Miracle-dz/UniFAR-FTUs huggingface dataset:
How a Lack of Green in the Residential Environment Lowers the Life Satisfaction of City Dwellers and Increases Their Willingness to Relocate

This paper investigates whether various forms of green spaces in the residential environment are associated with city dwellers’ life satisfaction and their willingness to relocate. Previous research on different forms of green spaces in the residential environment as a direct source of life satisfaction is scarce, and we know little about whether green spaces affect the decision to relocate. We address these topics with a two-equation model that estimates respondents’ considerations to relocate while accounting for life satisfaction. With this strategy, we are able to test which aspects of residential greenery (window view, green environment, green yard, own garden, and balcony) are associated with one or both outcomes, controlling for life-course events and demographic characteristics. The data come from a primary survey conducted in two large German cities, Cologne and Hamburg, in 2020/21 (N = 1886). The results show that not having green elements in the window view, not having a green yard, and—exclusively for parents—not having a garden increase the likelihood of considering residential relocation. Not having a balcony and not having a garden are directly associated with decreased life satisfaction, and decreased life satisfaction triggers the willingness to relocate.
Online Forecasting and Anomaly Detection Based on the ARIMA Model

Real-time diagnostics of complex technical systems such as power plants are critical to keep the system in its working state. An ideal diagnostic system must detect any fault in advance and predict the future state of the technical system, so predictive algorithms are used in the diagnostics. This paper proposes a novel, computationally simple algorithm based on the Auto-Regressive Integrated Moving Average model to solve anomaly detection and forecasting problems. The good performance of the proposed algorithm was confirmed in numerous numerical experiments for both anomaly detection and forecasting problems. Moreover, a description of the Autoregressive Integrated Moving Average Fault Detection (ARIMAFD) library, which includes the proposed algorithms, is provided in this paper. The developed algorithm proves to be an efficient algorithm and can be applied to problems related to anomaly detection and technological parameter forecasting in real diagnostic systems.
The Best Strategies for Inflationary Times

Over the past three decades, a sustained surge in inflation has been absent in developed markets. As a result, investors face the challenge of having limited experience and no recent data to guide the repositioning of their portfolios in the face of heightened inflation risk. In this article, the authors provide some insight by analyzing both passive and active strategies across a variety of asset classes for the United States, the United Kingdom, and Japan over the past 95 years. Unexpected inflation is bad news for traditional assets, such as bonds and equities, with local inflation having the greatest effect. Commodities have positive returns during inflation surges, but there is considerable variation within the commodity complex. Among the active strategies, the authors find that trend-following provides the most reliable protection during important inflation shocks. Active equity factor strategies also provide some degree of hedging ability. The authors also provide an analysis of alternative asset classes such as fine art and discuss the economic rationale for including cryptocurrencies as part of a strategy to protect against inflation. TOPICS: Developed markets, financial crises and financial market history, risk management, portfolio management/multi-asset allocation Key Findings ▪ The authors examine a range of passive and active strategies using a century of data in the United States, the United Kingdom, and Japan and find that passive equity and fixed-income strategies fare poorly during inflation surges. ▪ Commodities provide historical inflation protection, as do collectibles such as wine and fine art. ▪ Active strategies such as trend-following fare well during historical inflation surges, and equity factor strategies such as quality provide some protection.
Terroir of winter hardiness: bud LT50, water metrics, yield, and berry composition in Ontario Cabernet franc

