Miracle-dz/UniFAR-FTUs huggingface dataset:
Fake It Till You Make It : Reputation , Competition , and Yelp Review Fraud

Review sites have become increasingly important sources of information for consumers. Because these reviews affect sales, businesses have the incentive to game the system by leaving positive reviews for themselves, or negative reviews for their competitors. Such review fraud undermines the trustworthiness of consumer reviews, and constitutes a major risk factor for review sites. In this paper, we investigate review fraud on the popular consumer review site Yelp. We construct a novel data set to analyze this problem, combining restaurant reviews with Yelp’s algorithmic indicator of fake reviews. Using this imperfect indicator as a proxy, we develop an empirical methodology to identify the points in the life-cycle of a business during which review fraud is most prevalent. We find that a restaurant’s changing reputation affects its decision to engage in review fraud. Specifically, a restaurant is more likely to seek a positive fake review when its reputation is weak, i.e., when it has few reviews, or it has recently received bad reviews. Consistent with theory, we find that chains are less likely than independent restaurants to engage in review fraud. We then turn our attention to negative review fraud, and find that increased competition by similar restaurants the driving force behind it. †Part of this work was completed while the author was supported by a Simons Foundation Postdoctoral Fellowship.
The Computational Complexity Column Low-discrepancy Sets for High-dimensional Rectangles: a Survey

With this issue of the Bulletin, my tenure as editor of the Computational Complexity Column comes to an end. Lance Fortnow will edit this column beginning with the June issue, and we can look forward to a long series of informative columns under his direction. It has been a pleasure, and I am glad that the column will be in good hands. Although columns appearing in this space focus on complexity classes and lower bounds, it is important to realize that algorithmic techniques (upper bounds) frequently find application in proving lower bounds, and in proving new relationships among complexity classes. This is especially evident in the exciting developments in the field of derandomization. We are fortunate, in this issue of the Bulletin, to have an overview of some important algorithmic techniques by a leading figure in the field of derandomization. Abstract A sub-area of discrepancy theory that has received much attention in computer science recently , is that of explicit constructions of low-discrepancy point sets for various types of rectangle families in high dimension. This research has led to interesting applications in error-control coding , distributed protocols, Web document filtering, derandomization, and other areas. We give a short survey of this area here.
The Computational Complexity Column

The 1980’s was a golden period for Boolean circuit complexity lower bounds. There were major breakthroughs. For example, Razborov’s exponential size lower bound for monotone Boolean circuits computing the Clique function and the Razborov-Smolensky superpolynomial size lower bounds for constant-depth circuits with MOD p gates for prime p . These results made researchers optimistic of progress on big lower bound questions and complexity class separations. However, in the last two decades, this optimism gradually turned into despair. We still do not know how to prove superpolynomial lower bounds for constant-depth circuits with MOD 6 gates for a function computable in exponential time. Ryan Williams’ exciting lower bound result of 2011, that nondeterministic exponential time does not have polynomial-size unbounded fanin constant-depth circuits with MOD m gates for any composite m , has renewed optimism in the area. The best part is that his approach is potentially applicable to other lower bound questions. In this wonderful article, Rahul Santhanam explores this theme of connections between improved SAT algorithms and circuit lower bounds.
iological activity of heterologous murine interleukin-10 and preliminary tudies on the use of a dextrin nanogel as a delivery system

Interleukin-10 (IL-10) is an anti-inflammatory cytokine, which active form is a non-covalent homodimer with two intramolecular disulphide bonds essential for its biological activity. A mutated form of murine IL-10 was successfully expressed in E. coli, recovered and purified from inclusion bodies. Its ability to reduce tumor necrosis factor synthesis and down-regulate class II major histocompatibility complex vailable online 9 September 2010
The Logic in computer science Column

