Miracle-dz/UniFAR-FTUs huggingface dataset:
Scattering of SH waves induced by a non-symmetrical V-shaped canyon

SUMMARY Topographies have significant effects on seismic waves. The wavefunction expansion method has been frequently employed to study the topographic effect because this method can reveal the physics of the wave scattering and can testify the accuracy of numerical methods. The 2-D scattering and diffraction of plane SH waves induced by a non-symmetrical V-shaped canyon is examined here by using the wavefunction expansion method. Through a new domain decomposition strategy, the half-space containing a V-shaped canyon is divided into three subregions. Then the wavefield for every subregion is constructed in terms of an infinite series of wavefunctions with unknown coefficients in three coordinate systems, respectively. After that, three wavefields are all represented in the same coordinate system using the Graf addition theorem. The unknown coefficients are obtained by satisfying the continuity conditions of the auxiliary boundary. The proposed series solution of wavefunctions for a non-symmetrical V-shaped canyon can be reduced to a symmetrical case. Results in this study for the symmetrical case agree very well with those in the published literature. To show the effects of the non-symmetrical-geometry topography on the surface ground motion, a parametric study is carried out in the frequency domain. Surface and subsurface transient responses in the time domain demonstrate the phenomenon of wave propagating and scattering. Finally, the proposed model is successfully applied to two idealized cross sections of Pacoima canyon and Feitsui canyon.
Spatial-temporal variation of low-frequency earthquake bursts near Parkfield, California

Tectonic tremor (TT) and low-frequency earthquakes (LFEs) have been found in the deeper crust of various tectonic environments globally in the last decade. The spatial-temporal behaviour of LFEs provides insight into deep fault zone processes. In this study, we examine recurrence times from a 12-yr catalogue of 88 LFE families with ∼ 730 000 LFEs in the vicin-ity of the Parkﬁeld section of the San Andreas Fault (SAF) in central California. We apply an automatic burst detection algorithm to the LFE recurrence times to identify the clustering behaviour of LFEs (LFE bursts) in each family. We ﬁnd that the burst behaviours in the northern and southern LFE groups differ. Generally, the northern group has longer burst duration but fewer LFEs per burst, while the southern group has shorter burst duration but more LFEs per burst. The southern group LFE bursts are generally more correlated than the northern group, suggesting more coherent deep fault slip and relatively simpler deep fault structure beneath the locked section of SAF. We also found that the 2004 Parkﬁeld earthquake clearly increased the number of LFEs per burst and average burst duration for both the northern and the southern groups, with a relatively larger effect on the northern group. This could be due to the weakness of northern part of the fault, or the northwesterly rupture direction of the Parkﬁeld earthquake.
Analysis of Factors Affecting Accounting Information System Performance in Banking Sector

Accounting information systems is very important in the institution to support the growth performance of the institution, therefore it is necessary also an accounting information system supported by computerized information technology. This study to determine whether user involvement, personal technical ability, training and education programs, top management support, and system development formalization affect the accounting information system performance at banking company. The sample used in this study was obtained from the respondents which is employee of private national bank who used accounting information system in work. The analysis technique used is ordinary least square, multiple linear regression analysis. The results showed that user involvement, personal technical ability, training and education programs, top management support, and system development formalization have a significant effect on accounting information system performance.
The Impact of Interface Quality and Security/Privacy on Shoppers’ E-Loyalty: The Mediating Role of Flow

In the era of digitalization and the development of mobile applications, consumers can shop easily through marketplace applications anywhere and anytime. Following the rapid growth of e-marketplaces, particularly in Indonesia, this study determines the role of digital stimuli, namely: Interface Quality and Security/Privacy, on consumer loyalty to marketplaces, as well as the mediating role of Flow in these relationships. Data collection was done using the purposive sampling method for marketplace application users in Indonesia, and as many as 305 respondents were analyzed by the Second-Order Model using the SmartPLS 3.3. 3. This study found that Interface Quality affects E-Loyalty, directly or through Flow’s mediating role. In addition, the Security/Privacy of the marketplace application also affects E-Loyalty through Flow.
Door Detection and Distance Estimation in Habitat Simulator for 3D Environments

