Miracle-dz/UniFAR-FTUs huggingface dataset:
Age Climate : age stereotypes in organizations and older workers

Age climate describes how favorably older employees are perceived within a given organization. It integrates research on organizational (and psychological) climates and research on age stereotypes in the workplace. The main goals of this dissertation were (1) to develop the construct of age climate and present an instrument for its measurement, (2) to investigate relationships of individual (psychological) age climate perceptions with work-related outcomes at the individual level, including interindividual differences in these relationships, and (3) to assess the consensual validity of the developed scale as well as to explore relationships of the shared organizational age climate perceptions with organizational level outcomes. Study 1 demonstrates the usefulness of the Psychological Age Climate Scale (PACS). In a sample of 302 older employees (age 40+) from 8 companies, the PACS showed a high reliability and clear single factor structure. A fixed-effects approach to clustering revealed significant associations between psychological age climate (PAC) and older employees’ organizational commitment. In Study 2, analysis of a sample of 273 older workers (age 40-63) from different occupations revealed that the perception of a less favorable age climate was related to lower work ability. This relationship was stronger at higher ages. At higher ages Selection, Optimization, and Compensation strategy use buffered the detrimental effect of an unfavorable PAC on work ability. Study 3 introduces the concept of organizational age climate (OAC), defined as employees’ shared perceptions of how favorable older workers are perceived within their organization. Analysis of data from n = 204 employees age 45+ from 8 companies confirmed the consensual validity of OAC. Moreover, companies have significantly different OACs. Analysis of a sub-sample of three companies provides first evidence that companies’ OAC is related to their personnel, knowledge, and health management practices.
A Comparison of the State-of-the-Art Reinforcement Learning Algorithms for Health-Aware Energy and Emissions Management in Zero-Emission Ships

Zero-emission ships (ZESs) have gained interest to comply with the stringent regulations of international maritime organization. One way to build ZES is the hybridization of fuel cells with batteries. Traditionally, for a newly built ship, the energy and emissions management system (EEMS) is designed based on the initial condition of the fuel cells and batteries and used with fixed parameters in future execution. However, for a fuel cell and battery ZES, the EEMS gradually becomes suboptimal since the characteristics of fuel cells and batteries are continuously changing due to aging and degradation. In this article, a reinforcement learning (RL)-based EEMS is developed such that it can learn and adapt continuously to changes in the fuel cell/battery characteristics. Within RL, different types of algorithms, such as double deep <inline-formula><tex-math notation="LaTeX">$Q$</tex-math></inline-formula>-learning (DDQL), soft actor–critic (SAC), and proximal policy optimization (PPO) are implemented. The results are benchmarked against those of a typical rule-based EEMS. Each RL algorithm is trained with four reward function formulations; negative cost (<inline-formula><tex-math notation="LaTeX">$r_{1}$</tex-math></inline-formula>), negative quadratic cost (<inline-formula><tex-math notation="LaTeX">$r_{2}$</tex-math></inline-formula>), inverse cost (<inline-formula><tex-math notation="LaTeX">$r_{3}$</tex-math></inline-formula>), and inverse quadratic cost (<inline-formula><tex-math notation="LaTeX">$r_{4}$</tex-math></inline-formula>). The results demonstrate that health-aware EEMS can minimize fuel consumption and component degradation costs. <inline-formula><tex-math notation="LaTeX">$r_{1}$</tex-math></inline-formula> has led to the lowest operational expenses (OPEX) followed by <inline-formula><tex-math notation="LaTeX">$r_{2}$</tex-math></inline-formula>, while <inline-formula><tex-math notation="LaTeX">$r_{3}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$r_{4}$</tex-math></inline-formula> have high OPEX. Among the three algorithms, the DDQL led to the lowest reward followed by the SAC and then the PPO, when trained with <inline-formula><tex-math notation="LaTeX">$r_{1}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$r_{2}$</tex-math></inline-formula>.
Assessment of rainfall efficiency in an apple orchard