The 0-1 law for first-order properties of finite structures and its proof via extension axioms were first obtained in the context of arbitrary finite structures for a fixed finite vocabulary. But it was soon observed that the result and the proof continue to work for structures subject to certain restrictions. Examples include undirected graphs, tournaments, and pure simplicial complexes. We discuss two ways of formalizing these extensions, Oberschelp’s (1982) parametric conditions and our (2003) thesauri. We show that, if we restrict thesauri by requiring their probability distributions to be uniform, then they and parametric conditions are equivalent. Nevertheless, some situations admit more natural descriptions in terms of thesauri, and the thesaurus point of view suggests some possible extensions of the theory.
Systematic Variability of Soil Hydraulic Conductivity Across Three Vertisol Catenas

Systematic Variability of Soil Hydraulic Conductivity Across Three Vertisol Catenas. (August 2010) Leonardo Daniel Rivera, B.S., Texas A&M University Chair of Advisory Committee: Dr. Cristine Morgan Soil hydraulic properties, such as saturated hydraulic conductivity (Ks), have high spatial variation, but little is known about how to vary a few measurements of Ks over an area to model hydrology in a watershed with complex topography and multiple land uses. Variations in soil structure, macropores (especially in soil that shrink and swell), land use, and soil development can cause large variations in Ks within one soil type. Characterizing the impacts of soil properties that might vary systematically with land use and terrain attributes on Ks rates would provide insight on how management and human activity affect local and regional hydrology. The overall objective of this research was to develop a strategy for using published infiltration and Ks measurements by the Natural Resources Conservation Service for watershed hydrology applications in a Vertisol, and to extend this knowledge toward developing recommendations for future infiltration measurements. To achieve this goal, soil infiltration measurements were collected across three catenas of Houston Black and Heiden clays (fine, smectitic, thermic Udic Haplusterts) under three land uses (improved pasture, native prairie, and conventional
The Mediating Role of Meaning in Life in the Relationship between Adverse Childhood Experiences and Depressive Symptoms in Secondary Vocational School Students

: Secondary vocational school students have a poor student population and experience depressive symptoms more frequently and more prominently. The aim of this study was to investigate the mediating role of meaning in life between adverse childhood experiences and depressive symptoms in secondary vocational school students. The method applied in this paper is using CTO-SF, CESDS and the Meaning in Life Scale to assess adverse childhood experience, depressive symptom and meaning in life. Hayes's PROCESS macro of SPSS was used to test the relationship between these variables. Adverse childhood experiences were positively correlated with depressive symptoms; meaning in life partially mediated the relationship between adverse childhood experiences and depressive symptoms. Meaning in life is an important mediating mechanism in the association between adverse childhood experiences and depressive symptoms in secondary vocational school students, and implications for preventing or reducing depressive symptoms are discussed.
Computer-aided classification of lung nodules on computed tomography images via deep learning technique

: Lung cancer has a poor prognosis when not diagnosed early and unresectable lesions are present. The management of small lung nodules noted on computed tomography scan is controversial due to uncertain tumor characteristics. A conventional computer-aided diagnosis (CAD) scheme requires several image processing and pattern recognition steps to accomplish a quantitative tumor differentiation result. In such an ad hoc image analysis pipeline, every step depends heavily on the performance of the previous step. Accordingly, tuning of classification performance in a conventional CAD scheme is very complicated and arduous. Deep learning techniques, on the other hand, have the intrinsic advantage of an automatic exploitation feature and tuning of performance in a seamless fashion. In this study, we attempted to simplify the image analysis pipeline of conventional CAD with deep learning techniques. Specifically, we introduced models of a deep belief network and a convolutional neural network in the context of nodule classification in computed tomography images. Two baseline methods with feature computing steps were implemented for comparison. The experimental results suggest that deep learning methods could achieve better discriminative results and hold promise in the CAD application domain.
Effect of Location, Disinfection, and Building Materials on the Presence and Richness of Culturable Mycobiota through Oligotrophic Drinking Water Systems

