Miracle-dz/UniFAR-FTUs huggingface dataset:
Tutorial: The gravity-stripping process as applied to gravity interpretation in the eastern Mediterranean

Observed gravity data after latitude, elevation (free air), Bouguer and terrain corrections determine “the sum of all effects from the grass roots down” (Nettleton, 1971). In order to eliminate gravity effects corresponding to unwanted disturbances in the subsurface, various approaches can be used. One such approach that has proven the test of time is gravity interpretation by stripping (e.g., Woollard, 1938; Bible, 1961; Hammer, 1963). The removal of an effect of a known density contrast (i.e., constrained by independent geophysical and geological data) allows determination of gravity corresponding to other targets of interest. It is well known that the advantage of the gravity-stripping procedure is that it is more accurate than any mathematical (convolution) method for separation of the gravity field (including filtering procedures), as the latter contain not only information on the amplification of available gravity components, but also false anomalies. Moreover, all transformed (filtered) gravity sig.
Automatic Adjustment of the Visual Navigation System Based on the Results of Bench Tests

Current work is devoted to the development of a method for automatic adjustment of the visual navigation system based on the results of bench tests. The necessity of using visual navigation system as a part of the navigation complex of an unmanned aerial vehicle is shown. The features of VNS tunning are determined. The parameters of VNS that need to be configured are determined. It is shown that is expedient to use a simulation stand to adjust the VNS parameters. There are main criteria for evaluating performance and quality of VNS tunning and it is determined. An automatic system for adjusting the VNS parameters by using simulation stand has been developed, which includes the following modules: global parameters module, movement of the unmanned aerial vehicle physical model and determination the traveled distance module, a module for controlling the payload and gyro stabilization, a module for processing local landmarks on the resulting image, a module determining global positioning system coordinates, a module for assessing the accuracy of the system, module for setting system operation algorithms, local parameters.
LiDAR Augmented Optimal Path Planning for Unmanned Aerial Vehicle during Remote Sensing at Low Altitude and Network Sensor Data Acquisition

This technical report describes a Light Detection and Ranging (LiDAR) augmented optimal path planning at low level flight methodology for remote sensing and sampling Unmanned Aerial Vehicles (UAV). The UAV is used to perform remote air sampling and data acquisition from a network of sensors on the ground. The data that contains information on the terrain is in the form of a 3D point clouds maps is processed by the algorithms to find an optimal path. The results show that the method and algorithm are able to use the LiDAR data to avoid obstacles when planning a path from a start to a target point. The report compares the performance of the method as the resolution of the LIDAR map is increased and when a Digital Elevation Model (DEM) is included. From a practical point of view, the optimal path plan is loaded and works seemingly with the UAV ground station and also shows the UAV ground station software augmented with more accurate LIDAR data.
Exploring the Vulnerability of Implementing DDoS Detection Systems based on Random-Forest Classifiers and Open Datasets

DDoS attacks are threats to governments and IT industries as they can render important computing servers and networks inaccessible. Random forest classifiers are efficient and effective in detecting DDoS attacks when they are used with a large number of training samples to build up an accurate model. However, it is extremely difficult for IT professionals to construct a DDoS training dataset because a realistic DDoS attack scheme is characterized by a large swarm of geographically dispersed computers simultaneously flooding the victim server with superfluous requests. To overcome this difficulty, most of the existing DDoS-detection studies use open datasets to train their random-forest model. While the aforementioned methodology provides a convenient way to conduct academic research, it may not be safe in practice. Thus, we explored the vulnerability of implementing DDoS detection systems based on random-forest classifiers and open datasets. Using a publicly accessible machine-learning library named Scikit-learn and an open DDoS dataset named CIC-DDoS2019, we implemented random-forest-based DDoS detection for a security risk assessment.
PERFORMANCE EVALUATION OF SUB-SURFACE FLOW CONSTRUCTED WETLAND SYSTEMS UNDER VARIABLE HYDRAULIC LOADING RATES

Wastewater treatment has given an immense attention in the field of pollution control throughout the world. This has become a challenge in developing countries due to the limitations of resources and expertise. Constructed wetlands where water, plants and microorganisms interact to improve the quality of water have been proven to be an effective low-cost wastewater treatment technology in many parts of the world, which does not necessarily require skilled personnel to run the system. However, these systems are not yet widely spread in developing countries due to lack of information. Constructed wetlands can be designed as surface flow or subsurface flow systems, depending on the level of the water column. This study compares the performance of vertical subsurface flow (VSSF) and horizontal subsurface flow (HSSF) constructed wetland systems at laboratory scale at tropical condition. This paper also evaluates the effects of Hydraulic Loading Rate (HLR) on treatment capacity of wastewater parameters such as Five day Biochemical Oxygen Demand (BOD5), Total Suspended Solids (TSS), Nitrate Nitrogen (NO3 — N), Phosphate (PO4 3- ), Ammonia Nitrogen (NH4-N ), Fecal Coliforms (FC) and Total Coliforms (TC).
Effects of Visual Presentation Near the Mouth on Cross-Modal Effects of Multisensory Flavor Perception and Ease of Eating

