) in uremic patients.
Optimized Built-In Self-Repair for Multiple Memories

A new built-in self-repair (BISR) scheme is proposed for multiple embedded memories to find optimum point of the performance of BISR for multiple embedded memories. All memories are concurrently tested by the small dedicated built-in self-test to figure out the faulty memories, the number of faults, and irreparability. After all memories are tested, only faulty memories are serially tested and repaired by the shared built-in redundancy analysis according to the sizes of memories in descending order. Thus, the fast test and repair are performed with low area overhead. To accomplish an optimal repair rate and a fast analysis speed, an exhaustive search for all combinations of spare rows and columns is proposed based on the optimized fault collection. Experimental results show that the proposed BISR has the optimal repair rate because of the exhaustive search. The performance of the proposed BISR is located in the optimum point between the test and repair time, and the area overhead. For example, the proposed BISR requires 49.6% of the area and 1.3 times of the test and repair time in comparison with parallel BISR scheme for four memories (one 128 K, two 256 K, and one 512 K memories). Furthermore, the more there are memories, the more superior performance in terms of the test and repair time, and the area overhead is shown.
Extension of Semantic Lexicon Using Word Embeddings and Synonyms

In this paper, we propose a novel method to extend semantic lexicon by using word embeddings and synonyms. We compare the embedding values between the new word and the known words. We also compare the embedding values of synonyms between the new word and the known words. The system performance of semantic category assignment for words not appearing in the Sejong electronic dictionary is 32.19%, and the system performance of extended semantic category assignment is 51.14%. We proved that it is helpful to extend the semantic category of words in the Sejong electronic dictionary by assigning semantic categories to the new words for which semantic categories have not been assigned.
Optimal Power Generation and Load Management for Off-Grid Hybrid Power Systems with Renewable Sources via Mixed-Integer Programming

This paper addresses the optimal power generation and load management problems in off-grid hybrid electric systems with renewable sources based on appropriately constructed optimization problems. In this venue, the capacity and operating constraints for generating, storage and load units are first formulated as mixed-integer linear programming (MILP) models. In addition, we integrate the power curtailment strategies, such as temporary pause and multiple power supplies, for the load units in the MILP models to alleviate the peak power demands and power shortage without an adverse effect on the overall operation of the system. We subsequently consider the application of this framework for representative scenarios in the context of a residential power system with solar sources. Simulation results for the case of predetermined schedules with preset power requests, as well as for the case of varying schedules with updated power requests, are presented using the Preprint submitted to Energy Conversion and Management April 2, 2013 proposed optimization-based approach.
Molecular Genetic Analyses of Mating Pheromones Reveal Intervariety Mating or Hybridization in Cryptococcus neoformans

ABSTRACT The sexual mating of the pathogenic yeast Cryptococcus neoformans is important for pathogenesis studies because the fungal virulence is linked to the α mating type (MATα). We characterized C. neoformans mating pheromones (MFα 1 and MFa1) from 122 strains to understand intervariety hybridization or mating and intervariety virulence. MFα 1 in three C. neoformans varieties showed (a) specific nucleotide polymorphisms, (b) different copy numbers and chromosomal localizations, and (c) unique deduced amino acids in two geographic populations of C. neoformans var. gattii. MFα 1 of different varieties cross-hybridized in Southern hybridizations. Their phylogenetic analyses showed purifying selection (neutral evolution). These observations suggested that MATα strains from any of the three C. neoformans varieties could mate or hybridize in nature with MATa strains of C. neoformans var. neoformans. A few serotype A/D diploid strains provided evidence for mating or hybridization, while a majority of A/D strains tested positive for haploid MFα 1 identical to that of C. neoformans var. grubii. MFα 1 sequence and copy numbers in diploids were identical to those of C. neoformans var. grubii, while their MFa1 sequences were identical to those of C. neoformans var. neoformans; thus, these strains were hybrids. The mice survival curves and histological lesions revealed A/D diploids to be highly pathogenic, with pathogenicity levels similar to that of the C. neoformans var. grubii type strain and unlike the low pathogenicity levels of C. neoformans var. neoformans strains. In contrast to MFα 1 in three varieties, MFa1 amplicons and hybridization signals could be obtained only from two C. neoformans var. neoformans reference strains and eight A/D diploids. This suggested that a yet undiscovered MFa pheromone(s) in C. neoformans var. gattii and C. neoformans var. grubii is unrelated to, highly divergent from, or rarer than that in C. neoformans var. neoformans. These observations could form the basis for future studies on the role of intervariety mating in C. neoformans biology and virulence.
Parotid Secretory Protein Binds Phosphatidylinositol (3,4) Bisphosphate