: Atmospheric precipitation is the major input to the soil water balance. Its amount, intensity, and temporal distribution have an indubitable influence on soil moisture. The aim of the study (conducted in the years 2010–2013) was to evaluate soil water balance in an apple orchard as determined by daily rainfall. The amount and intensity of rainfall and daily evapotranspiration were measured using an automatic weather station. Changes in soil water content was carried out using capacitance probes placed at a depth of 20, 40 and 60 cm. The most common were single events of rainfall of up to 0.2 mm, while 1.3–3.6 mm rains delivered the greatest amount of water. A significant correlation was found between the amount of daily rainfall and changes in water content of individual soil layers. The 15–45 cm and 15–65 cm layers accumulated the greatest amount of high rainfall. The study showed a significant influence of the initial soil moisture on changes in the water content of the analysed layers of the soil profile. The lower its initial moisture content was, the more rainwater it was able to accumulate.
A major, intraplate, normal‐faulting earthquake: The 1739 Yinchuan event in northern China

A large continental normal‐faulting earthquake occurred in the Yinchuan Graben in northern China on 3 January 1739. This event is of significant interest for two reasons. First, it has been suggested on the basis of historical records of shaking that this was a magnitude 8.0 event. If this is true, the 1739 earthquake would be one of the largest continental normal‐faulting earthquakes ever recorded, and this should prompt us to consider the factors contributing to its unusual size. Second, there has been some debate in the literature about the causative structure, with at least three different faults posited as the seismogenic source. We use five 14C ages to date a series of scarps on the East Helanshan Fault, which lies to the west of the graben, and bracket the scarp formation to the last 350 years. We use high‐resolution, stereo imagery from the Pleiades satellites to build a 1 to 2 m resolution DEM of the fault and combine this with field observations to map the East Helanshan rupture in detail. We then construct a throw distribution, determine the slip vector azimuth, and reassess the earthquake magnitude using simple scaling relationships. We conclude that the 1739 earthquake occurred on the East Helanshan Fault, had a rupture length of approximately 87 km, a maximum throw of 5.1 m, and an average throw of 3.0 m, yielding a best estimate magnitude in the range Mw 7.1 to Mw 7.6. We suggest that the previous magnitude estimates are biased by enhanced shaking of the sediments within the Yinchuan Graben.
Investigation of time series-based genre popularity features for box office success prediction

Predicting the profitability of movies at the early phase of production can be helpful to support the decision to invest in movies however, due to the limited information at this stage it is a challenging task to predict the movie’s profitability. This study proposes genre popularity features using time series prediction. We argue that a movie can produce better box office returns if its genre’s popularity is high at the time of release. The novel genre popularity features are proposed in terms of budget, revenue, frequency, success, and return on investment (ROI). The proposed features couple the predicted genre popularity with release time, in order to train the machine learning classifiers. The experimentation shows that the Gradient Boosting classifier gained a significant improvement using proposed features and achieved an accuracy of more than 92.4%, i.e., 35.7% better than an existing state of the art study considering a multi-class problem.
MALT-1 shortens lifespan by inhibiting autophagy in the intestine of C. elegans

The caspase-like protease MALT1 promotes immune responses and oncogenesis in mammals by activating the transcription factor NF-κB. MALT1 is remarkably conserved from mammals to simple metazoans devoid of NF-κB homologs, like the nematode C. elegans. To discover more ancient, NF-κB -independent MALT1 functions, we analysed the phenotype of C. elegans upon silencing of MALT-1 expression systemically or in a tissue-specific manner. MALT-1 silencing in the intestine caused a significant increase in life span, whereas intestinal overexpression of MALT-1 shortened life expectancy. Interestingly, MALT-1-deficient animals showed higher constitutive levels of autophagy in the intestine, which were particularly evident in aged or starved nematodes. Silencing of the autophagy regulators ATG-13, BEC-1 or LGG-2, but not the TOR homolog LET-363, reversed lifespan extension caused by MALT-1 deficiency. These findings suggest that MALT-1 limits the lifespan of C. elegans by acting as an inhibitor of an early step of autophagy in the intestine.
Matrix black box algorithms - a survey