Doors play a pivotal role in navigation and interaction within 3D environments, whether in robotics, gaming, or architectural simulations. Accurate door detection and distance estimation are crucial for enhancing spatial awareness and enabling efficient path planning. In this research, we present a comprehensive approach to door detection and distance estimation within the Habitat simulator. Our methodology leverages the YOLOv8 deep learning model to detect doors and utilizes depth maps for precise distance estimation. We address the challenge of distinguishing between open and closed doors and demonstrate the effectiveness of our approach through a systematic evaluation. The results showcase a remarkable capability in detecting doors with high accuracy, providing valuable insights for spatial understanding and robotic navigation. With an achieved F1-score of 96.53% in our experiments, this work significantly contributes to the field of door detection and distance estimation for 3D environments, with potential applications in various domains, including robotics, virtual reality, and architectural simulations.
Relationships among hydrogeomorphic processes and the distribution, age and stand characteristics of woody species in Great Basin upland riparian areas

Riparian ecosystems often constitute less than one percent of the central Great Basin landscape but provide critical ecosystem services. Shrubs and trees are fundamental components of these riparian ecosystems that can provide stabilization of sediment and resistance to stream down-cutting. This can promotes ground-water recharge and maintenance of elevated water tables. Fluvial processes shape landforms and riparian woody species distribution across those fluvial landforms. In the arid to semi-arid west, riparian woody species are distributed along vertical elevation gradients within stream reaches (i.e., height above and distance from the channel) and along longitudinal elevation gradients within watersheds (i.e., contributing area and local bedrock) according to their life history and ecophysiological traits. Thus, knowledge of the hydrogeomorphic context at both watershed and stream reach scales is essential for understanding woody species establishment and persistence in riparian ecosystems. This study was located in the central Great Basin across four study watersheds characterized by small watershed size, low relief, and narrow valley floors. Streams were relatively high stream gradient, channel bed material was coarse to fine-grained and bedrock geology varied among watersheds. The study examined the influences of hydrogeomorphic setting and flood disturbance on the distribution, age and stand characteristics of four “key” woody riparian species (Betula occidentalis, Salix exigua, Salix lutea, and Populus tremuloides) with different ecological amplitudes and life history characteristics. Three questions were addressed: (1) How do hydrogeomorphic factors affect the spatial patterning of riparian woody species with different ecological amplitudes and life history traits ? (2) How do the hydrogeomorphic setting and flood events affect establishment of woody species with different ecological amplitudes and life history traits ? (3) How does the hydrogeomorphic setting affect the stand structure of woody species with different ecological amplitudes and life history traits ? Geomorphic data were sampled along stream cross-sections and included all inset terraces and
Trend and uncertainty in spatial‐temporal patterns of hydrological droughts in the Amazon basin

Spatial‐temporal patterns of hydrological droughts in the Amazon basin are derived from drought indices computed from existing streamflow data. Principal component analysis and Monte Carlo simulations are employed to account for the uncertainty and overcome the limitations of missing data in streamflow records. Results show that northern and southern subbasins differ in drought trends and in patterns of correlation between drought indices and climate anomalies originating from the Pacific (El Niño–Southern Oscillation) and Atlantic (differences in sea surface temperature across the equator) Oceans. A significant trend toward more intense droughts is found in the southern subbasins, which is highly correlated to tropical Atlantic Ocean sea surface temperature anomalies. That drying trend might have distinct causes in each subbasin and can lead to potential intensification of regional impacts.
TReLU: A Novel Activation Function for Modern Day Intrusion Detection System Using Deep Neural Networks