Molecular interactions that direct trafficking of secreted proteins are not well-described in salivary glands. Here, we report that the soluble cargo protein Parotid Secretory Protein (PSP) is bound to the membranes of secretory granules isolated from rat parotids. This is apparently due to specific interaction with phosphatidylinositol phosphates (PtdInsP). PSP binds PtdIns(3,4)P2, 10-fold greater than PtdIns(3,5)P2 or PtdIns(4)P, and does not bind PtdIns(3)P or PtdIns(5)P. Human PSP synthesized in vitro also binds PtdIns(3,4)P2. Bacterially expressed rat PSP binds PtdIns(3,4)P2 with a Kd of 2.4 x 10-11 M. Other major secretory proteins (amylase, proline-rich protein) are not bound to isolated granule membranes and do not bind phosphatidylinositol phosphates. Immunofluorescence shows PtdIns(3,4)P2 at the secretory granules, and fluorescent PtdIns(3,4)P2 can flip from the outer leaflet to the inner leaflet of the membrane. Binding of PSP to PtdInsPs may contribute to sorting during the formation of the secretory granules, or sorting by retention during maturation of the granules.
Mitigation of liquefaction beneath existing facilities using denitrification

Microbially mediated dissimilatory reduction of nitrate, or denitrification, offers the promise for non-disruptive mitigation of the potential for earthquake-induced liquefaction beneath existing facilities. Denitrification can mitigate liquefaction in two ways: by desaturation of the soil through generation of gas and by cementation of the soil through precipitation of calcium carbonate as calcite. Laboratory column tests demonstrate that desaturation via biogenic gas occurs almost immediately upon stimulation of the denitrifying microbes, providing short term mitigation while calcite is being precipitated. Once enough calcite is precipitated, denitrification provides long term mitigation. Laboratory simple shear testing demonstrates that a relatively small decrease in the degree of saturation, as little as 5%, and a relatively small amount of calcite precipitation, as little as 0.4 percent of the dry weight of the soil, can both provide substantial mitigation of liquefaction potential. When there is sufficient normal stress on the ground surface (mitiga t ing the potential for shallow crack development due to gas production), these processes are nondisruptive and thus provide a non-disruptive means of mitigating liquefaction beneath existing facilities. 1 Regents’ Professor, School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85281 (email: Edward.Kavazanjian@asu.edu) 2 Geotechnical Engineer, Geosyntec Consultants, Columbia, MD 21044 3 Regents’ Professor, School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85281 4 Research Professor, School of Sustainable Engineering and the Built Environment, Arizona State University , Tempe, AZ 85281 5 Graduate Research Associate, School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85281 6 Associate Professor, School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85281 Kavazanjian, E. , Jr., Rittmann, B.E. , Hamdan, N. , O’Donnell, S.T. , Hall, C. , and van Paassen, L. Mitigation of Liquefaction Beneath Existing Facilities Using Denitrification. Proceedings of the 11 National Conference in Earthquake Engineering, Earthquake Engineering Research Institute, Los Angeles, CA. 2018 Eleventh U.S. National Conference on Earthquake Engineering Integrating Science, Engineering & Policy June 25-29, 2018 Los Angeles, California Mitigation of Liquefaction Beneath Existing Facilities Using Denitrification Edward Kavazanjian, Jr., Sean T. O’Donnell, Bruce Rittmann, Nasser Hamdan, Caitlyn Hall, and Leon A. van Paassen
Compassion in Organizations : Cause for Concern or Distress

