Miracle-dz/UniFAR-FTUs huggingface dataset:
Addressing sustainable development goals for confronting climate change: Insights and summary solutions in the stress stupidity system

Abstract We employ the concept of stupidity to address why more has not been done to address climate change and sustainable development. While the ‘new’ science of stupid has long existed in organizational studies, academicians have been too polite to call it that and organizational researchers historically labeled it the ‘threat-rigidity effect. ’ With Alvesson and Spicer’s ‘stupidity-based theory of organizations’ management researchers overcame this reluctance. In this work we explore what we will call the ‘stress-stupidity system. ’ Building on the threat-rigidity effect, we outline the elements of the stress-stupidity system and look at how we may be able to ‘fix stupid’ to address issues of sustainability.
Association of body image dissatisfaction with body mass index trajectory: the Adolescent Nutritional Assessment Longitudinal Study cohort

ABSTRACT Objective To examine the association of body image dissatisfaction (BID) with body mass index (BMI) trajectory among students from a metropolitan area of Rio de Janeiro. Methods Data were analyzed for 809 middle school students followed from 2010 to 2013, and 1131 high school students followed from 2010 to 2012. BID was assessed using a body silhouettes scale. Type of school (public and private) was used as a proxy of socioeconomic status. Results In the middle school cohort, girls from private schools who wanted to have smaller and bigger silhouettes gained fewer BMI units than those who were satisfied with their body image ( p < 0.05). In the high school, girls from private schools who wished to have bigger and smaller silhouettes experienced greater BMI increase than girls who were satisfied with their body image ( p < 0.05). Also, in the high school cohort, boys from public schools who wished to have smaller and bigger silhouettes experienced smaller BMI increase than boys who were satisfied ( p < 0.05). Conclusion BID may be related to the BMI trajectory in girls from private schools and in boys from public schools.
Revisiting Second Language Readers’ Memory for Narrative Texts: The Role of Causal and Semantic Text Relations

Abstract Previous studies have investigated how second language (L2) readers construct memory for narrative texts according to causal relations between the events described. This study aims to extend their findings by including semantic text relations (similarity of meaning) as another variable, which are theoretically expected to play an additional role in comprehension. With this aim, 121 Japanese learners of English read a set of 200-word long narratives adapted from previous studies. The causal relationships between the text statements were identified using a causal network analysis, whereas the semantic text relations were evaluated by a computational method (latent semantic analsyis). After reading the narratives, participants performed a written recall task. The results of the recall analysis confirmed that the global causal text relations influence the memory for narrative texts. The results further revealed that local semantic relations between adjacent text statements also have an impact. These findings are discussed in light of theories of discourse comprehension.
“They Think I'm a Lawyer”: Undocumented College Students as Legal Brokers for Their Undocumented Parents

Past research demonstrates that children of immigrants serve as language and cultural brokers for their parents. However, much of this work centers on immigrants with protected legal status. Drawing on thirty in&#8208;depth interviews with undocumented college students, I conceptualize the phenomenon of legal brokering to capture how undocumented students share legal resources with their parents. In addition to this conceptualization, I find that four factors shaped how students served as legal brokers: (1) online platforms; (2) institutional support; (3) networks of support; and (4) involvement in immigrant rights organizations. These findings advance theoretical frameworks in segmented assimilation theory, sociolegal studies, and immigrant illegality.
Aptitude of Vermicompost and Bio-fertilizers on Crop growth, yield and economics of Turmeric (Curcuma longa L.)

