Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of thermodynamics of the atmosphere in relation to pre-monsoon convective activity over north India

This paper explores the relationship between the vertical structure of the atmosphere and variation of deep (precipitating) convection over north India during pre-monsoon months using data for the year 2001. From the model analysis field, CAPE and other thermodynamic parameters for Kolkata, as representative of east India and Delhi, as representative of northwest India, are computed. The vertical vorticity profiles for these two stations have also been calculated. The study reveals that both for Kolkata and Delhi CAPE is poorly correlated with the rainfall amount. However, the encouraging result is that it has reasonably good skill score (bias and threat scores) to explain occurrence or non-occurrence of convective activity on the subsequent day. Time evolution of vertical structure of atmosphere indicates that nature of convective activities over Kolkata changes as the season advances. The rainfall becomes more dependent on lower tropospheric vorticity and moisture conditions become conducive for deeper convection and taller convective clouds to form with the advance of the season due to a significant increase in the lower tropospheric vorticity. This strengthening of the dynamic support to convective rainfall may be because of the pre-monsoon synoptic pattern becoming more pronounced with the progress of the season. Over Delhi, rainfall dependence on moisture is more at the beginning of the season. As for Kolkata, in this case also character of convection changes as season progresses, with increasing dependence of rainfall on lower tropospheric vorticity field. However, dynamic support is not an important initiator of convection over Delhi. The study also suggests that, the day to day drying of the atmosphere in the lower levels over Kolkata is due to subsidence of upper layer dry air while over Delhi, horizontal advection is mainly responsible for the change in moisture content of the atmosphere.
Autonomous lighting assessments in buildings: part 1 – robotic navigation and mapping

ABSTRACT Approximately 40% of all US energy usage and carbon emissions are attributed to buildings. Energy audits of buildings are an effective way to identify significant energy savings, but the extensive training required by auditors and cost of the labour intensive audits result in only a small fraction of buildings receiving an audit. Automation of the audit process using robots can offer more detailed information for better recommendations, greater consistency in analysis and recommendations, and greatly reduce the cost of audits. This paper introduces such a system and proposes navigational strategies that would be used by ground and aerial robots as they conduct automated energy audits. The strategies are divided into the interior and exterior environments. Simulations for both the interior and exterior navigational algorithms are presented, showing success in completely exploring previously unknown areas, identifying and maneuvering to objects of specific interest to energy audits, and circumnavigating open exterior perimeters of buildings.
Updated operational models for long-range forecasts of Indian summer monsoon rainfall

Based on operational 16 parameter models, the India Meteorological Department, since 1989, has been issuing the long-range forecasts for monsoon rainfall (June-September) for the country as a whole. Qualitative forecasts of category of monsoon (deficient, normal and excess) proved accurate on all the 11 years (1989-99). However, the errors in the quantitative forecasts, particularly from 1996-99 were more than the model error of ± 4 %. Therefore the operational 16-parameter models (parametric and power regression) were updated by replacing four predictors whose relationship with monsoon rainfall has weakened in recent years. The new predictors introduced into the models are Arabian Sea SST, South Indian Ocean SST, Europe Pressure Gradient and Darwin Pressure Tendency. The model constants were recalculated with the data for the period 1971-95. The performance of the updated model was found to be far better especially during the recent years. The absolute mean error of the forecasts from the updated model for the period 1991-99 was 3.2 % as against 7.0 % of the operational forecasts. As these updated models showed promise, they were introduced in 2000 for issuing the operational long-range forecasts of Indian summer monsoon rainfall.
Modeling Trust in Multiagent Mobile Vehicular Ad-Hoc Networks through Enhanced Knowledge Exchange for Effective Travel Decision Making