The security of computer networks is of paramount importance in today’s digital age, where network intrusion attempts are becoming more sophisticated and frequent. Intrusion detection systems (IDS) which were established long ago are used extensively in the industry but are also limited in their ability to detect modern intrusion techniques that are often obfuscated and hidden in network traffic. As a result, there is a growing need for advanced techniques in network security that can effectively identify and mitigate such attacks.This study proposes a novel activation function TReLU, which is implemented with a hybrid model of CNN and BiLSTM. This function edges out the currently used activation functions for this use case. Additionally, to reduce the training time, parallel programming in Python is leveraged to accelerate the computation of the model. We have used three benchmark IDS datasets to evaluate our proposed model with TReLU. Compared to the previous works of other authors, the experimental results depict that our model outperforms or slightly edges them and various other state of the art models.
Hydrologic and Environmental Impacts of Imperviousness in an Industrial Catchment of Northern Italy

AbstractThe increase of imperviousness due to urbanization creates adverse effects on the hydrological and environmental processes in a catchment. The increase in impervious areas leads to a higher runoff peak flow and stormwater pollution, even for a short duration of low-intensity rainfall. The present study focuses on the Bivio Vela catchment, an urban catchment of Pavia in northern Italy. This paper emphasizes both experimental and modeling approaches to the rainfall-runoff process and pollutant dynamics on the catchment surface and in the combined sewer system, considering significant increases in impervious area. Recent and future catchment developments caused the conversion of approximately 33% of the total area from nonurban pervious area to impervious area. The study also deals with the performance assessment of the wet-weather control system of the catchment, introducing simple indicators that account for the requirements of the urban drainage system and treatment plant. Imperviousness associate.
Spatial Distribution Patterns and the Evolution Process of Carbon Storage in a Typical Karst Canyon Area

Abstract: Qinglong County in Guizhou, China is a typical karst canyon area. Using quadrat methods and a land use transfer matrix we studied the carbon storage spatial distribution pattern and evolution process over three independent periods (1988, 1999 and 2009) in this area. Based on the results we estimated the carbon pool capacity of the entire karst canyon area in Guizhou and contribution ratios. Carbon storage and average carbon density of the karst area in Qinglong decreased at first, and then increased over the sampling period. The actual carbon storage of the karst canyon area in Guizhou was estimated to be 42.55 Tg. The average carbon intensity of the karst canyon area in Guizhou is far higher than that of national terrestrial ecosystems, especially in vegetation areas. Through cross comparison, we found that karst canyon areas have great carbon sequestration potential and we suggest that it is necessary to control and prevent rocky desertification in karst areas in China.
Thermal Behavior of Crystalline Silicon Bottom Cell in a Monolithic Perovskite/Si Tandem Solar Cells

Monolithic Perovskite/Si tandem solar cells represent a promising direction in photovoltaic technology. However, understanding the temperature coefficient is essential for predicting performance and improving the temperature adaptability of these devices under varying weather conditions. This paper conducts a detailed analysis of the thermal behavior of c-Si as a bottom cell in a monolithic Perovskite/Si tandem arrangement, exploring how its behavior differs from standalone configurations. This investigation is carried out through a numerical simulation using SCAPS software. The simulation considers the temperature-dependent bandgap and absorption for both c-Si and perovskite, as well as the temperature effects on series and shunt resistances. Four simulation scenarios were analyzed, 1) as a standalone c-Si solar cell, 2) c-Si bottom cell in perovskite/Si tandem structure with spectrum split at the perovskite bandgap, 3) c-Si bottom cell, considering perovskite temperature-dependent bandgap, and 4) c-Si bottom cell, considering perovskite layer thickness, absorption and its temperature-dependent bandgap. The results reveal that c-Si solar cells in tandem structures experience notable differences in temperature coefficients, especially in the short-circuit and MPP current densities, compared to standalone configurations. This difference is mainly attributed to the spectrum splitting and temperature-dependent perovskite absorption. Splitting the spectrum leads to an increase in the temperature coefficient of JSC from 0.0944% °C−1 to 0.2539% °C−1; this temperature coefficient reached 0.983% °C−1 when the top cell layer thickness and perovskite's temperature-dependent bandgap and absorption were incorporated into the analysis. Nevertheless, only a minor variation was observed in the voltage temperature coefficient, for both in standalone c-Si cells and those incorporated as bottom cells in the tandem structure.
INCREASING FRUIT QUALITY OF PEACHES AND NECTARINES: THE MAIN GOALS OF ISF-FO (ITALY)