Nutrient management is one of the fundamental cultural practices that impact the soil fertility status in addition to plant growth. However, injudicious utility of chemical fertilizer harm the soil health along with entire ecosystem (Chanahan et al., 2018). Organic manures and bio-fertilizers are the alternative sources of plant nutrition. Intensification of crop production and sustainability of soil fertility status is the sole objective that can be achieved by these biological inputs (Roy et al., 2011). Vermicompost are generally obtained by a non-thermophilic biodegradation of natural International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 6 (2020) Journal homepage: http://www.ijcmas. com
A Global Review of PWR Nuclear Power Plants

Nuclear energy is presented as a real option in the face of the current problem of climate change and the need to reduce CO2 emissions. The nuclear reactor design with the greatest global impact throughout history and which has the most ambitious development plans is the Pressurized Water Reactor (PWR). Thus, a global review of such a reactor design is presented in this paper, utilizing the analysis of (i) technical aspects of the different variants of the PWR design implemented over the past eight years, (ii) the level of implementation of PWR nuclear power plants in the world, and (iii) a life extension scenario and future trends in PWR design based on current research and development (R&D) activity. To develop the second analysis, a statistical study of the implementation of the different PWR variants has been carried out. Such a statistical analysis is based on the operating factor, which represents the relative frequency of reactors operating around the world. The results reflect the hegemony of the western variants in the 300 reactors currently operating, highlighting the North American and French versions. Furthermore, a simulation of a possible scenario of increasing the useful life of operational PWRs up to 60 years has been proposed, seeing that in 2050 the generation capacity of nuclear PWRs power plants will decrease by 50%, and the number of operating reactors by 70%.
Growing pains: Paradoxical tensions and vicious cycles in new venture growth

In this article, we explore how paradoxical tensions related to exploration–exploitation dynamics may shape vicious cycles in high-growth ventures. Based on an inductive, interpretive case study at a telecommunications firm in the United Kingdom, we identify a set of drivers through which vicious cycles may emerge and persist over time. While some drivers are associated with originating the vicious cycle (cycle originators), others are associated with sustaining it (cycle perpetuators). Cycle originators identified in the study include tradeoff cognition, structural separation, and a structural leadership void. Cycle perpetuators include intergroup tensions, ineffectual integration, and a temporal leadership void. We show how the interplay between these drivers in a self-reinforcing process culminates in the escalation of tensions and a political turnover (cycle climax). In the field study, we observe the operation of this pattern over two full cycles. Based on the findings, we develop a framework relating paradoxical tensions to vicious cycles in new venture growth. We conclude by challenging traditional stage-based conceptualizations of new venture growth, and by discussing the implications of our study for research on the linkages between organizational paradox, ambidexterity, and venture growth theory.
La pandémie Covid-19 et l’émergence d’un nouveau technolecte

Dans cet article, nous allons essayer d’approcher le technolecte de la pandemie de la Covid-19 qui est un domaine technolectal en pleine emergence actuellement, suite a la crise sanitaire que traverse le monde depuis l’identification d’un nouveau coronavirus a Wuhan en Chine, a la fin du mois de decembre 2019. Il s’agit d’etudier les unites technolectales relevant de ce domaine et qui ne cessent de parsemer les textes de la presse electronique marocaine d’expression francaise. Le corpus recueilli contient des unites technolectales simples et complexes provenant de domaines specifiques (sante, medecine, droit, sociologie, etc.) ; elles semblent creer une dynamique de la langue francaise qui use de neologie et de creativite. Il s’ensuit que le technolecte de la Covid-19 presente une particularite, celle d’englober plusieurs domaines specifiques a la fois.
Personal Semantic Variations in Word Meanings: Induction, Application, and Analysis

When people verbalize what they have felt with diﬀerent sensory functions, they often represent diﬀerent meanings such as with temperature range using the same word cold or the same meaning by using diﬀerent words (e.g., hazy and cloudy ). These interpersonal variations in word meanings have the eﬀects of not only preventing people from communicating eﬃciently with each other but also causing troubles in natural language processing ( NLP ). Accordingly, to highlight interpersonal semantic variations in word meanings, a method for inducing personalized word embeddings is proposed. This method learns word embeddings from an NLP task, distinguishing each word used by diﬀerent individuals. Review-target identiﬁcation was adopted as a task to prevent irrelevant biases from contaminating word embeddings. The scalability and stability of inducing personalized word embeddings were improved using a residual network and independent ﬁne-tuning for each individual through multi-task learning along with target-attribute predictions. The results of the experiments using two large scale review datasets conﬁrmed that the proposed method was eﬀective for estimating the target items, and the resulting word embeddings were also eﬀective in solving sentiment analysis. By using the acquired personalized word embeddings, it was possible to reveal tendencies in semantic variations of the word meanings.
Exploring SNPs (Single Nucleotide Polymorphisms) of Myostatin gene in coding region in Bali cattle