Safe drinking water is a constant challenge due to global environmental changes and the rise of emerging pathogens—lately, these also include fungi. The fungal presence in water greatly varies between sampling locations. Little is known about fungi from water in combination with a selection of materials used in water distribution systems. Our research was focused on five water plants located in the Pannonian Plain, Slovenia. Sampled water originated from different natural water sources and was subjected to different cleaning methods before distribution. The average numbers of fungi from natural water, water after disinfection, water at the first sampling point in the water network, and water at the last sampling point were 260, 49, 64, and 97 CFU/L, respectively. Chlorination reduced the number of fungi by a factor of 5, but its effect decreased with the length of the water network. The occurrence of different fungi in water and on materials depended on the choice of material. The presence of the genera Aspergillus, Acremonium, Furcasterigmium, Gliomastix, and Sarocladium was mostly observed on cement, while Cadophora, Cladosporium, Cyphellophora, and Exophiala prevailed on metals. Plastic materials were more susceptible to colonization with basidiomycetous fungi. Opportunistically pathogenic fungi were isolated sporadically from materials and water and do not represent a significant health risk for water consumers. In addition to cultivation data, physico-chemical features of water were measured and later processed with machine learning methods, revealing the sampling location and water cleaning processes as the main factors affecting fungal presence and richness in water and materials in contact with water.
Exploration of possible use of linseed oil as a dietary replacement of FO in farm-made tilapia ( Oreochromis niloticus ) feeds

This study explored the impact of varying dietary linseed oil composition on growth, survival and tissue polyunsaturated fatty acids (PUFA) profiles in Nile tilapia ( Oreochromis niloticus) . Five iso-nitrogenious diets with varying linseed and sunflower oil concentrations were formulated and fish fed twice daily to for 3 months. Commercial diet was used as a control in triplicate tanks set for each diet treatment. Growth parameters were measured from changes in body weight and length. A 75:25 ratio of sunflower oil to linseed oil gave a better survival and specific growth rate than 100% linseed oil or 100% sunflower oil. Tissue PUFA composition were determined using gas chromatography. High dietary linseed oil composition (100%) resulted into significantly high (P<0.05) total n3 fatty acids (9.9-25%) and DHA (1.8-7.9%) in muscles whereas liver n3 fatty acids and DHA composition ranged between 9.3-25.5 and 0.7-2.6%, respectively. Muscle and liver n3/n6 ratio ranged between 0.7-2.2 and 0.7-2.6 while tissue arachidonic acid (ARA 20.4 n6) content ranged between 2.6-3.5% in muscles and 3.4-4.5% in the liver. ARA 20.4 n6 values were low relative to the dietary precursor, linoleic acid, LA, 18.2 n6. Fatty acid deposition in the tissues increased with the feeding period with the third feeding month recording significantly higher DHA, total n3 and n3/n6 ratio. Based on the result, dietary linseed oil > 50% reduced growth and survival rate in tilapia, however, it increased tissue accumulation of essential fatty acids which also increased with the length of feeding period.
Frictional properties of phyllosilicate‐rich mylonite and conditions for the brittle‐ductile transition

To understand frictional properties of natural phyllosilicate‐rich mylonite along fault depth, friction experiments on simulated mylonite gouge were conducted at temperatures of 100–600°C, effective normal stresses of 100–300 MPa, and loading rates of 0.04–1.0 µm/s. Experimental results show that at temperatures above 200°C, frictional strength of the mylonite gouge exhibits systematic increase with temperature, in the range of 0.52–0.73. Under 200–300 MPa normal stress conditions, velocity dependence of mylonite gouge shows a transition from initial velocity‐strengthening (Regime 1) to velocity‐weakening behavior (Regime 2) at a temperature between 200 and 300°C and transitions back to velocity‐strengthening behavior (Regime 3) as temperature increases. The latter transition is also found to be promoted by slower loading rates. Friction stability of the mylonite gouge also exhibits a strong pressure sensitivity. While velocity‐strengthening behavior in Regime 3 is absent under 100 MPa normal stress condition, stable frictional behavior is significantly enhanced at higher effective normal stresses, with the transition temperature to velocity strengthening decreasing with effective normal stress. Microstructural analysis shows that the transition of velocity dependence from velocity weakening to velocity strengthening corresponds to transition from cataclastic flow to semibrittle process featured by mylonitic structures (S‐C fabrics). The formation of mylonitic fabrics is due to plastic deformation of phyllosilicates combined with thermally activated grain size reduction of hard clasts (quartz and plagioclase). Our results may help constrain depth range of seismogenesis within phyllosilicate‐rich fault zone and imply that variation of effective normal stress may affect faulting behavior.
Impact of climate change on crop water use and productivity: A case study of Bagmati River basin, Nepal.

