Miracle-dz/UniFAR-FTUs huggingface dataset:
Microscale and Mesoscale Aeolian Processes of Sandy Coastal Foredunes from Background to Extreme Conditions

Aeolian transport affects beach and foredune pre-storm morphologies, which directly contribute to storm responses. However, significant spatiotemporal variation exists within beach-dune systems regarding how biotic and abiotic factors affect topography. There are multiple metrics for quantifying topographic change, with varying pros and cons, but understanding how a system changes across spatiotemporal scales relative to varying forcings is necessary to accurately model and more effectively manage these systems. Beach and foredune micro- and mesoscale elevation changes (Δz) were quantified remotely and in situ across a mid-Atlantic coastal system. The microscale field collections consisted of 27 repeat measurements of 73 elevation pins located in vegetated, transitional, and unvegetated foredune microhabitats over three years (2015 to 2018) during seasonal, event-based, and background wind-condition collections. Unoccupied aerial System (UAS) surveys were collected to link microscale point Δz to mesoscale topographic change. Microscale measurements highlight how Δz varies more pre- to post-event than seasonally or monthly, but regardless of collection type (i.e., seasonal, monthly, or event-based), there was lower Δz in the vegetated areas than in the associated unvegetated and partially vegetated microhabitats. Despite lower Δz values per pin measurement, over the study duration, vegetated pins had a net elevation increase of ≈20 cm, whereas transitional and unvegetated microhabitats had much lower change, near-zero net gain. These results support vegetated microhabitats being more stable and having better sediment retention than unvegetated and transitional areas. Comparatively, mesoscale UAS surfaces typically overestimated Δz, such that variation stemming from vegetation across microhabitats was obscured. However, these data highlight larger mesoscale habitat impacts that cannot be determined from point measurements regarding volumetric change and feature mapping. Changes in features, such as beach access paths, that are associated with increased dynamism are quantifiable using mesoscale remote sensing methods rather than microscale methods. Regardless of the metric, maintaining baseline data is critical for assessing what is captured and missed across spatiotemporal scales and is necessary for understanding the contributors to heterogeneous topographic change in sandy coastal foredunes.
Key Encryption Method for SCADA Security Enhancement

With the growing demands of Industrial Control Systems (ICS) in all over the world, the industries such as water, electric and gas are using real time infrastructures for communication between filed devices connected within "networks such as using Local Area Network (LAN). Wide Area Networks (WAN)" or/and over internet to fulfill the requiremenets of industrial processing and automation. Supervisory Control and Data Acquisition (SCADA) system is part of ICS. This system is based on real-time processing infrastructure, systems control and design. In existing survey, several mechanisim/solutionms were developed for reliable delivery of data without any attack. Severla techniques were also implemented " such as using secure socket layer/transport layer security (SSL/TLS), secure shell (SSH) and Internet Protocol Security (IPSec)" for securing data across internet and overcoming the attacks and security because these are based on TCP/IP protocol for communication and on cryptography algorithms for the purpose of security. Based on detail SCADA security analysis, the cryptography techniques have been adopted to enhance the security of these critical systems. The proposed security solutions takes novel approach to implement the best security performance cryptography algorithms included AES, RSA and SHA-2, as a security layer within distributed network protocol (DNP3) stack. This novel approach successfully enhanced the security of DNP3 protocol as a part of SCADA system while comparing with end-to-end security implementations.
Enhancing Potential Re-Finding in Personalized Search With Hierarchical Memory Networks