Various studies have suggested that altering the appearance of food can impact multisensory flavor perception. The cross-modal effect of such visual changes on gustation may allow for the presentation of food tastes that are difficult to express with simple combinations of taste stimuli. This cross-modal effect of visual changes on gustation holds potential for applications in gustatory displays. However, the current limitation of existing Head-Mounted Displays (HMDs) is their restricted vertical Field of View (FoV), which prohibits the display of images near the mouth while eating. This limitation may impede the cross-modal effect of visual changes on multisensory flavor perception. Additionally, the lack of visibility around the mouth area challenges the ease of eating. To address these issues, we design a Video See-Through (VST)-HMD with an expanded vertical FoV (approx. 100 [deg]). Using the HMD, we investigated how presenting visual information near the mouth affects the cross-modal effects of flavor perception and ease of eating. In our experiment, machine learning techniques were utilized to alter the appearance of food. However, the result showed no significant differences in the amount of cross-modal effects or the ease of eating between the groups with and without visual information near the mouth. As a discussion of this result, the participants may not direct their visual attention to the food when they put the food in their mouths. The experiment also examined whether visual changes alter the taste as well as the smell and texture of the food. The findings demonstrated that visual changes could present the smell and texture of the food following the modifications. This result was confirmed irrespective of the visibility near the mouth.
Harambee: Reinforcing African voices through collaborative processes and technologies.

In the course of their various activities, the Harambee Project proponents recognized that processes supporting collaboration and partnership are critical to enhancing the participation of Africans in their own development. There is both an immediate and strong need in Africa for capacity development in the design of processes that assist in the creation, use and sharing of knowledge, and in the use of ICTs to support such engagement. Harambee assists its proponents and partners in supporting specific networks and communities in Africa by increasing their respective capacities to facilitate and coordinate such groups. Through the implementation of focus network pilot activities, provision of channels for knowledge sharing, a small grant facility and the development of research and training materials, Harambee is increasing the capacity of network coordinators and ultimately the effectiveness of the networks themselves. This case study provides a brief background of Harambee and presents its approach to development through strengthening networks. It also presents some of the key lessons learned as well as what it sees as the major challenges that lie ahead.
Lactoferrin facilitates potential glucose regulation accompanied by the enhancement of 3 incretin effect

1 2 Lactoferrin facilitates potential glucose regulation accompanied by the enhancement of 3 incretin effect. 4 5 Yuta Maekawa, Akihiko Sugiyama and Takashi Takeuchi* 6 Department of Veterinary Medicine, Tottori University, 4-101 Koyama-Minami, Tottori 680-8553, Japan. 7 8 Addresses: 9 Yuta Maekawa, 10 Department of Veterinary Medicine, Tottori University, 4-101 Koyama-Minami, Tottori 680-8553, Japan. 11 Phone & Fax: +81-857-31-5645 12 e-mail: t011tm@yamaguchi-u.ac. jp 13 14 Akihiko Sugiyama, 15 Department of Veterinary Medicine, Tottori University, 4-101 Koyama-Minami, Tottori 680-8553, Japan. 16 Phone & Fax: +81-857-31-5591 17 e-mail: sugiyama@muses.tottori-u.ac. jp 18 19 *Corresponding Author; Takashi Takeuchi, Department of Veterinary Medicine, Tottori University, 4-101 20 Koyama-Minami, Tottori 680-8553, Japan. 21 Phone & Fax: +81-857-31-5645 22 e-mail: takeuchi@muses.tottori-u.ac. jp 23 24 Page 1 of 27
Estimating Precipitation Data Using a Fuzzy- based Technique

As a flexible tool that may be adapted to many systems, fuzzy logic was employed to develop a new technique for estimation of precipitation data. This fuzzy-based technique estimates precipitation for any point upon available data from the neighboring meteorological stations. The contributions of each station is weighed due to its differential longitudes, latitudes, and altitudes with respect to the point of interest. This was accomplished through two membership functions for distance and elevation. Each of these functions are composed of four fuzzy sets (triangular and trapezoidal shapes with partial overlaps), which in turn led to sixteen fuzzy rules. Computing weights for each station activates a minimum of two and a maximum of four rules. The technique was tested for Khorasan province in eastern Iran using the data from 48 meteorological stations. Finally, the results from the fuzzy-based technique are compared with the results of two other commonly used methods, namely simple average and inversed-distance. The results generally showed the minimum error for fuzzy technique. The minimum mean- absolute-error and the model deviation of the estimated values were found for the fuzzy-based technique. Inversed- distance and simple average methods showed higher values for these parameters. The role of the number of stations involved in the estimation process was also discussed. The optimal number of stations are found to be four.
Sub-basalt imaging from gravity studies over Deccan volcanic province of Central India