This thesis explores how to effectively model trust in the environment of mobile vehicular ad-hoc networks. We consider each vehicle’s travel path planning to be guided by an intelligent agent that receives traffic reports from other agents in the environment. Determining the trustworthiness of these reports is thus a critical task. We take as a starting point the multi-dimensional trust model of Minhas et al. That work had a two-phased approach: i) model trust and ii) execute an algorithm for using that trust modeling, when deciding what route to take. The framework presented in this thesis aims to clarify i) the messaging that should be supported, ii) the internal representation of the messaging and the trust information and iii) the algorithms for sending and receiving information (thus updating knowledge) in order to perform decision making during route planning. A significant contribution is therefore offered through clarification and extension of the original trust modeling approach. In addition we design a comprehensive, extensive simulation testbed that is used to validate the effectiveness and robustness of the model. This testbed supports a variety of metrics and is able to perform testing in environments with a large number of cars. This constitutes the second significant contribution of the thesis. Overall, we present a valuable model for knowledge management in mobile vehicular ad-hoc networks through a combination of trust modeling, ontological representation of concepts and facts, and a methodology for discovering and updating user models. Included is a representation and implementation of both a push-based and pull-based messaging protocol. We also demonstrate the effectiveness of this model through validation conducted using our simulation testbed, focusing first on a subset of the multi-faceted trust model in order to highlight the value of the underlying representation, decision making algorithm and simulation metrics. One very valuable result is a demonstration of the importance of the combined use of the different dimensions employed in the trust modeling.
Innovative Mechanism of Rural Finance: Risk Assessment Methods and Impact Factors of Agricultural Loans Based on Personal Emotion and Artificial Intelligence

Agricultural finance is in an embarrassing position in the current financial environment, especially during the process of COVID-19. Based on a small-scale peasant economy, it can no longer meet the rapidly rising demand of farmers for agricultural finance. Moreover, there has been a serious disconnection between the financial system of secondary and tertiary industries, and the quality of development needs to be improved urgently. The agricultural loan risk assessment has always been the main problem that we pay great attention to in the innovation of agricultural finance. Agricultural loans are an indispensable element in supporting agricultural development and promoting rural revitalization strategy. However, financial institutions have certain credit risks in reviewing and issuing agricultural loans. This article studies the speech emotion recognition of farmers in loan review to assess loan risk. As for emotional confusion caused by speech segmentation, a special method of data connection between Convolutional Neural Networks (CNNs) and Bidirectional Long Short-Term Memory (Bi-LSTM) Networks is designed, and a variable-length speech emotion recognition model including CNN and Bi-LSTM is designed. Experimental results show that the proposed algorithm can effectively improve the risk assessment of farmers in loan review.
Development of Similar Materials for Liquid-Solid Coupling and Its Application in Water Outburst and Mud Outburst Model Test of Deep Tunnel

In order to explore the evolution mechanism of water and mud inrush, based on the fluid-solid coupling similarity theory and a large number of matching tests, fault similar materials with mountain sand, gravel, and red clay as raw materials and surrounding similar rock materials with mountain sand, red clay, cement, and water as raw materials are developed. Similar materials’ physical and mechanical properties and hydraulic properties with different ratios are tested and analyzed. The results show that the red clay content influences the mechanical properties of similar materials and their hydraulic properties, and the gravel substrate mainly influences the fault permeability coefficient. Similar material can be adjusted within a certain range of mechanical parameters. The material is simple and suitable for developing similar materials for different low and medium strength rock masses. Finally, a similar material was used in a model test of the tunnel fault fracture zone to reveal the mechanism of water and mud bursts in the tunnel. The study results can be used as a reference for the development of similar materials for tunnel fracture zone surrounding rocks.
Genotype Effect as One of the Affecting Factors on The Success of Anther Culture in Eggplant (Solanum melongena L.)