Abstract: Winter hardiness may be influenced by vineyard terroir-driven factors, and vineyard zones with low water status [leaf water potential (ψ)] could be more winter hardy than vines with high water status (higher leaf ψ). Six Cabernet franc vineyards were chosen throughout the Niagara region in Ontario. Data were collected at fruit set, lag phase, and veraison [soil water content (SWC), leaf ψ], at harvest (yield components, berry composition), and three times during winter (LT50; the temperature at which 50% of buds die) in the 2010–2012 seasons. Interpolation by kriging and mapping of variables was completed using ArcGIS, and statistical analyses (linear correlation, k-means clustering, principal components analysis, multilinear regression) were performed. Spatial trends were observed in each vineyard for SWC, leaf ψ, yield components, berry composition, and LT50. Geographic information systems (GIS) and statistical analysis revealed that leaf ψ could predict LT50, with strong positive correlations between LT50 and leaf ψ values in most vineyards in 2010–2011. In the dry 2012 season, leaf ψ (particularly at veraison; range −1.3 to −1.6 MPa) was positively correlated to LT50, yield, titratable acidity (TA), pH, and Brix and negatively to SWC, color, anthocyanins, and phenols. Overall, vineyards in different appellations (Niagara Lakeshore, Lincoln Lakeshore, Four Mile Creek, Beamsville Bench) showed many similarities. These results suggest that there is a spatial component to winter injury, as with other aspects of terroir. Furthermore, this study allows for means by which to compare winter hardiness to other critical variables to better understand the terroir of the Niagara region.
Heterozygosity of the Alpha 1‐Antitrypsin Pi*Z Allele and Risk of Liver Disease

The serpin family A member 1 (SERPINA1) Z allele is present in approximately one in 25 individuals of European ancestry. Z allele homozygosity (Pi*ZZ) is the most common cause of alpha 1‐antitrypsin deficiency and is a proven risk factor for cirrhosis. We examined whether heterozygous Z allele (Pi*Z) carriers in United Kingdom (UK) Biobank, a population‐based cohort, are at increased risk of liver disease. We replicated findings in Massachusetts General Brigham Biobank, a hospital‐based cohort. We also examined variants associated with liver disease and assessed for gene–gene and gene–environment interactions. In UK Biobank, we identified 1,493 cases of cirrhosis, 12,603 Z allele heterozygotes, and 129 Z allele homozygotes among 312,671 unrelated white British participants. Heterozygous carriage of the Z allele was associated with cirrhosis compared to noncarriage (odds ratio [OR], 1.53; P = 1.1×10−04); homozygosity of the Z allele also increased the risk of cirrhosis (OR, 11.8; P = 1.8 × 10−09). The OR for cirrhosis of the Z allele was comparable to that of well‐established genetic variants, including patatin‐like phospholipase domain containing 3 (PNPLA3) I148M (OR, 1.48; P = 1.1 × 10−22) and transmembrane 6 superfamily member 2 (TM6SF2) E167K (OR, 1.34; P = 2.6 × 10−06). In heterozygotes compared to noncarriers, the Z allele was associated with higher alanine aminotransferase (ALT; P = = 4.6 × 10−46), aspartate aminotransferase (AST; P = 2.2 × 10−27), alkaline phosphatase (P = 3.3 × 10−43), gamma‐glutamyltransferase (P = 1.2 × 10−05), and total bilirubin (P = 6.4 × 10−06); Z allele homozygotes had even greater elevations in liver biochemistries. Body mass index (BMI) amplified the association of the Z allele for ALT (P interaction = 0.021) and AST (P interaction = 0.0040), suggesting a gene–environment interaction. Finally, we demonstrated genetic interactions between variants in PNPLA3, TM6SF2, and hydroxysteroid 17‐beta dehydrogenase 13 (HSD17B13); there was no evidence of epistasis between the Z allele and these variants. Conclusion: SERPINA1 Z allele heterozygosity is an important risk factor for liver disease; this risk is amplified by increasing BMI.
A Comprehensive Model to Study the Dynamic Accessibility of the Park & Ride System

A Park and Ride (P&R) system is an intermodal point where private vehicle users transfer to public transport to make a combined trip. Several researchers have measured the static accessibility of the P&R system. However, studying dynamic accessibility leads to a comprehensive model consisting of a series of elements and steps that allow for travel time analysis in various traffic conditions. Therefore, the purpose of this article is to develop an integrated model that provides a set of procedures which determine the travel origin points of the P&R system, calculate the trips in different traffic conditions (in this article, the results are shown in three scenarios: no traffic (NT), low traffic (LT), and heavy traffic (HT)), and include a hot spot analysis and correlation in order to finally be able to display the dynamic accessibility using geospatial software. The result shows that the accessibility of the P&R system varies depending on the traffic volume and the variation of the accessibility in the different areas that conform to the urban environment. In conclusion, the integrated model helps users decide on the best time to travel to the P&R system, allows transport planners to develop strategies to make the system more functional, and gives an excellent opportunity to develop a travel information system.
How does reverse factoring affect operating performance? An event study of Chinese manufacturing firms