Compassion in organizations is researched as a three-stage interrelated process of noticing another’s pain, empathic concern or feeling another’s pain, and taking action to relieve all, or some, of their suffering. Current organizational compassion theory identifies agent capacities of emotional flexibility and agent diversity in the form of cognitive, affective and resource diversity as essential to compassionate acts in organizations. However, the sustained need to remain empathic for othersin caring organizations, such as healthcare and social services, and in socio-economic contexts where suffering is endemic, may lead to empathic distress, and a need to express self-oriented actions. These experiences have an effect on both cognitive and affective processing.This paper advances a model of empathy according to Enaction, a dynamical systems approach to embodied cognition. It aims to illustrate the unpredictable and non-linear, dynamical nature of the empathic process. It highlights the contribution of self-awareness, based on embodiment and active sensing, in enhancing the recursive, intrapersonal processing of somatic, cognitive and affective factors. This is deemed to be essential to perspective-taking, thus encouraging empathic concern rather than empathic distress.
HYPERSPECTRAL CLOSE-RANGE LWIR IMAGING SPECTROMETRY – 3 CASE STUDIES by

Long wavelength infra-red (LWIR) imaging spectrometry data acquired with the SisuROCK instrument were tested for their ability to estimate mineral abundances in rock samples. Three diverse targets were selected to test the method. The targets were the Kemi chrome mine, the Pyhäsalmi Cu-Zn-S mine and the Kedonojankulma Cu-Au ore prospect. In Kemi, the scope was to determine whether the ore types and a few host rocks were distinguishable by LWIR. In Pyhäsalmi and Kedonojankulma, the main focus of the study was on the identification of the alteration minerals amongst other minerals. A set of exploration drilling powders from Pyhäsalmi was also included in the study. Their mineral abundances and three main chemical commodities, Cu, Zn and S, were additionally estimated.
Modeling Heterogeneous Cellular Networks Interference Using Poisson Cluster Processes

Future mobile networks are converging toward heterogeneous multitier networks, where macro-, pico-, and femtocells are randomly deployed based on user demand. A popular approach for analyzing heterogeneous networks (HetNets) is to use stochastic geometry and treat the location of BSs as points distributed according to a homogeneous Poisson point process (PPP). However, a PPP model does not provide an accurate model for the interference when nodes are clustered around highly populated areas. This motivates us to find better ways to characterize the aggregate interference when transmitting nodes are clustered following a Poisson cluster process (PCP) while taking into consideration the fact that BSs belonging to different tiers may differ in terms of transmit power, node densities, and link reliabilities. To this end, we consider K-tier HetNets and investigate the outage probability, the coverage probability, and the average achievable rate for such networks. We compare the performance of HetNets when nodes are clustered and otherwise. By comparing these two types of networks, we conclude that the fundamental difference between a PPP and a PCP is that, for a PPP, the number of simultaneously covered mobiles and the network capacity linearly increase with K. However, for a PCP, the improvements in the coverage and the capacity diminish as K grows larger, where the curves saturate at some point. Based on these observations, we determine the scenarios that jointly maximize the average achievable rate and minimize the outage probability.
The Role of Emotional Intelligence in Entrepreneurial Networking

With no doubt, the route to growth and economic recovery depends on creating more businesses and having a workforce with the skills to support business start-ups. Entrepreneurship and economic recovery are two sides of the same coin. Entrepreneurship is an important mechanism permeating the knowledge filter to facilitate the spillover of knowledge thus generating economic growth (Audretsch, 2007). As professional networks are key factors to help coping with economic uncertainty, entrepreneurs must network to survive.
Learning to Generate Market Comments from Stock Prices