Global climate change induced by increased greenhouse gas concentration has been widely accepted. Natural and human systems are expected to be exposed to direct effects of temperature and precipitation change. The agriculture sector is most vulnerable to climate change. Thus, climate change can have serious implications on the agro-based national economy of Nepal. Limited studies have been carried out to analyze the impacts of climate change in a national level. However, impacts of climate change in the basin level have not been quantified yet. Moreover, spatial and temporal variability of climate change might be hazardous in a local level. Considering these facts, this study aims to evaluate the impact of climate change on crop water use and productivity in the Bagmati River basin, Nepal. To evaluate local effects of climate change, the whole Bagmati basin (3,700 km) was divided into two upper and lower zones. Statistical tools were used in the trend analysis and scenario development of climatic variables. Assessment of crop water use and productivity in the basins were carried out using (i) baseline weather data and (ii) weather data modified by plausible future climate change through widely accepted CROPWAT computer model. Trend analysis of maximum and minimum temperature records (1987 to 2005) from 9 stations distributed across Bagmati basin showed that mean annual temperature in the high altitude region (elevation 250-2300 m) of the basin is increasing much faster than the low altitude region (elevation 80-250m). Similarly, annual precipitation trends (1978 to 2005) are also increasing in the basin. However, these trends are not consistent with all Nepal (1981 to 1998) trends. Maize is already facing water stress in the low altitude of the basin and the situation is likely to increase in the future. All scenarios project negative results (4% to 29%), especially the Canadian Climate Change Model (CCCM) projection (15% to 29%) in 2xCO2 condition. Climate change exerts an insignificant (0 to 4.5%) reduction on Maize yield in high altitude region of the Bagmati basin (without considering beneficial effects of CO2 on the crop). Business-As-Usual (BAU) scenarios experience greater reduction in Maize yield (31% to 45%) than the other scenarios by the year 2060, if climatic parameters in the Bagmati basin followed all Nepal trend rather than basin trend.
Problem‐solving test: Conditional gene targeting using the Cre/loxP recombination system

Terms to be familiar with before you start to solve the test: gene targeting, knock‐out mutation, bacteriophage, complementary base‐pairing, homologous recombination, deletion, transgenic organisms, promoter, polyadenylation element, transgene, DNA replication, RNA polymerase, Shine‐Dalgarno sequence, restriction endonuclease, polymerase chain reaction, primer, transcription, SV40 virus, malignant transformation, spacer region, gene expression, agarose gel electrophoresis, ethidium bromide staining, Southern‐blotting, probe, reporter gene. © 2013 by The International Union of Biochemistry and Molecular Biology, 41(6):445–449, 2013
Light-Stimulated IGZO Transistors with Tunable Synaptic Plasticity Based on Casein Electrolyte Electric Double Layer for Neuromorphic Systems