The goal of personalized search is to tailor the document ranking list to meet user's individual needs. Previous studies showed users usually look for the information that has been searched before. This is called re-finding behavior which is widely explored in existing personalized search approaches. However, most existing methods for identifying re-finding behavior focus on simple lexical similarities between queries. In this paper, we propose a personalized framework based on hierarchical memory networks (MN) to enhance the identification of the potential re-finding behavior. Specifically, we explore the potential re-finding behaviors of users from two dimensions. (1) Granularity dimension. The framework carries out re-finding identification with external memories from word, sentence, and session levels. (2) Query intent dimension. Query-based re-finding and document-based re-finding are taken into account to cover user's different query intents. To enhance the interaction between different memory slots, we optimize the <inline-formula><tex-math notation="LaTeX">$READ$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>R</mml:mi><mml:mi>E</mml:mi><mml:mi>A</mml:mi><mml:mi>D</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="zhou-ieq1-3126066.gif"/></alternatives></inline-formula> operation of MN with two strategies that utilize the information in memory in a multi-hop way. Endowed with these memory networks, we can enhance user's potential re-finding behaviors and build a fine-grained user model dynamically. Experimental results on two datasets have a significant improvement over baselines, and the optimized <inline-formula><tex-math notation="LaTeX">$READ$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>R</mml:mi><mml:mi>E</mml:mi><mml:mi>A</mml:mi><mml:mi>D</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="zhou-ieq2-3126066.gif"/></alternatives></inline-formula> operation shows better performance.
PENGARUH KREATIVITAS DAN KERJASAMA TIM TERHADAP KINERJAMANAJER PADA PT. JESSLYN K CAKES INDONESIACABANG SURABAYA

The purpose of this research is to analysis team cooperation and creativity have influence to manager performance. Data that used in this research is primary data in form of quesioner with semantic differential scale. As responder is manager and assisten manager of PT. Jesslyn K. Cakes Indonesia Branch Surabaya, with sample 26 responder. While to analysis influence between team cooperation and creativity to manager performance using Technique Analysis Doubled Linear Regression. Result of analysis indicate that team cooperation and creativity have an effect to manager performance its truth, this indicated from value of R2 is 0,671 meaning that team cooperation and creativity by simultaneous can explain variation of manager performance as 67,1% and the rest equal to 32,9% explained by other variable which do not be studied at this research. And can also seen from correlation value is 0,819 showing very strong correlation between team cooperation and creativity with manager performance that is equal to 81,9 %.
An analysis of precipitation occurrences in Los Alamos, New Mexico, for long-term predictions of waste repository behavior

This study describes precipitation as an uncontrolled natural input influencing the hydrology of waste repositories in terms of their ultimate long-term closure. The general climatology of the western states, including that of New Mexico and Los Alamos, is first described. An analysis of the precipitation patterns at Los Alamos is then presented to be used for predicting long-term precipitation occurrences and shallow land burial site behavior. The waste management implications of this precipitation analysis are then discussed and future meteorological research needs are identified. 13 refs., 10 figs., 2 tabs.
Geochemical interactions between CO2, pore-waters and reservoir rocks : lessons learned from laboratory experiments, field studies and computer simulations

As is now generally accepted mankind’s burning of fossil fuels has resulted in the mass transfer of greenhouse gases, like CO2, to the atmosphere and a measurable change in the global climate. While the reduced use of fossil fuels must be our ultimate goal in order to reverse this trend, short to medium term solutions are needed which can make an impact today. Various CO2 abatement strategies have been proposed, with deep geological storage being one of the most promising. The present volume organises presentations given by leading international researchers at a NATO Advanced Research Workshop (held in Tomsk, Russia in November of 2004) on the state-of-the-art of geological storage of CO2. The book is divided into 5 parts. Part 1 provides background by describing how human activities are modifying the atmosphere in industrially-active areas in Siberia. Part 2 outlines the innovative idea of using deep permafrost layers as either impermeable boundaries below which CO2 can be injected or as a cooling source for the formation CO2 clathrates. Part 3 describes recent studies conducted on naturally occurring CO2 reservoirs, sites which have the potential to help us understand the possible long-term evolution of CO2 storage sites. Part 4 outlines various industrial-scale applications of CO2 geological storage and shows it to be technically practical, economically feasible and, to date, very safe. Finally Part 5 gives us a view of the future, showing how energy uses are predicted to change over the next 50 years and how the public must be involved in any future decisions regarding climate change abatement.
Bulk Processing of Multi-Temporal Modis Data, Statistical Analyses and Machine Learning Algorithms to Understand Climate Variables in the Indian Himalayan Region