The gene MSTN is a member of the superfamily growth gene transforming growth factor β (TGF-β) that functions to suppress muscle growth. The purpose of this study was to analyze the polymorphisms of MSTN genes in the coding region (exon 1, 2, and 3) in Bali cattle kept at the Breeding Center for Bali cattle (BPTU-HPT) in Denpasar. The number of samples used was 52 heads male of Bali cattle aged 2-3 years. SNP identification was done by amplifying the coding region, exon 1, exon 2 and exon 3 MSTN genes using direct sequencing method. Analysis of MSTN gene sequences in Bali cattle was carried out by using the BioEdit and MEGA7 programs. The present study found a total of 18 SNP mutations namely point mutation that are 4 SNP (g.313 C>A, g.324 T>A, g.330 T>G, g.400 G>A) in exon 1, 1 SNP (g.2609 G>A) in exon 2, and 13 SNP (g.4821 C>A, g.4838 C>T, g.4842 A>C, g.4849 T>C, g.4868 C>A, g.4873 C>G, g.4900 T>G, 4905 C>G, g.4957 C>G, g.4959 C>A, g.4969 T>A, g.4974 T>C, g.5044 C>A) in exon 3. SNPs found in the MSTN gene in Bali cattle might be used as candidates for Marker Assisted Selection, especially in Bali cattle.
Developing and evaluating predictive conveyor belt wear models

Abstract Conveyor belt wear is an important consideration in the bulk materials handling industry. We define four belt wear rate metrics and develop a model to predict wear rates of new conveyor configurations using an industry dataset that includes ultrasonic thickness measurements, conveyor attributes, and conveyor throughput. All variables are expected to contribute in some way to explaining wear rate and are included in modeling. One specific metric, the maximum throughput-based wear rate, is selected as the prediction target, and cross-validation is used to evaluate the out-of-sample performance of random forest and linear regression algorithms. The random forest approach achieves a lower error of 0.152 mm/megatons (standard deviation [SD] = 0.0648). Permutation importance and partial dependence plots are computed to provide insights into the relationship between conveyor parameters and wear rate. This work demonstrates how belt wear rate can be quantified from imprecise thickness testing methods and provides a transparent modeling framework applicable to other supervised learning problems in risk and reliability.
CLUSIA HILARIANA, A KEY SPECIES ON NUTRIENT CYCLING IN SAND DUNE VEGETATION THICKETS