Anther culture technique is one of the commonly used method in order to obtain haploid plants in eggplant. It is known that androgenic response in eggplant is variable and one of the most important factors determining success is the genotype effect. Low or insufficient embryogenic response limits the use of doubled haploid technology in breeding programs. Therefore, determining the embryogenic responses of genotypes is a step for the use of this technology in breeding studies. In this study, 61 eggplant genotypes at various breeding stages (F1, F2
Particle Filter-based Dual Estimation for Synchronous Generators

This study proposes a particle filter (PF)-based dual estimation method for tracking the dynamic states of a synchronous generator. The authors consider the situation where the field voltage measurements are not readily available. The PF is modified to treat the field voltage as an unknown input which is sequentially estimated along with the other dynamic states. To exploit the tracking results from the estimator, the authors consider the application of use the estimated field voltage to identify internal failures in the excitation subsystem. The proposed method is tested on a 10-machine, 39-bus system to assess selectivity between estimation for regular external disturbances and both physical failure, and modelling abnormality within excitation system. The presented studies show that the proposed method (i) provides reasonable tracking results for the dynamic states and the field voltage simultaneously, (ii) rapidly tracks minor excitation loss due to exciter internal failure while maintaining selectivity and (iii) is robust to measurement noise.
Fully integrated ultra low voltage cold start system for thermal energy harvesting . . .

Wireless sensor networks used in various monitoring and sensing applications rely on energy harvesting for battery-less operation, as it minimizes the need for human intervention, and offers long term monitoring solutions. Typical energy harvesters use high efficiency boost converters, which are able to step-up voltages from as low as 10 mV. However, they often need > 200 mV in order to start up initially. Current solutions for achieving a low voltage start up require the use of bulky off-chip transformers, leading to undesired area overhead. This research work presents proof-of-concept for a fully integrated start-up system, which can cold-start from < 50 mV using on-chip magnetics, and also be used as an energy harvesting charger for ultra low power applications. The use of lossy on-chip transformers in a Meissner Oscillator compared to high-quality off-chip transformers pose new design and optimization challenges. Hence, we have derived intuitive analytical expressions that are well-suited for use with the on-chip magnetics, and used them to co-optimize the oscillator components. An optimized depletion mode MOS transistor was fabricated and tested with an off-chip transformer, to exhibit oscillations from <3 mV DC input voltage. An optimized on-chip transformer, 36x smaller in area than the off-chip transformers, is currently awaiting layout and fabrication. A switched capacitor DC-DC circuit has also been designed, which can rectify and boost up the oscillator’s output voltage to 1.2 V, to have a complete start-up system for energy harvesting. Thesis Supervisor: Anantha P. Chandrakasan Title: Vannevar Bush Professor of Electrical Engineering and Computer Science
Launch fly balls for better batting statistics: Applicability of “fly-ball revolution” to Japan’s professional baseball league

ABSTRACT “Fly-ball revolution” in Major League Baseball (MLB), spotlighting an underlining tenet that batters should aim for big fly balls rather than grounders, has attracted interest from countless players around the world. Its applicability, however, is not clear for players of different physical abilities or teams with different game strategies from MLB’s. This paper aims to test a hypothesis that hitting fly balls do not result in better batting statistics than hitting grounders in Japan’s Nippon Professional Baseball (NPB). From radar-tracking outputs collected in the official games, the speed, launch angle, and batting results of all batted balls in play were extracted (n = 39,469). In-play batting average (IPBA) and slugging percentage (IPSP) were compared between fly balls and grounders. The results showed the better batting statistics for fly balls (IPBA = 0.381 ± 0.018; IPSP = 0.730 ± 0.079) than grounders (IPBA = 0.267 ± 0.010; IPSP = 0.285 ± 0.010). Thus, our hypothesis was rejected. The balls launched at 10°−20°, called line drives, resulted in higher IPBA over the typical speed range (120 − 150 km/h), suggesting that NPB players whose ball speed was typical should aim for line drives, rather than high fly balls by accepting the tenet.
Six Thinking Hats Approach to HR Analytics

Historically, the human resources (HR) function and functionaries have struggled to establish their credibility and value in the eyes of key stakeholders, including the top management and line managers. Arguably, one of the reasons for this struggle for acceptance is their inability to present data-driven, business-oriented proposals, requiring urgent attention to elevate the analytical capability of the HR function. This paper focuses on the role and significance of HR analytics to organizations through a Six Thinking Hats approach. It presents a holistic understanding of HR analytics encompassing the concept, benefits, limitations, and likely solutions.
Flow chemistry—Microreaction technology comes of age