Studies relating to trends of vegetation, snowfall and temperature in the north-western Himalayan region of India are generally focused on specific areas. Therefore, a proper understanding of regional changes in climate parameters over large time periods is generally absent, which increases the complexity of making appropriate conclusions related to climate change-induced effects in the Himalayan region. This study provides a broad overview of changes in patterns of vegetation, snow covers and temperature in Uttarakhand state of India through bulk processing of remotely sensed Moderate Resolution Imaging Spectroradiometer (MODIS) data, meteorological records and simulated global climate data. Additionally, regression using machine learning algorithms such as Support Vectors and Long Short-term Memory (LSTM) network is carried out to check the possibility of predicting these environmental variables. Results from 17 years of data show an increasing trend of snow-covered areas during pre-monsoon and decreasing vegetation covers during monsoon since 2001. Solar radiation and cloud cover largely control the lapse rate variations. Mean MODIS-derived land surface temperature (LST) observations are in close agreement with global climate data. Future studies focused on climate trends and environmental parameters in Uttarakhand could fairly rely upon the remotely sensed measurements and simulated climate data for the region.
Following performance evaluation of a mechanically coupled platoon

Coupling some trucks with the same destination is called a truck platoon system. The leading truck is driven manually and the following trucks are driven automatically by using sensors on the mechanical link. Mechanical links not only restrict the movability of the following trucks, but are also used for sensors. We evaluate the manipulability and the following performance on the linked platoon system. The relation between the measure of manipulability and the following performance is also explained. Finally, the optimized link formation is proposed in this paper.
A Jasmonate-Induced Defense Elicitation in Mature Leaves Reduces Carbon Export and Alters Sink Priority in Grape (Vitis vinifera Chardonnay)

This work aims to understand how Vitis vinifera (Chardonnay) vines prioritise the export and distribution of recently fixed photoassimilate between root tissue, fruit, and defence, following the elicitation of a defence response. Jasmonic acid (JA) and its methyl ester, MeJA, are endogenous plant hormones, known collectively as jasmonates, that have signalling roles in plant defence and consequently are often used to prime plant defence systems. Here, we use exogenous jasmonate application to mature source leaves of Chardonnay grapevines to elucidate the prioritisation strategy of carbon allocation between plant defence and growth. Our results demonstrate that jasmonate application to Chardonnay leaves can elicit a defence response to Botrytis cinerea, but the effect was localised to the jasmonate-treated area. We found no evidence of a systemic defence response in non-treated mature leaves or young growing tissue. JA application reduced the photosynthetic rate of the treated leaf and reduced the export rate of recently fixed carbon-11 from the leaf. Following JA application, a greater proportion of available recently fixed carbon was allocated to the roots, suggesting an increase in sink strength of the roots. Relative sink strength of the berries did not change; however, an increase in berry sugar was observed seven days after JA treatment. We conclude that the data provide evidence for a “high sugar resistance” model in the mature treated leaves of the vine, since the export of carbon was reduced to ensure an elevated defence response in the treated leaf. The increase in berry sugar concentration seven days after treatment can be explained by the initial prioritisation of a greater portion of the exported carbon to storage in the roots, making it available for remobilisation to the berries once the challenge to defence had passed.
On the Usability of Transformers-based Models for a French Question-Answering Task