Interspecific plant-plant interactions studies showed that C lusia hilariana plays a facilitation role in the scattered vegetation thickets of the Brazilian sandy coastal plain vegetation (Restinga). In the Clusia open formation in the Jurubatiba Restinga National Park there are thickets differing in the presence and senescence of Clusia : (1) healthy Clusia thickets (HCT); (2) senescent Clusia thickets (SCT); and also (3) thickets without Clusia (TWC). The aim of this long term study was to assess soil chemistry, litterfall mass and nutrient input and its leaf-litter decomposition in Clusia thickets, testing the hypotheses that: (1) the presence of Clusia increases soil nutrient concentrations in the thickets; (2) litterfall mass and nutrient input are dependent on the senescence stage of Clusia , being higher in HCT than in SCT; (3) decomposition and nutrient release of Clusia leaves are faster in HCT than in SCT, evaluating if C. hilariana promotes an improvement in nutrient cycling according to its presence and senescence in the thickets and reinforcing the role of Clusia as a nurse plant. Collection of nutrients in soils, litterfall and Clusia leaf decomposition rates were measured between 2001 and 2008. The HCTs presented higher annual litterfall mass and nutrient input than the SCTs, Clusia leaf-fall contributed the bulk of the total litterfall (70 % HCT, 34 % SCT). Nitrogen, as all other nutrient inputs from Clusia leaf-litter, was higher in HCT, although Clusia leaves had low N concentrations and a higher C/N ratio. Clusia -leaf decomposition was faster in HCT than in SCT during the first year of the experiment. The slow decomposition and nutrient release from Clusia leaf-litter, may be an important mechanism of nutrient conservation. We concluded that C. hilariana acts as a key species, and as a nurse plant, in relation to nutritional dynamics, organic matter, nutrient input, and decomposition via its litter, which decreased according to its senescence.
Infiltration efficiency and subsurface water processes of a sustainable drainage system and consequences to flood management

With increased intensity rainfall events globally and urban expansion decreasing permeable surfaces, there is an increasing problem of urban flooding. This study aims to better understand rainfall infiltration into a Sustainable Drainage System (SuDS) permeable pavement, compared with an adjacent Green Area of made ground, in relationship to groundwater levels below both areas. Both areas were instrumented with soil water content and matric potential sensors and four shallow boreholes were instrumented with groundwater level sensors. Surface infiltration rates were measured using a double‐ring infiltrometer. Results showed that average infiltration rates of the SuDS (1,925 mm/hr) were significantly higher than the Green Area (56 mm/hr). The SuDS was well designed to transfer rainfall rapidly to the aquifer below, where groundwater levels rapidly rose within 1 hr of a 1 in 30 year event (32.8 mm/hr). In comparison, soil compaction of the made ground Green Area decreased infiltration rates, but still enabled the majority of rainfall events to infiltrate. The aquifer below the Green Area responded more slowly, as lower matrix potentials facilitated water retention in the soil profile, slowing water draining to the aquifer. This work reiterates the importance of ensuring a 1 m separation depth between the base of the SuDS infiltration zone and aquifer depth.
A Study of the Effects of Exchange Rates on the Stock Companies in the Petrochemical Industry of the Eurozone

Considering the importance of the petrochemical industry as one of the strategic sectors in the eurozone economy, this study aims to evaluate the relationship between exchange rate fluctuations and stock market prices in the eurozone petrochemical industry. This paper applies Jorion’s model and panel regression framework to monthly data spanning from 2002 to 2018. Panel regressions were estimated for three periods: the whole sample, the period before the financial crisis, and the period after the crisis. These divisions allowed for the testing of the persistence of exchange rate exposure in the petrochemical sector over time. This paper provides evidence of the magnitude of the impact of exchange rate shocks. Additionally, this paper shows that the petrochemical sector of the eurozone was exposed to significant exchange rate risk at the 1 percent level during the whole sample period and that this exposure was still present even after we split the test period into the precrisis and postcrisis datasets. However, foreign exchange rate exposure increased after the start of the financial crisis in 2008. The negative coefficient of the variable representing exposure suggests that the depreciation of the euro was followed by an increase in the stock returns of the petrochemical companies in the eurozone.
Memory-Aware Active Learning in Mobile Sensing Systems