The implementations of matrix multiplication on contemporary, vector-oriented, and multicore-oriented computer hardware are very carefully designed and optimized with respect to their efﬁciency, due to the essential signiﬁcance of that operation in other science and engineering domains. Consequently, the available implementations are very fast and it is a natural desire to take advantage of the efﬁciency of those implementations in other problems, both matrix and nonmatrix. Such an approach is often called a black box matrix computation paradigm in the literature on the subject. In this article, we gathered a broad series of algorithms taking advantage of the efﬁciency of fast matrix multiplication algorithms in other mathematical and computer science operations.
The Blairgowrie magnetic anomaly and its interpretation using simplex optimisation

Abstract The large magnetic anomaly which runs along the Highland Boundary Fault of Scotland immediately to the NW of Blairgowrie has been studied by both a ground-based magnetic survey and a palaeomagnetic investigation. A newly developed optimisation program, making use of a simplex algorithm, was used to model the long wavelength component of this effectively two-dimensional anomaly. The consequent model consists of a vertical, rectangular body, 3 km wide and 13 km deep, whose top surface is 2 km below ground level, with a magnetisation directed vertically downwards. The composition of this body is most likely to be that of an ultra-basic, metamorphic complex which has been brought up to its present position between two of the many near-vertical faults in the area. The medium wavelength structure of the anomaly was modelled using the common technique of trial and error, and can be interpreted in terms of a pair of Devonian andesitic lavas and a small extension of the main ultrabasic block. Subsequent palaeomagnetic remanence measurements confirmed that the magnetisation of the two lavas recorded a Devonian polarity reversal. The magnetisation of the ultrabasics is directed vertically downwards, exactly as deduced from the earlier modelling work.
Application of Mamdani Fuzzy Logic Inference System to Optimise CNC Machine Motion Dynamics

The article presents the application of Mamdani Fuzzy Logic Inference System to optimize the operation of a Computerized Numerical Control (CNC) machine for given dynamic parameters. These parameters are maximum speed, acceleration and JERK. The JERK parameter determines the rate of change of acceleration. The parameters are defined for each working axis of the machine. In order to check the correctness of the solution proposed in the paper, the learning and testing process was conducted on specially designed database including different trajectories generated for machining with different machine dynamics parameters. The approach presented in the paper using elements of fuzzy logic to optimize the operation of the CNC machine proved to be very good. The authors, in cooperation with industry, will develop the aforementioned solution leading to implementations and further scientific publications.
Mg-Bentonite in the Parnaíba Paleozoic Basin, Northern Brazil

Bentonite deposits are rare in Brazil and most of their production comes from a single region. A new bentonite occurrence, the Formosa bentonite from northern Brazil, is described here. The occurrence is associated with altered Mesozoic volcanic rocks of the Parnaíba Sedimentary Basin, one of the largest continental flood basalt (CFB) provinces on Earth. The purpose of the present study was to evaluate the physical and chemical properties of a new smectite-bearing deposit in Brazil. Analysis has shown that the major mineral present in the Formosa bentonite is a dioctahedral smectite along with minor amounts of hematite, K-feldspar, and kaolinite. Quartz is absent. A Li+-saturation test (Hofmann-Klemen treatment) revealed a montmorillonite smectite; large interlayer-Mg2+ contents revealed by N2 adsorption/desorption and cation exchange capacity results suggested a Mg-bentonite. This characterization helped to explore the structure-functionality (reactivity) relationship and to develop index tests for industrial applications and the research of new materials.Use of this material as a desiccant-grade bentonite is envisaged (desiccant-grade bentonites contain Mg2+ and/or Ca2+ as the dominant exchangeable cations), or it could be activated with Na+ for use in many industrial applications (e.g. as a drilling fluid or for pelletizing iron ore). The large areal occurrence of the flood basalts suggests the possibility of very large deposits of these bentonites, a promising new exploration target for this class of industrial minerals in northern Brazil.
Comparison of Analytical Solutions to Evaluate Aquifer Response to Arbitrary Stream Stage