PurposeAs a popular supply chain finance (SCF) strategy, reverse factoring has been widely adopted by buyer firms. However, the extant literature provides scant empirical evidence on the performance effect of reverse factoring. The purpose of this study is to seek to narrow this gap by empirically examining the relationship between reverse factoring and operating performance and the contingency conditions of this relationship.Design/methodology/approachBased on a sample of 167 announcements of reverse factoring implementation made by publicly listed Chinese manufacturing firms between 2014 and 2018, this paper employs a long-term event study approach to analyze the operating performance effect of reverse factoring as well as the moderating effects of production and innovation capabilities.FindingsThe event study results indicate that reverse factoring has a positive effect on buyer firms' operating performance in terms of cost efficiency and operating margin. In addition, both production and innovation capabilities positively moderate the relationship between reverse factoring and operating margin. However, neither of them moderates the relationship between reverse factoring and cost efficiency.Originality/valueThis is the first study that empirically examines the impact of reverse factoring on operating performance based on secondary data. Furthermore, it sheds light on the SCF literature by providing insights into the contingency effects of production and innovation capabilities, which also extends our understanding of the application of extended resource-based view in SCF research.
Habitat Partitioning and Overlap by Large Lacertid Lizards in Southern Europe

South-western Europe has a rich diversity of lacertid lizards. In this study, we evaluated the occupancy patterns and niche segregation of five species of lacertids, focusing on large-bodied species (i.e., adults having >75 mm snout-vent length) that occur in south-western Europe (Italian to the Iberian Peninsula). We characterized the niches occupied by these species based on climate and vegetation cover properties. We expected some commonality among phylogenetically related species, but also patterns of habitat segregation mitigating competition between ecologically equivalent species. We used multivariate ordination and probabilistic methods to describe the occupancy patterns and evaluated niche evolution through phylogenetic analyses. Our results showed climate niche partitioning, but with a wide overlap in transitional zones, where segregation is maintained by species-specific responses to the vegetation cover. The analyses also showed that phylogenetically related species tend to share large parts of their habitat niches. The occurrence of independent evolutionary lineages contributed to the regional species richness favored by a long history of niche divergence.
Antibacterial Activity of Crude and Fractions of Momordica foetida Leaf Extracts

The leaves of Momordica foetida were screened for their phytochemical composition and antimicrobial potential. Phytochemical screening of the crude extract showed the presence of various secondary metabolites which included alkaloids, flavonoids, terpenoids, steroids, saponins and tannins. In-vitro antimicrobial activities of the crude extract and five solvent fractions were screened against 28 bacterial strains using traditional methods. Among the five fractions, ethyl acetate exhibited the highest broad spectrum antibacterial activity against the tested bacteria and the decreased in the order of ethyl acetate > butanol > chloroform > aqueous > hexane fraction at a concentration of 5.0 mg mL -1 . The zone of inhibition exhibited by the EtOAc and BuOH fractions ranged from 8 to 17 mm while the CHCl3 fraction was between 7.5 and 15 mm. The hexane and aqueous fractions showed a zone of inhibition that ranged from 7 to 14 mm. The minimum inhibitory concentration (MIC) exhibited by EtOAc, CHCl3 and HEX fractions against the bacterial strains ranged between 0.156 and 2.5 mg mL -1 while that of BuOH and aqueous fractions ranged between 0.3125 and 5.0 mg mL -1 . The antibacterial activities of
Were Foreign Exchange Markets Reacting Negatively to Political Events? The Case of Malaysia