In 1980, the Forli branch of the Istituto Sperimentale per la Frutticoltura started a breeding program with the precise aim of improving fruit quality in peach. The main objectives pursued and the results obtained were: a) to join the excellent flavor of the traditional white-fleshed Italian varieties with the good commercial characteristics of cultivars from USA. 'Alba', 'Bea', 'Neve' and 'Crizia' have been already released, and several promising selections are under advanced evaluation. Though of high quality standard, the selected material does not match the high flesh firmness with the good flavor of the old Italian varieties, presumably because flesh firmness plays a role in determining the fruit flavor; b) to introduce the "stony hard" character in genotypes that meet high horticultural standard and have melting flesh fruits. Up to now, the best result obtained is the selection IFF 331 that, together with the "stony hard" trait, has very good fruit color and size; c) to increase ascorbic acid (Vitamin C) content, which is generally poor in peach fruit. We started with a few genotypes characterized by relatively high ascorbic acid content and good flavor. In the progeny derived from the first crosses, a wide range of variability was found for color, fruit size and Vitamin C content; d) to obtain early ripening peach and nectarine cultivars with stones that are small and unsusceptible to split-pit. At the moment, few of the seedlings exhibited the desired characteristics. Moreover, all the F(2) nectarines were sensitive to skin cracking and surface speckling.
The phytoplankton ecology of the Firth of Clyde sea-lochs Striven and Fyne

Lochs Fyne and Striven are deep-silled fjords opening into the northern Firth of Clyde. They receive relatively little freshwater from local runoff, have a relatively low rate of tidal exchange, and undergo periods of deep water stagnation. Both contain fish farms which have lost stock because of phytoplankton blooms. Loch Striven was investigated in detail in 1980. Observations are also reported for 1979 and 1981, and for Loch Fyne from 1980–1982. Most stratification in Striven is due to salinity layering, but most of the freshwater in the loch probably originates in the Clyde Estuary and is associated with high concentrations of nitrate. Typical phytoplankton biomasses in Striven are the same as those in the western seaboard Loch Creran, but maxima exceed those in Creran. In addition to a red tide of Gyrodinium aureolum in September, 1980, three periods of high biomass seem to be a regular feature of the phytoplankton calendar in Striven. The spring increase takes place in March or early April, is dominated by the diatom Skeletonema costalum, and probably depends on the stabilizing effects of reduced near-surface salinities. A summer flourishing of Leptocylindrus danicus and dinoflagellates is also associated with near-surface salinity layering. A late spring bloom of diatoms, dinoflagellates and small flagellates, some ichthyotoxic, appears to be related to the occurrence of thermohaline stratification and near-surface nutrient depletion; on some occasions lochhead upwelling may also have been involved. Insofar as data are available, the ecology of phytoplankton in Loch Fyne appears similar to that in Loch Striven.
Prediction of Higher Education Students Academic Success Levels Based on Personality Traits

The academic success of students takes in a crucial part in academic institutions since it is a factor measure to identify the performance of an institution. Timely identification of students' CGPA range can reduce concerns about students’ academic life and it will help to improve the success and avoid the risks. The usage of machine learning techniques for prediction purposes has increased recently. In this paper, we focus the study on big five personality model used for determining the behavior of a person and where an individual will lie on the range for each of the five traits; using machine learning techniques to estimate a student's degree of academic accomplishment. In this work, Decision Tree Classifier, Random Forest Classifier, Naive Bayes Classifier, and Support Vector Classifier (SVC) have been used as machine learning techniques. The results were obtained at a recognition rate for accuracy of 90.2% by the Decision Tree Classification algorithm.
Application of Machine Learning and Deep Learning Algorithms in Predicting Virtual Network Functions for Network Function Virtualization