AbstractGroundwater table response to arbitrarily varied stream stage is a practical engineering issue related to stream-aquifer interaction processes. A one-dimensional (1D) linear Boussinesq equation is invariably used in the interpretation. Previous studies have emphasized the employment of convolution integration and pulse or function fitting methods to solve this problem. Consequently, complicated mathematical derivations and numerical calculations are involved during an analysis. In this paper, we transformed the previously published solutions into an easily solved formation to investigate this problem. Then the solution is solved based on the trapezoidal method and applied in cases. The solution fits favorably with the previous classic solutions in the simulations of groundwater table responses to sinusoidal, linear, and unit step rise varied stream stages. This approach was also applied to interpret groundwater table fluctuations induced by typical flood waves and field measured stream stage fluct.
An Adaptive Synchronous Driving Phase Control Method of GaN-Based Full-Bridge 6.78-MHz WPTS

The GaN-based active rectifiers have the potential to improve the efficiency of the several megahertz wireless power transfer system (WPTS). The full-bridge active rectifier can eliminate extra dc–dc converters for output regulation with less voltage stress than resonant rectifiers, such as Class E, Φ rectifiers. However, the lack of the synchronous phase control method is the core challenge for full-bridge active rectifier in 6.78-MHz WPTSs. Meanwhile, the increasing switching losses and reverse conduction losses of the gallium nitride high electron mobility transistors are the main constraints on the efficiency of the system. This article proposes an adaptive synchronous driving phase control (ASDPC) method of the GaN-based full-bridge rectifiers in 6.78-MHz WPTS. With the proposed method, the full-bridge rectifier can obtain the maximum output power in the critical zero voltage switching operation over a wide load range. A 50-W 6.78-MHz WPTS is built to verify the effectiveness and stability of the proposed ASDPC method. The dc–dc efficiency is improved in the wide load range of 8–50 Ω (11.8–54.57 W) and reaches 87.18% at Po = 44.9 W. Compared to the system without ASDPC, the efficiency can be improved by 5.2% at light load and 3.1% at heavy load.
Use of morphometric and phenological indicators of Betula pendula Roth for environmental health assessment

The article presents the results of long-term biomonitoring of the quality of the environmental of the city of Yoshkar-Ola (Russia) based on the analysis of morphological and phenological indicators of Betula pendula Roth. The authors studied Betula pendula trees at various stages of ontogenesis in the generative period. The authors also found out the heterogeneity of ontogenetic groups of trees by morphological and phenological characteristics in different ecotopes of the city, differing in the degree of pollution by industrial and transport emissions, using principal component analysis A decrease in the morphometric parameters of the Betula pendula leaf blade and leaf damage by phyllophagous insects do not always indicate a deterioration in the quality of the habitat. Moderate doses of atmospheric toxicants can accelerate the growth of B. pendula leaves. However, in conditions of urban pollution, the stability of B. pendula development is disrupted, which is manifested in an increase in the leaf asymmetry index. There are the most informative indicators of the state of the environment in individuals B. pendula: morphometric – an indicator of fluctuating asymmetry of leaves, phenological – the timing and duration of phenophases. The young generative trees of B. pendula are most sensitive to habitat pollution.
A Prospective Cohort Study of Inter-Alpha-Trypsin Inhibitor Heavy Chain 4 as a Serologic Marker in Relation to Severity and Functional Outcome of Acute Intracerebral Hemorrhage