This article explores the effects of political events on foreign exchange returns in Malaysia. We identify five political events in recent history, namely the 13th General Election (GE13), the imprisonment of a key opposition politician, the scandal from the 1MDB exposé, the appointment of a new Central Bank Governor and the 14th General Election (GE14). Using event studies, our findings show that the imprisonment of the opposition party leader triggered a favourable response from the foreign exchange market. However, market reactions to the 1MDB scandal were largely unfavourable. The GE13 triggered unfavourable market response, while the reverse is true for market reactions to GE14. Market response to the appointment of the new Central Bank Governor was rather positive. The Event Study is the first of its kind that examines the foreign exchange market implications of key political events in Malaysia. There are practical considerations that emanate from these findings. JEL Classification: F31, D72, D73, O38
Metatalk and metalinguistic knowledge: the interplay of procedural and declarative knowledge in the classroom discourse of first-language grammar teaching

Abstract ‘High-quality talk’ is a fundamental principle of many approaches to teaching grammar. However, relatively few studies have attempted to characterize this talk with attention to the ways in which classroom dialogue might engender metalinguistic thinking. This paper explores how the concepts of procedural and declarative metalinguistic knowledge may be applied to classroom discourse in order to identify the problems and potentials of grammatical ‘Metatalk’. The data is drawn from observations of functionally-oriented grammar lessons in 17 classrooms across England. This opportunity sample was drawn from the intervention group of a randomized control trial, all of whom were working within a pedagogical model which embeds attention to grammar as a resource for meaning-making within the teaching of writing. Given the impact of effective teacher-student dialogue on student learning, studies such as this are valuable for illuminating how classroom talk operates within the teaching of grammar for writing. The findings particularly reveal the role of teacher-guided talk during collaborative writing activities in facilitating bi-directional transfer between declarative and procedural metalinguistic knowledge.
Applying machine learning methods to detect convection using Geostationary Operational Environmental Satellite-16 (GOES-16) advanced baseline imager (ABI) data

Abstract. An ability to accurately detect convective regions is essential for initializing models for short-term precipitation forecasts. Radar data are commonly used to detect convection, but radars that provide high-temporal-resolution data are mostly available over land, and the quality of the data tends to degrade over mountainous regions. On the other hand, geostationary satellite data are available nearly anywhere and in near-real time. Current operational geostationary satellites, the Geostationary Operational Environmental Satellite-16 (GOES-16) and Satellite-17, provide high-spatial- and high-temporal-resolution data but only of cloud top properties; 1 min data, however, allow us to observe convection from visible and infrared data even without vertical information of the convective system. Existing detection algorithms using visible and infrared data look for static features of convective clouds such as overshooting top or lumpy cloud top surface or cloud growth that occurs over periods of 30 min to an hour. This study represents a proof of concept that artificial intelligence (AI) is able, when given high-spatial- and high-temporal-resolution data from GOES-16, to learn physical properties of convective clouds and automate the detection process. A neural network model with convolutional layers is proposed to identify convection from the high-temporal resolution GOES-16 data. The model takes five temporal images from channel 2 (0.65 µ m) and 14 (11.2 µ m) as inputs and produces a map of convective regions. In order to provide products comparable to the radar products, it is trained against Multi-Radar Multi-Sensor (MRMS), which is a radar-based product that uses a rather sophisticated method to classify precipitation types. Two channels from GOES-16, each related to cloud optical depth (channel 2) and cloud top height (channel 14), are expected to best represent features of convective clouds: high reflectance, lumpy cloud top surface, and low cloud top temperature. The model has correctly learned those features of convective clouds and resulted in a reasonably low false alarm ratio (FAR) and high probability of detection (POD). However, FAR and POD can vary depending on the threshold, and a proper threshold needs to be chosen based on the purpose.
Chemical composition of germinating Tunisian almond (Prunus Amygdalus Mill.) seedlings oil