Summary Large part of the northwest and central India is covered with Deccan volcanic of Cretaceous origin. Presence of thick sequence of Mesozoic sediments underneath the volcanic cover has opened a new frontier for hydrocarbon exploration in India. Recently, detailed gravity measurements were carried out over the Deccan Syneclise of central India as a part of integrated geophysical studies for the delineation of subtrappen Mesozoic sediments. Bouguer anomaly map of the region depicts number of significant short wavelength anomalies due to shallow sources superposed on long wavelength regional anomalies due to deep-seated sources. Important among them are (i) an E-W trending broad relative gravity high associated with the Satpura mountains belt indicating presence of high density magmatic material at the deeper level (ii) a large wavelength regional gravity low in the southern part bears an inverse correlation with topography of Ajanta hills indicating mass deficiency beneath the excess topography load due to isostatic compensation (iii) short wavelength nearly E-W trending gravity low suggest the presence sediments below the volcanic cover. The residual gravity field obtained using frequency domain filtering reveals number of linear positive anomalies due to basement upwarp apart from short wavelength negative anomalies aligned in E-W direction probably due to sediments. Quantitative modeling of residual gravity field constrained by other geophysical information has brought out prominent subtrappean Mesozoic sub-basins along the Tapti rift. It is observed that thickness of sediments increases towards the east reaching to a maximum of about 2.0 Km. It is therefore inferred that the Deccan Syneclise region of central India has large potential for hydrocarbon exploration.
Bit-serial systolic architecture for 2-D non-separable discrete wavelet transform

In this paper, we have presented a bit-serial systolic-like architecture for the computation of non-separable two-dimensional discrete wavelet transform (2-D DWT) based on the principle of distributed arithmetic. The computational core of the proposed structure is highly regular and modular. The computations which become redundant due to the decimation process are eliminated to obtain a low-complexity computing algorithm for the 2-D DWT. Moreover, it exploits the advantage of constant wavelet filter-base in the DA-based structure to reduce the hardware-complexity. It is shown that the proposed structure involves very low hardware complexity, and significantly less area-time complexity compared with the existing bit-level designs.
Adaptability and stability of conilon coffee in areas of high altitude

In view of the predicted models of global climate change and differences in prices and production costs, there is increased interest in Coffea canephora cultivation in areas of high altitude. However, this species is sensitive to low temperatures, where genotypes vary regarding adaptation/tolerance mechanisms, demonstrating genotype x environment interaction. The aim of this study was to evaluate the stability and adaptability of C. canephora varieties in high-altitude areas. The experiments were carried out in February 2004, in Bom Jesus do Itabapoana, Rio de Janeiro State, Brazil, at an altitude of 725 m. Four clonal varieties (EMCAPA 8111, EMCAPA 8121, EMCAPA 8131, and EMCAPA 8151) and five harvests (2006 to 2010) were used. The experimental design was randomized blocks with four treatments and six plots, with 12 plants in each plot and spaced 2.5 x 1.2 m. Adaptability and stability parameters were determined using methods based on
Fingerprinting: Tiktok Analysis of Network Traffic Using Data Capture Tools

Cybersecurity is fundamental nowadays, both in industrial environments as well as in homes and social networks. It is of vital importance due to the fact that sensitive information is constantly being entered into computing devices, which are easily accessible to cybercriminals when there is insufficient computer security, lack of resources or simply out of ignorance or the assumption that one is insignificant as a target. Therefore, this article aims to delve into the privacy policies and understand the data that is sent from an Android mobile device to the servers of the social network called TikTok. Understanding how personal information is handled and protected is critical in an era where the digital landscape is intertwined with our daily lives. By examining the mechanisms and protocols used by platforms such as TikTok, we can gain insight into potential risks and vulnerabilities that may arise in the process. By fostering a deeper understanding of privacy and data security practices in relation to popular apps and platforms, individuals can make informed decisions about their digital footprint and take proactive steps to protect their personal information.
Catecholaminergic Polymorphic Ventricular Tachycardia

Catecholaminergic polymorphic ventricular tachycardia (CPVT) is characterized by episodic syncope occurring during exercise or acute emotion in individuals without structural cardiac abnormalities. Arrhythmias may be well tolerated, with only mild symptoms such as dizziness or lypothymia. The underlying cause of these episodes is the onset of fast ventricular tachycardia (bidirectional or polymorphic). Spontaneous recovery occurs when these arrhythmias self-terminate. In other instances, ventricular tachycardia may degenerate into ventricular fibrillation and cause sudden death if cardiopulmonary resuscitation is not readily available. The mean age of onset of symptoms (usually a syncopal episode) of CPVT is between age seven and twelve years; onset as late as the fourth decade of life has been reported. If untreated, CPVT is highly lethal, as approximately 30% of affected individuals experience at least one cardiac arrest and up to 80% one or more syncopal spells. Sudden death may be the first manifestation of the disease.
Manuscript Title: On the nature of radio-wave radiation from particle cascades