For many tasks, state-of-the-art results have been achieved with Transformer-based architectures, resulting in a paradigmatic shift in practices from the use of task-specific architectures to the fine-tuning of pre-trained language models. The ongoing trend consists in training models with an ever-increasing amount of data and parameters, which requires considerable resources. It leads to a strong search to improve resource efficiency based on algorithmic and hardware improvements evaluated only for English. This raises questions about their usability when applied to small-scale learning problems, for which a limited amount of training data is available, especially for under-resourced languages tasks. The lack of appropriately sized corpora is a hindrance to applying data-driven and transfer learning-based approaches with strong instability cases. In this paper, we establish a state-of-the-art of the efforts dedicated to the usability of Transformer-based models and propose to evaluate these improvements on the question-answering performances of French language which have few resources. We address the instability relating to data scarcity by investigating various training strategies with data augmentation, hyperparameters optimization and cross-lingual transfer. We also introduce a new compact model for French FrALBERT which proves to be competitive in low-resource settings.
Mixture preparation in petrol engines

The aim of this work is to study the aspects of mixture preparation in petrol engines which are of interest to the mechanical engineers and researchers. The work reviewed the characteristics and behaviour of fuel and air flow in the intake manifolds of petrol engines and emphasised on investigation of fuel distribution between cylinders in a carburation engine and a multi-point injection engine. Characteristics of the flows of liquid fuel film, fuel droplets, fuel evaporation and process of mixing of fuel and air were analysed. The presence and behaviour of a large amount of liquid fuel film and fuel droplets in the intake manifolds was confirmed to be a main cause of inhomogeneity of mixture supplied to the cylinders. Atomising fuel spray and heating inlet manifolds are good methods for improving fuel evaporation and mixing of fuel and air in the intake manifolds to achieve homogeneous mixture for good operations of the engines. Fuel distribution between cylinders of a carburation engine and a multi-point injection engine was investigated, using the method of exhaust gas analysis. The results showed that in the multi-point injection engine fuel distribution between the cylinders is much better than in the carburation engine although the injection engine is equipped with a pneumatically controlled fuel injection pump (delta A/F ratio of 0.35 to 0.93 in the injection engine in contrast of delta A/F ratio of 0.76 to 1.7 in the carburation engine at normal running conditions). Injection engines equipped with an electronically controlled fuel injection system would have much better improvement in fuel distribution than the injection engine used for the present study. Heating the intake manifold in the carburation engine (by increasing coolant temperature) indicated a good improvement in fuel distribution between the cylinders while heating inlet air was not an effective way. In the injection engine, fuel distribution between the cylinders was seen to be not significantly affected by heating.
High Unawareness of Chronic Kidney Disease in Germany

Chronic kidney disease (CKD) is associated with an increased risk for cardiovascular events, hospitalizations, end stage renal disease and mortality. Main risk factors for CKD are diabetes, hypertension, and older age. Although CKD prevalence is about 10%, awareness for CKD is generally low in patients and physicians, hindering early diagnosis and treatment. We analyzed baseline data of 3305 participants with CKD Stages 1–4 from German cohorts and registries collected in 2010. Prevalence of CKD unawareness and prevalence ratios (PR) (each with 95%-confidence intervals) were estimated in categories of age, sex, CKD stages, BMI, hypertension, diabetes and other relevant comorbidities. We used a log-binomial regression model to estimate the PR for CKD unawareness for females compared to males adjusting for CKD stage and CKD risk factors. CKD unawareness was high, reaching 71% (68–73%) in CKD 3a, 49% (45–54%) in CKD 3b and still 30% (24–36%) in CKD4. Prevalence of hypertension, diabetes or cardiovascular comorbidities was not associated with lower CKD unawareness. Independent of CKD stage and other risk factors unawareness was higher in female patients (PR = 1.06 (1.01; 1.10)). Even in patients with CKD related comorbidities, CKD unawareness was high. Female sex was strongly associated with CKD unawareness. Guideline oriented treatment of patients at higher risk for CKD could increase CKD awareness. Patient–physician communication about CKD might be amendable.
A Structural Overview of Vascular Endothelial Growth Factors Pharmacological Ligands: From Macromolecules to Designed Peptidomimetics