Network functions virtualization (NFV) is a methodology that replaces hardware middleboxes with more flexible software alternatives called virtualized network functions (VNFs). These VNFs need to be created and their resource allocation needs to be changed as per traffic demands to dynamically adapt to changes. However, determining the appropriate number of resources to be allotted for each VNF instance is challenging, as fixed resource consumption is often assumed in existing optimization methods. This can lead to either resource wastage or poor service quality. A novel machine learning algorithm trained on actual VNF data, which includes performance measures and resource needs is proposed to address this issue. These trained models can accurately predict the number of resources needed for each VNF to handle a specific traffic load. These machine learning models are incorporated into an algorithm for simultaneous VNF placement and scaling, and their effect on the final VNF placements is evaluated.
Contribution of Aerosol Species to the 2019 Smoke Episodes over the East Coast of Peninsular Malaysia

Large-scale biomass burning (BB) emits large amounts of aerosols that lead to transboundary smoke events and adversely impacts human health, whilst causing societal and environmental issues. High ambient PM 2.5 concentration in the year 2019 based on New Malaysia Ambient Air Quality Standard (NMAAQS) was identified as high pollution episodes, HP1 and HP2 on the east coast Peninsular Malaysia (ECPM). Meanwhile, the low PM 2.5 concentration episodes are known as LP1 and LP2. The transboundary smoke events in Indochina and Indonesia are linked to HP1 (March–April) and HP2(August–September), respectively from backward trajectory and MERRA-2 model re-analyses weather data. The correlation analysis showed a significantly strong positive correlation (r) of black carbon (HP1: 0.91; HP2: 0.96), organic carbon (HP1: 0.90; HP2: 0.94), and sulphate (HP1: 0.80; HP2: 0.61) with the aerosol optical depth (AOD) levels during high pollution episodes. The synoptic weather condition and inter-monsoon in HP1 and southwest monsoon in HP2 introduce strong wind speed and favourable wind pattern that can initiate the long-range transport of high AOD and PM 2.5 to the ECPM region. In conclusion, this study demystified the sources of BB emissions, the transport route of transboundary smoke events, their influence factors during different high pollution periods, and the links between aerosol species from local and non-local emissions with AOD levels and PM 2.5 concentrations along the ECPM, which altogether provide crucial information on climate variability signal and can help in developing a corresponding strategy for high pollution episodes.
Relationship between the severity of acute pancreatitis and vitamin D level in geriatric patient population

Aim: It is important to determine the severity of acute pancreatitis (AP) and its prognosis.The aim of this study is to research the efficiency of vitamin D level on the severity of acute pancreatitis in geriatric population. Material and Methods: Files of 4108 patients were analyzed retrospectively. Serum vitamin D levels of total 404 patients (geriatric 160 (n:160); non-geriatric 244 (n:244)) were compared between mild, moderate and severe groups according to revised Atlanta classification for acute pancreatitis. Relationship between the severity of acute pancreatitis and vitamin D levels were analyzed. Results: No significant difference was observed in non-geriatric patients in terms of vitamin D levels according to the Atlanta classification for acute pancreatitis. However, there were significant differences both between mild and moderate groups and between moderate and severe groups in geriatric patients (p<0.005). AP was more severe in patients with a low vitamin D level (p<0.005). Conclusion: We have concluded that vitamin D levels may be insufficient to predict the severity of acute pancreatitis considering age factor, which is a substantial indicator of its prognosis. Vitamin D levels have been found out to be efficient in the severity of disease in geriatric acute pancreatitis patients compared to non-geriatric ones.