Over the past two decades, microreaction technology has matured from early devices and concepts to encompass a wide range of commercial equipment and applications. This evolution has been aided by the confluence of microreactor development and adoption of continuous flow technology in organic chemistry. This Perspective summarizes the current state-of-the art with focus on enabling technologies for reaction and separation equipment. Automation and optimization are highlighted as promising applications of microreactor technology. The move towards continuous processing in pharmaceutical manufacturing underscores increasing industrial interest in the technology. As an example, end-to-end fabrication of pharmaceuticals in a compact reconfigurable system illustrates the development of on-demand manufacturing units based on microreactors. The final section provides an outlook for the technology, including implementation challenges and integration with computational tools. AIChE J, 2017 © 2016 American Institute of Chemical Engineers AIChE J, 63: 858–869, 2017
Redirecting Imipramine against Bluetongue Virus Infection: Insights from a Genome-wide Haploid Screening Study

Bluetongue virus (BTV), an arbovirus of ruminants, is a causative agent of numerous epidemics around the world. Due to the emergence of novel reassortant BTV strains and new outbreaks, there is an unmet need for efficacious antivirals. In this study, we used an improved haploid screening platform to identify the relevant host factors for BTV infection. Our screening tool identified and validated the host factor Niemann–Pick C1 (NPC1), a lysosomal membrane protein that is involved in lysosomal cholesterol transport, as a critical factor in BTV infection. This finding prompted us to investigate the possibility of testing imipramine, an antidepressant drug known to inhibit NPC1 function by interfering with intracellular cholesterol trafficking. In this study, we evaluated the sensitivity of BTV to imipramine using in vitro assays. Our results demonstrate that imipramine pretreatment inhibited in vitro replication and progeny release of BTV-4, BTV-8, and BTV-16. Collectively, our findings highlight the importance of NPC1 for BTV infection and recommend the reprofiling of imipramine as a potential antiviral drug against BTV.
Resting-State Neural-Activity Alterations in Subacute Aphasia after Stroke

Linguistic deficits are frequent symptoms among stroke survivors. The neural mechanism of post-stroke aphasia (PSA) was incompletely understood. Recently, resting-state functional magnetic resonance imaging (rs-fMRI) was widely used among several neuropsychological disorders. However, previous rs-fMRI studies of PSA were limited to very small sample size and the absence of reproducibility with different neuroimaging indexes. The present study performed comparisons with static and dynamic amplitude of low-frequency fluctuations (ALFF) and functional connectivity (FC) based on modest sample size (40 PSA and 37 healthy controls). Compared with controls, PSA showed significantly increased static ALFF predominantly in the bilateral supplementary motor area (SMA) and right hippocampus-parahippocampus (R HIP-ParaHip) and decreased static ALFF in right cerebellum. The increased dynamic ALFF in SMA and decreased dynamic ALFF in right cerebellum were also found in PSA. The static and dynamic ALFF in right cerebellum was positively correlated with spontaneous speech. The FC between the SMA and R HIP-ParaHip was significantly stronger in patients than controls and positively correlated with ALFF in bilateral SMA. In addition, the FC between the R HIP-ParaHip and the right temporal was also enhanced in patients and negatively correlated with repetition, naming, and comprehension score. These findings revealed consistently abnormal intrinsic neural activity in SMA and cerebellum, which may underlie linguistic deficits in PSA.
New Potential Sphalerite, Chalcopyrite, Galena and Pyrite Reference Materials for Sulfur Isotope Determination by Laser Ablation‐MC‐ICP‐MS