The vascular endothelial growth factor (VEGF) family of cytokines plays a key role in vasculogenesis, angiogenesis, and lymphangiogenesis. VEGF-A is the main member of this family, alongside placental growth factor (PlGF), VEGF-B/C/D in mammals, and VEGF-E/F in other organisms. To study the activities of these growth factors under physiological and pathological conditions, resulting in therapeutic applications in cancer and age-related macular degeneration, blocking ligands have been developed. These have mostly been large biomolecules like antibodies. Ligands with high affinities, at least in the nanomolar range, and accurate structural data from X-ray crystallography and NMR spectroscopy have been described. They constitute the main focus of this overview, which evidences similarities and differences in their binding modes. For VEGF-A ligands, and to a limited extent also for PlGF, a transition is now observed towards developing smaller ligands like nanobodies and peptides. These include unnatural amino acids and chemical modifications for designed and improved properties, such as serum stability and greater affinity. However, this review also highlights the scarcity of such small molecular entities and the striking lack of small organic molecule ligands. It also shows the gap between the rather large array of ligands targeting VEGF-A and the general absence of ligands binding other VEGF members, besides some antibodies. Future developments in these directions are expected in the upcoming years, and the study of these growth factors and their promising therapeutic applications will be welcomed.
Dynamic Lidar Ratio Calculation and Aerosol Vertical Extinction Coefficient Retrieval Based on Observed Visibility

Micropulse lidar (MPL) cannot directly retrieve the aerosol extinction coefficient under cloudy conditions and at night. Therefore, we used ground visibility, Fernald’s near-end solution method, and the linear correlation between the near-end lidar signal (photons) and ground aerosol extinction coefficient (correlation coefficient = 0.98), to calculate the lidar constant and lidar ratio (LR). We compared the aerosol optical depth (AOD) retrieved from MPL and the AOD retrieved from the multifilter rotating shadowband radiometer (MFRSR-7) at the same band (532 nm). The correlation coefficient was 0.77. The vertical distribution of aerosols in daytime and nighttime during summer was obtained from lidar in July at 00:00 and 12:00 Beijing time (UTC+8). In daytime, under clear sky conditions, the distribution displayed a unimodal and peak at approximately 2000 m. The distribution at night was more complicated than that in the day, with three results. The first was monotonically decreasing from ground to upper layer, with a peak at 600 m and two peaks at approximately 1200 m. In general, the aerosol extinction coefficient at nighttime is higher than that at daytime below 1200 m. The near-ground extinction coefficient at night is higher than in the day.
SENSORY-INTEGRATION THERAPY IN THE TREATMENT OF AGGRESSIVE BEHAVIOR IN CHILDREN WITH MULTIPLE DISABILITIES

In recent years, sensory-integration therapy has emerged as one of the most popular treatments for aggressive behavior in children with different disorders. This article is devoted to an experimental study aimed at determining the effects of sensory-integration therapy on the aggressive behavior of children with multiple disabilities. Eighteen children participated in the study. The registration of the children's behavioral responses for 24 consecutive school days allowed the collection of evidence in support of the thesis in the study. The individual child’s frequency of aggressive behaviors in four domains was recording on 12 days while undergoing sensory-integrative therapy and 12 days without a treatment with sensory-integrative techniques. The following methods were used in the analysis of the results: Paired samples t-tests to test the four null hypotheses, a Shaprio-Wilk test for the assumption of normality, Cohen's d to determine the effect size attributable to the therapy, and descriptive statistics for the dependent variables. The statistical results indicated a high level of significance for the three variables: aggression towards property, physical aggression, and aggression toward self. The obtained average values for the three modules are evidence for the positive effects of the sensory-based therapy in children with emotional and behavioral problems. The fourth variable, verbal aggression did not show a statistically significant difference between the mean values before and after the sensory-based intervention.