The nature of the radio-wave radiation generated by particle cascades in both the Earth’s atmosphere and dense media such as ice has, historically, been much debated. This situation changed in the early 2010’s, with the community converging on the common terminology of “geomagnetic” and “Askaryan” radiation to describe the two emission mechanisms. However, this convergence arose from discussions at various conferences and workshops, and was ultimately reached through agreement between simulation codes and experimental measurements. In this article therefore, I use relatively simple geometrical arguments, and a minimum of calculations based on single particle tracks, to explain the nature of radiation from extensive air showers (EAS) and cascades in dense media such as ice. I identify well-determined frequency regimes where the radiation from the Askaryan effect will be bremsstrahlung-like and Cherenkov-like, being respectively below/above 1 GHz in EAS and 100 MHz in dense media; and where geomagnetic emission will be transversecurrent-like and where it will resemble synchrotron radiation, respectively below/above a few GHz in EAS, depending on the height of cascade development. I suggest how these transitions in the nature of the emission may be experimentally observed.
Advances in Soybean Breeding for Super High-yielding

We used cross breeding and evaluated progenies and lines under conditions of high fertility with irrigation,developed Zhonghuang 13,Zhonghuang 19 and Zhonghuang 35,three soybean cultivars with super high-yielding,and made certain progress in soybean breeding for super high-yielding and cultivation.Zhonghuang 13 and Zhonghuang 19 each obtained yield of4.5 t·ha-1 twice.Zhonghuang 35 got to 6.0 t·ha-1 three times by using drip irrigation with fertilizer,lodging controlled by chemical and soil pH regulation by ferrous sulphate.Zhonghuang 13 won State and Beijing first-class Science and Technology Award,Zhonghuang 13 occupied first place among released soybean cultivars in China during the past five years.
A cosmopolitan inversion facilitates seasonal adaptation in overwintering Drosophila

Abstract Fluctuations in the strength and direction of natural selection through time are a ubiquitous feature of life on Earth. One evolutionary outcome of such fluctuations is adaptive tracking, wherein populations rapidly adapt from standing genetic variation. In certain circumstances, adaptive tracking can lead to the long-term maintenance of functional polymorphism despite allele frequency change due to selection. Although adaptive tracking is likely a common process, we still have a limited understanding of aspects of its genetic architecture and its strength relative to other evolutionary forces such as drift. Drosophila melanogaster living in temperate regions evolve to track seasonal fluctuations and are an excellent system to tackle these gaps in knowledge. By sequencing orchard populations collected across multiple years, we characterized the genomic signal of seasonal demography and identified that the cosmopolitan inversion In(2L)t facilitates seasonal adaptive tracking and shows molecular footprints of selection. A meta-analysis of phenotypic studies shows that seasonal loci within In(2L)t are associated with behavior, life history, physiology, and morphological traits. We identify candidate loci and experimentally link them to phenotype. Our work contributes to our general understanding of fluctuating selection and highlights the evolutionary outcome and dynamics of contemporary selection on inversions.
NMF with time-frequency activations to model non stationary audio events

Real world sounds often exhibit non-stationary spectral characteristics such as those produced by a harpsichord or a guitar. The classical Non-negative Matrix Factorization (NMF) needs a number of atoms to accurately decompose the spectrogram of such sounds. An extension of NMF is proposed hereafter which includes time-frequency activations based on ARMA modeling. This leads to an efficient single-atom decomposition for a single audio event. The new algorithm is tested on real audio data and shows promising results.
Efficient Mobile node Hand-Over Mechanism using AOL by setting RWPB

Mobile nodes are not static. They will move on random possibilities within and beyond boundaries. Identifying node's random movement for data transmission is addressed in this paper. The common problem identified in Random waypoint movement is the lack in velocity distribution and solution addressed to this problem is Random Waypoint on the Border (RWPB). It has been addressed earlier and the solutions for this problem were velocity distribution. Generally poor velocity distribution will stop mobile nodes and make them stationary. Such nodes will remain idle over a period of time depending on velocity distribution. This scenario will effect node movement particularly in the aspect of mobile node handover management. We have proven this result in MANET for avoiding delay in mobile handover management by keeping every mobile node active. Mobile handover mechanism is the way for changing mobile control from one node to another without any latency. If latency prevails it leads to packet loss and delay distortion. Hence RWPB along with efficient Handover mechanism makes the MANET efficient in terms of its service and accessibility. The simulated results of this work were done with NS2 mobility pack.