The sulfur isotope system is important in tracing a variety of geochemical processes. However, the availability of matrix‐matched reference materials for in situ sulfur isotope ratio measurement is limited. This study analysed four sulfide specimens to investigate their potential as reference materials for in situ sulfur isotope determination, including three natural sulfide minerals (sphalerite SPH‐1, chalcopyrite GC‐1 and galena NWU‐GN), and one resin preserved pyrite powder (RPPY). These four sulfides were analysed independently in four laboratories using both bulk and microbeam analysis techniques, all of which gave equivalent results within uncertainty with comparable accuracy and precision. The sulfur isotopes of these four sulfides are homogeneous based on a large number of isotope determinations by solution nebulisation multi‐collector inductively coupled plasma‐mass spectrometry (MC‐ICP‐MS) and laser ablation (LA) MC‐ICP‐MS. The mean δ34S values for SPH‐1, RPPY, GC‐1 and NWU‐GN determined by gas source isotope ratio mass spectrometry (GS‐IRMS) and solution nebulisation MC‐ICP‐MS are −7.13 ± 0.41‰ (2s), 3.66 ± 0.24‰ (2s), −0.65 ± 0.28‰ (2s), 28.21 ± 0.17‰ (2s) relative to the Vienna‐Canyon Diablo troilite (V‐CDT) reference value, respectively, and which are proposed as potential preferred values. Over 400 spot analyses performed on randomly selected fragments of each sulfide by LA‐MC‐ICP‐MS yielded highly consistent δ34S values with the preferred values. Thus, SPH‐1, GC‐1, NWU‐GN and RPPY are considered a set of candidate matrix‐matched sulfide reference materials for in situ sulfur isotope determination.
Design and Application of Pseudorandom Coded Sweep for Mini-SOSIE

The miniaturized, high-energy-output mini-SOSIE has become an important source in seismic exploration. It has seriously impeded resolution because of the coherent vibration frequency and periodical problem of the signal. In order to solve these problems, this paper designed a vibrator signal generator. In this paper, a pseudorandom coding technique is tested as a sweep control method for mini-SOSIE. The pseudorandom coding sequence is produced by Matlab and is of good auctocorrelation characteristic. By comparing experimental field data from sources which is controlled by pseudorandom coding method and the rammer, the pseudorandom scheme yields significant improvements, and greatly improved signal-to-noise (SNR) and resolution.
An Improved Power Quality Disturbance Detection Using Deep Learning Approach

Recently, the distribution network has been integrated with an increasing number of renewable energy sources (RESs) to create hybrid power systems. Due to the interconnection of RESs, there is an increase in power quality disturbances (PQDs). The aim of this article was to present an innovative method for detecting and classifying PQDs that combines convolutional neural networks (CNNs) and long short-term memory (LSTM). The disturbance signals are fed into a combined CNN and LSTM model, which automatically recognizes and classifies the features associated with power quality disturbances. In comparison with other methods, the proposed method overcomes the limitations associated with conventional signal analysis and feature selection. Additionally, to validate the proposed method's robustness, data samples from a modified IEEE 13-node hybrid system are collected and tested using MATLAB/Simulink. The results are good and encouraging.
Microclimatic conditions drive summer flight phenology of Platypus cylindrus in managed cork oak stands

The oak pinhole borer, Platypus cylindrus F. , mainly colonizes oaks (Quercus sp.), and it is considered among the most serious pests of cork oak (Quercus suber L.). Despite being traditionally considered as a secondary pest in thermophilic oak woodlands, outbreaks seem to be more frequent throughout the Mediterranean Basin thus becoming a growing forest health concern. In the Iberian Peninsula, this insect mainly attacks cork oaks (Q. suber) causing intense stress to mature trees specially after cork harvesting season. In this study, we investigated the summer flight phenology of P. cylindrus in six stands located in north‐eastern Spain. We recorded the number of insects trapped in pheromone‐baited traps from late April to early September of 2021, and computed sex ratio, average date of flight and season flight curve in each plot. We fitted a GAM model to evaluate how population dynamics are driven by date and climatic factors. A total of 1795 insects were collected during the sampling period. Population peaks occurred from late May to mid‐August. The fitted GAM predicted changes in the number of captures throughout the summer varying with microclimatic conditions. In addition, diversity of trapped non‐target Curculionidae resulted moderate with low evenness including either ambrosia or bark beetles. This study represents the first attempt at modelling P. cylindrus flight, thus providing insights into the association between climate, pests and forestry.