Background The inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4) may regulate immunity and inflammation. The current study was conducted to determine its role as a biomarker for reflecting the severity and predicting outcomes of intracerebral hemorrhage (ICH). Methods In this prospective cohort study, 185 patients with supratentorial ICH were enrolled, among whom 62 had blood obtained not only at admission but also on days 1, 3, 5, 7, 10, and 14. In addition, 62 healthy controls underwent blood collection at the start of the study. The serum ITIH4 levels were then quantified. We recorded early neurological deterioration (END) and poor prognosis (modified Rankin Scale [mRS] scores of 3–6]) six months after ICH. Results Serum ITIH4 levels decreased prominently in the early phase after ICH, continued to decline until day 5, then gradually increased until day 14, and were significantly lower during 14 days in patients than in controls. Serum ITIH4 levels on admission were independently associated with serum C-reactive protein levels, National Institutes of Health Stroke Scale (NIHSS) scores and hematoma volume. Admission serum ITIH4 levels were independently associated with mRS scores, END, and poor prognosis. No substantial differences existed in the areas under the receiver operating characteristic curve of END and poor prognosis prediction between the serum ITIH4 levels, NIHSS scores, and hematoma volume. Prediction models, in which serum ITIH4 levels, NIHSS scores, and hematoma volume were integrated, were relatively reliable and stable using a series of statistical methods. In addition, the prediction model of poor prognosis had a higher discriminatory ability than the NIHSS scores and hematoma volume alone. Conclusion A dramatic decline in serum ITIH4 levels during the early period following ICH is independently related to the inflammatory response, stroke severity, and poor neurologic outcomes, suggesting that serum ITIH4 may be a useful prognostic biomarker of ICH.
Occurrence, Abundance, and Length Frequency Distribution of Queen Conch, Strombus gigas (Gastropoda) in Shallow Waters of the Jaragua National Park, Dominican Republic.

A BSTRACT . —The distribution of juvenile queen conch has been associated with certain ecologically unique characteristics within seagrass beds, such as strong tidal circulation patterns, depth of 2 to 4 m, and seagrass beds with intermediate biomass. Knowledge of the location of nursery grounds is important to guarantee their protection for fisheries management or stock enhancement programs. Jaragua National Park is located in the Southwest portion of the Dominican Republic and supports an important artisanal fishery for lobsters, queen conch, and fishes. To provide precise information on juvenile queen conch distribution in the shallow waters of the Jaragua National Park, 34 sites (stations) were visited during the months of March and June-July, 1997. Data were collected on conch abundance, length, age, habitat type and depth (to a maximum of 20 m). For conch density and abundance estimations, the area was divided into five regions (Canal de Beata, Bucan de Tui, El Cuevon, Bahia de Las Aguilas, Cabo Rojo). Most of the conch found were juveniles (88.9%). Canal de Beata had the highest density of juveniles (114.2 conchs/ha) and abundance (658,707 conchs), while Bucan de Tui had the lowest density (4.0 conchs/ha) and Cabo Rojo had the lowest abundance (14,343 conchs). The overall estimates of juvenile density and abundance was 53.0 conchs/ha and 1,076,169 conchs, respectively. Juveniles ranged from 5 to 26 cm in length (mean: 14 cm). Juvenile density was highest on mixed seagrass beds (73.9 conchs/ha) and below 7 m depth (73.7 conchs/ha). Adult density at these depths was 4.6 conchs/ha. Canal de Beata is a suitable nursery ground and should be protected.
Development reference model to build management reporter using dynamics great plain aggregated

The digital technology transformation impacts changes in business patterns that require companies to innovate to act appropriately in making strategic decisions quickly, precisely, and accurately to increase efficiency, be practical company performance, and impacts changes in business patterns that require companies to innovate to act appropriately in making strategic decisions quickly to improve the performance. An enterprise resource planning (ERP) system is one step toward achieving performance. ERP system is one step to achieving performance. ERP system is essential for companies to automate the efficiency of business processes. The decisions from management in implementing the ERP system are necessary for ERP implementation to be successful. However, in practice, companies still experience complexity. For that, it needs to be considered related a business process reference model is essential to enhance efficiency in implementing the ERP used. This research discusses the business process reference model based on the ERP dynamics great plain (GP) application aggregated using management reporter (MR) to help users better understand the practical overview. The methodology utilizes a reference model based on Microsoft Dynamics GP guidelines with a business process redesign approach. This contributes to developing business processes to help users understand using the ERP dynamics GP application.