We propose a novel active learning framework for activity recognition using wearable sensors. Our work is unique in that it takes limitations of the oracle into account when selecting sensor data for annotation by the oracle. Our approach is inspired by human-beings’ limited capacity to respond to prompts on their mobile device. This capacity constraint is manifested not only in the number of queries that a person can respond to in a given time-frame but also in the time lag between the query issuance and the oracle response. We introduce the notion of mindful active learning and propose a computational framework, called EMMA, to maximize the active learning performance taking informativeness of sensor data, query budget, and human memory into account. We formulate this optimization problem, propose an approach to model memory retention, discuss the complexity of the problem, and propose a greedy heuristic to solve the optimization problem. Additionally, we design an approach to perform mindful active learning in batch where multiple sensor observations are selected simultaneously for querying the oracle. We demonstrate the effectiveness of our approach using three publicly available activity datasets and by simulating oracles with various memory strengths. We show that the activity recognition accuracy ranges from 21 to 97 percent depending on memory strength, query budget, and difficulty of the machine learning task. Our results also indicate that EMMA achieves an accuracy level that is, on average, 13.5 percent higher than the case when only informativeness of the sensor data is considered for active learning. Moreover, we show that the performance of our approach is at most 20 percent less than the experimental upper-bound and up to 80 percent higher than the experimental lower-bound. To evaluate the performance of EMMA for batch active learning, we design two instantiations of EMMA to perform active learning in batch mode. We show that these algorithms improve the algorithm training time at the cost of a reduced accuracy in performance. Another finding in our work is that integrating clustering into the process of selecting sensor observations for batch active learning improves the activity learning performance by 11.1 percent on average, mainly due to reducing the redundancy among the selected sensor observations. We observe that mindful active learning is most beneficial when the query budget is small and/or the oracle’s memory is weak. This observation emphasizes advantages of utilizing mindful active learning strategies in mobile health settings that involve interaction with older adults and other populations with cognitive impairments.
Midwest Peregrine Falcon demography, 1982-1995

gmSTmXCT. --Peregrine Falcon (Falco peregrinus) restoration in the midwestern U.S. has resulted in a growing population estimated in 1995 to consist of 67 pairs. Dispersal from hack or natal sites has huge variation, but mean dispersal distance of females (320 km) is about twice that of males (176 km). Minimum first-year survival is 23% but actual first-year survival probably exceeds 30%. Annual survival of territorial adults is 86% (93% for females and 79% for males). Age at first breeding is usually two years although some females and a few males begin breeding at one year of age. Peregrines seem not to delay first breeding beyond two years by choice. Only a small proportion of birds fledged become breeders. Successful individuals vary greatly in productivity, which is correlated with life span. Fidelity to territory is strong, but territorial shifts do occur. Mate fidelity appears to be a by-product of territorial fidelity. The midwestern population of peregrines appears to be secure. Reproduction and survival are adequate to permit growth to current carrying capacity although 80% of the peregrines nest on manmade structures and only 20% on cliffs.
Fast ADMM-based approach for high-resolution ISAR imaging

Due to the sparse nature of inverse synthetic aperture radar (ISAR) images, sparsity-driven algorithms have been developed for high-resolution ISAR imaging. Recently, alternating direction method of multipliers (ADMMs) has been introduced for sparse signal recovery. In this Letter, based on ADMM, a fast algorithm for ISAR imaging is proposed which has lower computational complexity than that of conventional sparse representation-based methods and achieves good robustness in low-signal-to-noise ratio conditions. Experimental results based on both simulations and real data of the Yak-42 airplane show the superiority of the proposed method.
Novel fabrication technique for NiTi and TiN micro-structures by femtosecond lasers

NiTi shape memory alloy (SMA) thin films were deposited onto silicon substrate using pulsed DC magnetron sputtering technique. To obtain crystalline NiTi thin films has to be synthesized at higher temperatures (475 - 525) °C. This high temperature requirement restricts the ease in conventional lithographic procedures. The recent advancements in the laser micromachining lend their applications into the fabrication of miniaturized systems. The femtosecond lasers (FSL) allow non-thermal processing of materials by ablation. This work focuses on the deposition and fabrication of NiTi (≈1.5 μm. thick) and titanium nitride (TiN ≈0.3 μm. thick) thin films based miniaturized systems by femtosecond laser bulk micromachining. The NiTi and TiN microstructures were release by bottom silicon etch using reactive ion etching chlorine chemistry (RIE-Cl).