In this study, optoelectronic synaptic transistors based on indium–gallium–zinc oxide (IGZO) with a casein electrolyte-based electric double layer (EDL) were examined. The casein electrolyte played a crucial role in modulating synaptic plasticity through an internal proton-induced EDL effect. Thus, important synaptic behaviors, such as excitatory post-synaptic current, paired-pulse facilitation, and spike rate-dependent and spike number-dependent plasticity, were successfully implemented by utilizing the persistent photoconductivity effect of the IGZO channel stimulated by light. The synergy between the light stimulation and the EDL effect allowed the effective modulation of synaptic plasticity, enabling the control of memory levels, including the conversion of short-term memory to long-term memory. Furthermore, a Modified National Institute of Standards and Technology digit recognition simulation was performed using a three-layer artificial neural network model, achieving a high recognition rate of 90.5%. These results demonstrated a high application potential of the proposed optoelectronic synaptic transistors in neuromorphic visual systems.
Reﬂections on the Impact of an Intergenerational Digital Storytelling Program on Changing Attitudes and Fostering Dialogue and Understanding across the Generations

: Digital storytelling (DST) has the primary goal of giving underrepresented voices a platform to be seen and heard. Adding an intergenerational dimension can bring about many other beneﬁts for all participants as well as the wider community. This article presents a reﬂection on the Positive Ageing Digital Storytelling Intergenerational Program (PADSIP), outlining the various elements involve in program planning and implementation, reﬂecting on the past 15 years of program delivery, and underscoring future directions. PADSIP brings together older adults from both community and residential care settings with high school students in an intergenerational context. The process involves collaboratively creating digital stories that explore shared passions and lived experiences. Over the past 15 years, the program has evolved to include various adaptations to accommodate diverse groups, including neurodiverse individuals and those with disabilities. The program, originally taking a ten-session weekly format, has even become an integral part of school curricula in one local high school. Although the COVID-19 pandemic prompted adjustments including temporary transition of program meetings to online platforms as well as video production assistance, the intergenerational bonds and meaningful dialogues remained strong. By challenging stereotypes and fostering deeper connections, the program highlights the potential for intergenerational DST to positively reshape attitudes and understanding among participants. Current and future program research seek to delve into the mechanisms that facilitate such transformative outcomes, investigating the in-depth connections and communication that characterise the intergenerational DST approach.
sensiPhy: an R-package for sensitivity analysis in phylogenetic comparative methods 1

1. Biological conclusions drawn from phylogenetic comparative methods can be sensitive to 12 uncertainty in species sampling, phylogeny and data. To be confident about our conclusions, we 13 need to quantify their robustness to such uncertainty. 14 2. We present sensiPhy, an R-package to easily and rapidly perform sensitivity analysis for 15 phylogenetic comparative methods. sensiPhy allows researchers to evaluate the sampling effort, 16 detect influential species and clades, assess phylogenetic uncertainty and quantify the effects of 17 intraspecific variation, for phylogenetic regression and for metrics of phylogenetic signal, 18 diversification and trait evolution. 19 3. Uniquely, sensiPhy allows users to simultaneously quantify the effects of different types of 20 uncertainty and potential interactions among them. 21 4. Using real data, we show how conclusions from comparative methods can be affected by 22 uncertainty and how sensiPhy can help determine if a conclusion is robust. 23 5. By providing a single, intuitive and user-friendly resource that can evaluate various sources of uncertainty, sensiPhy aims to encourage researchers, and particularly less experienced users, to 25 incorporate sensitivity analyses in their phylogenetic comparative analyses.
Discussion Forums Using Semantic Similarity Based Topic Chains

Students’ conversations in academic settings evolve over time and can be aﬀected by events such as the COVID-19 pandemic. In this paper, we employ a Contextualized Topic Modeling technique to detect coherent topics from students’ posts in online discussion forums. We construct topic chains by connecting semantically similar topics across months using Word Mover’s Distance. Consistent academic discourse and contemporary events such as the COVID-19 outbreak and the Black Lives Matter movement were found among prominent topics. In later months, new themes around students’ lived experiences emerged and evolved into discussions reﬂecting the shift in educational experiences. Results revealed a signiﬁcant increase in more general topics after the onset of pandemic. Our proposed framework can also be applied to other contexts investigating temporal topic trends in large-scale text data.