This paper presents a novel encoder-decoder model for automatically generating market comments from stock prices. The model first encodes both short- and long-term series of stock prices so that it can mention short- and long-term changes in stock prices. In the decoding phase, our model can also generate a numerical value by selecting an appropriate arithmetic operation such as subtraction or rounding, and applying it to the input stock prices. Empirical experiments show that our best model generates market comments at the fluency and the informativeness approaching human-generated reference texts.
Design Tips for Steel in Low or Moderate Seismicity Regions

MMOST OF THE UNITED STATES HAS LOW OR MODERATE SEISMICITY. Historically, buildings in these areas were not designed explicitly to resist earthquake forces. People living in these areas most likely have never experienced a damaging earthquake, and building designers and constructors in these regions do not have extensive experience with earthquake-resistant construction. National model building codes now include seismic design requirements that directly impact areas where seismicity is low or moderate. Many state and local jurisdictions have adopted a newer national model code, forcing structural engineers throughout the United States to understand and apply these new code requirements and, in many cases, to explain them to architects, building owners, and contractors. The seismic design provisions are not simple. The consequence of misapplying these provisions could result in buildings that lack the intended strength and ductility or that are unnecessarily costly. The core seismic design requirements in most modern United States building codes are found in Minimum Design Loads for Buildings and Other Structures (ASCE/SEI 7-05, 2005; ASCE/SEI 7-02, 2002). The latest version is ASCE/SEI 7-05, which recently replaced ASCE/SEI 7-02. The fundamental approach and requirements of the two versions are very similar; however, some important changes that are relevant to areas of low or moderate seismicity are noted throughout this paper. The seismic design forces for a building depend on several factors: the ground motion characteristics of the geographic area (seismic maps); the geology of the site (site class); the occupancy of the building (seismic use group or occupancy category); the building’s fundamental period of vibration (T); and the building’s framing system and seismic forceresisting system (R Value). ASCE/SEI 7-05 defines six seismic design categories (SDCs), A through F. SDC A and SDC B are for low seismic risk; SDC C is for moderate seismic risk; and SDCs D, E, and F are for high seismic risk. The only requirements for SDC A are a minimum lateral strength and complete load path; therefore, the tips included here apply primarily to SDC B and C buildings. Essential facilities and buildings that represent a substantial hazard to human life in the event of failure (Seismic Use Group III or Occupancy Category III) may be assigned to SDC D in regions of moderate seismicity.
ENHANCED TERMITE RESISTANCE OF SCOTS PINE ( PINUS SYLVESTRIS L . ) SOLID WOOD BY PHENOL-FORMALDEHYDE TREATMENT

In order to assess the resistance of phenol-formaldehyde (PF) modified wood to subterranean termites (Reticulitermes flavipes), laboratory no-choice tests following the standard EN 117 (2013) were performed for 8 weeks. Scots pine (Pinus sylvestris L.) sapwood specimens were modified with low molecular weight PF-resin in two concentrations. After vacuum-pressure impregnation and curing, the wood specimens were subjected to an accelerated aging test according to the standard EN 84 (1997). Five replicates per each concentration group were exposed to termites as well as unmodified wood. Following exposure, the specimens were evaluated for termite damage using a visual rating system and mass losses were also recorded. All treated samples showed higher resistance to termites than the controls. After testing period, 100 % termite mortality was found for modified wood. PF-resin treatment significantly reduced the feeding activity of termites and the mass losses caused.
SOCIO-ECONOMIC FACTORS AFFECTING ADOPTION OF HYBRID SEEDS AND SILVERY PLASTIC MULCH FOR CHILI FARMING IN CENTRAL JAVA APRI KUNTARININGSIH