Almonds (Prunus amygdalus) are a rich source of many essential nutrients. However, there is a lack of enough information on almond varieties' biochemical composition, especially at the germination stage. Therefore, this study was conducted to determine the chemical components of the germinating Tunisian almonds. The study included determining the content of oils, proteins, fatty acids, and triglycerides during germination. Results indicated that the oleaginous seeds are rich in oil (55 to 65% of the dry mass) and crude protein (21.825 mg/mL). The dominant polyunsaturated fatty acids are oleic and linoleic acids which represent 64.53% and 24.38%, respectively, while palmitic acid is the most dominant saturated fatty acid with 7.65% of the total fatty acids. Also, the primary molecular types of triglycerides detected by L.C. analysis are triolein (32.3%) and dioleolinolein (24.0%), followed by palmitodiolein (12.5%) and oleodilinolein (12.6%.). The physico-chemical properties study revealed that almond oil remains stable, thus preserving its quality and nutritional value, even during transition from dormancy to germination. On the other hand, we also detected the presence of a lipolytic activity which is maximum on the 3rd day of germination (4.66 mUI). Our results indicate that almond oil plays an important role in human nutrition due to the presence of unsaturated fatty acids, and it is more stable than other oils.
Meat‐related cognitive dissonance: The social psychology of eating animals

As the practice of eating animals as meat faces increased scrutiny for its ethical, health, and environmental implications, a subfield devoted to its psychology has begun to flourish. Researchers have been especially interested in understanding how individuals morally care for animals and wish them no harm yet simultaneously eat them as food. Merging theories of cognitive dissonance, moral disengagement, and neutralization, the current review aims to provide a framework of meat ‐ related cognitive dissonance (MRCD) that explains this belief–behavior inconsistency. First, we evaluate the existing research on mechanisms that (a) prevent MRCD from occurring and (b) reduce MRCD once it has occurred. Second, we highlight promising avenues for further research on MRCD. The purpose of this review, ultimately, is to synthesize findings from this emerging area of research and to highlight its exciting future directions for the field of social psychology.
Influence of Synthesis-Related Microstructural Features on the Electrocaloric Effect for 0.9Pb(Mg1/3Nb2/3)O3–0.1PbTiO3 Ceramics

Despite having a very similar electrocaloric (EC) coefficient, i.e., the EC temperature change divided by the applied electric field, the 0.9Pb(Mg1/3Nb2/3)O3–0.1PbTiO3 (PMN-10PT) ceramic prepared by mechanochemical synthesis exhibits a much higher EC temperature change than the columbite-derived version, i.e., 2.37 °C at 107 °C and 115 kV/cm. The difference is due to the almost two-times-higher breakdown field of the former material, 115 kV/cm, as opposed to 57 kV/cm in the latter. While both ceramic materials have similarly high relative densities and grain sizes (>96%, ≈5 μm) and an almost correct perovskite stoichiometry, the mechanochemical synthesis contributes to a lower level of compositional deviation. The peak permittivity and saturated polarization are slightly higher and the domain structure is finer in the mechanochemically derived ceramic. The secondary phases that result from each synthesis are identified and related to different interactions of the individual materials with the electric field: an intergranular lead-silicate-based phase in the columbite-derived PMN-10PT and MgO inclusions in the mechanochemically derived ceramic.
Finding the Limits of Magnetic Hyperthermia on Core-Shell Nanoparticles Fabricated by Physical Vapor Methods

Magnetic nanoparticles can generate heat when exposed to an alternating magnetic field. Their heating efficacy is governed by their magnetic properties that are in turn determined by their composition, size and morphology. Thus far, iron oxides (e.g., magnetite, Fe3O4) have been the most popular materials in use, though recently bimagnetic core-shell structures are gaining ground. Herein we present a study on the effect of particle morphology on heating efficiency. More specifically, we use zero waste impact methods for the synthesis of metal/metal oxide Fe/Fe3O4 nanoparticles in both spherical and cubic shapes, which present an interesting venue for understanding how spin coupling across interfaces and also finite size effects may influence the magnetic response. We show that these particles can generate sufficient heat (hundreds of watts per gram) to drive hyperthermia applications, whereas faceted nanoparticles demonstrate superior heating capabilities than spherical nanoparticles of similar size.