Transfer teknologi pertanian tidak akan berdampak jika petani tidak mengadopsi teknologi tersebut. Dengan demikian, adopsi teknologi yang ditransfer merupakan salah satu tahapan penting dalam proses pembangunan pertanian dan pedesaan. Makalah ini menganalisis faktor sosial ekonomi yang mempengaruhi adopsi teknologi modern untuk usahatani cabai oleh petani di Jawa Tengah. Cabai merupakan sayuran bernilai tinggi yang relatif lebih menguntungkan dibanding sayuran lainnya dan menyediakan tingkat pendapatan dan lapangan kerja yang lebih tinggi dibanding padi. Namun budidaya cabai memerlukan modal lebih tinggi. Data untuk penelitian ini dikumpulkan dari survai lapangan pada 160 petani di tiga kabupaten di Jawa Tengah, yaitu Magelang, Brebes dan Rembang pada tahun 2009-2010. Teknologi cabai yang dianalisis di sini adalah penerapan benih hibrida dan plastik mulsa perak. Hasil analisis menunjukkan bahwa tingkat pendidikan formal dan akses terhadap kredit merupakan faktor penting yang mempengaruhi petani cabai untuk mengadopsi teknologi tersebut. Tetapi, pengalaman dalam usahatani sayuran memiliki dampak negatif. Dengan demikian, temuan penelitian ini menunjukkan bahwa jika teknologi pertanian cabai diperkenalkan kepada masyarakat petani yang masih muda dan memiliki akses terhadap kredit, maka teknologi tersebut lebih memungkinkan diadopsi oleh masyarakat tani.
Effects of Potassium Fertilization on Growth and Yield of Wetland Rice in Grey Terrace Soils of Bangladesh

Variable rates (0, 20, 40, 60 and 80 kg ha -1 ) of potassium (K) fertilization effects on growth, yield as well as the relationship between yield and growth parameters of T. Aman (monsoon season) rice were examined in 2010 at Bangladesh Rice Research Institute (BRRI) research farm, Gazipur, Bangladesh following randomized complete block design with three replications. Test rice variety was BRRI dhan49 and the soil was Aeric Haplaquept. Plant height, panicle length, dry matter production at maturity, straw and grain yields significantly (p < 0.01) increased in a quadratic fashion; but tillersm -2 , panicles m -2 , spikelet panicle -1 , filled grains in a panicle, dry matter yield at panicle initiation (PI) stage increased significantly (p < 0.01) in a linear fashion when K rates were increased from 0 to 80 kg ha -1 . Maximum grain yield (4958 kg ha -1 ) was obtained at 80 kg K ha -1 . Panicles m -2 , spikelets in a panicle, filled grains, dry matter yield, harvest index, 1000 grain weight had significant positive association with grain yield. Optimum K rate and K requirement of BRRI dhan49 was found to be 64.14 kg ha -1 13 kg t -1 rice. Calculated K dose for T. Aman rice was much higher than the recommended dose. Therefore, potassium dose for wet season rice should be increased for desired yield otherwise potassium mining from soil and yield reduction might be occurred.
Machine-Learned or Expert-Engineered Features? Exploring Feature Engineering Methods in Detectors of Student Behavior and Affect

There is a long history of research on the development of models to detect and study student behavior and affect. Developing computer-based models has allowed the study of learning constructs at fine levels of granularity and over long periods of time. For many years, these models were developed using features based on previous educational research from the raw log data. More recently, however, the application of deep learning models has often skipped this feature engineering step by allowing the algorithm to learn features from the fine-grained raw log data. As many of these deep learning models have led to promising results, researchers have asked which situations may lead to machine-learned features performing better than expert-generated features. This work addresses this question by comparing the use of machine-learned and expert-engineered features for three previously-developed models of student affect, off-task behavior, and gaming the system. In addition, we propose a third feature-engineering method that combines expert features with machine learning to explore the strengths and weaknesses of these approaches to build detectors of student affect and unproductive behaviors.