Miracle-dz/UniFAR-FTUs huggingface dataset:
Turkish Teachers' Experiences on the Distance Education Process and Technological Education Tools

Education has had an important place throughout history. Education should continue continuously because it shapes society. Education is required to progress in fields such as construction, health, agriculture, transportation, tourism, science, art, literature, etc. Because education is important for the future of society, it continues even in extraordinary situations such as war and epidemics. Education continued remotely during the COVID-19 epidemic, which was considered an extraordinary situation. The COVID-19 virus, which has felt its impact in many areas around the world, has caused changes in some areas in Turkey. The aim of the study is to determine the experiences of Turkish teachers regarding the educational method applied and the technological tools used to continue education during the distance education process. This study also aims to shed light on other studies on how the distance education process can become more efficient. Qualitative research method and case design were preferred in the study, which included the opinions of the Turkish teachers who participated in the study about the distance education process. In the study, it was stated that our teachers as a country were not yet ready for the distance education system, but this process in which we suddenly found ourselves with the pandemic was managed well in line with the possibilities. During the pandemic period distance education process, having communication skills and mastering technology came to the fore as teacher competencies. It has been determined that the most important factor behind students' inability to attend class is the lack of materials. In addition, the most used communication tool during the distance education process during the pandemic period was the phone, while the most used communication application was Whatsapp. It was concluded that Zoom and EBA applications are the most preferred applications after Whatsapp. Various suggestions were made in the light of the findings obtained at the end of the study.
Adopting a Flying Base Station for Connectivity Coverage of Temporary Events

To provide connectivity coverage for a temporary event that occurred for a short period in a remote area, deploying a classical network architecture for communication coverage would not be the most efficient approach. For such a temporary event, one innovative technique in 5G networks that can be followed is to provide connectivity from a potable base station called by unmanned aerial vehicle (UAV). This paper shows a performance comparison of using a classical network architecture with one or multiple fixed-located base stations and the approach of adopting a one-flying base station based on UAV for covering moving multiple user equipment (UEs) in a remote area. The results in this paper show that the proposed approach based on a one-flying base station outperforms the traditional approach based on multiple stationary base stations in terms of the received channel capacity.
ADMM-Based Solution for mmWave UL Channel Estimation with One-Bit ADCs via Sparsity Enforcing and Toeplitz Matrix Reconstruction

Low-power millimeter wave (mmWave) multi-input multi-output communication systems can be enabled with the use of one-bit analog-to-digital converters. Owing to the extreme quantization, conventional signal processing tasks such as channel estimation are challenging, making uplink (UL) multiuser receivers difficult to implement. To address this issue, we first reformulate the UL channel estimation problem, and then combine the idea of $\ell_{1}$ regularized logistic regression classification and Toeplitz matrix reconstruction in a properly designed optimization problem. Our new method is referred to as $\ell_{1}$ regularized logistic regression with Toeplitz matrix reconstruction (L1-RLR-TMR). In addition, we develop a computationally efficient alternating direction method of multi-pliers (ADMM)-based implementation for the L1-RLR-TMR method. Numerical results demonstrate the performance of the L1-RLR-TMR method in comparison with other existing methods.
Response and intensification of fruit trees in mitigation of degraded farmlands and adaptation to climate change in farming communities Kusolwa, P.M., Mgembe, E.R., Madalla, N., Nyomora, A., Kanemba, A.D. and

The response for acceptance of fruit trees in farmland was determined in four selected villages in Morogoro region. Farmers realizing the level of farmland degradation were highly motivated to adopt the innovation for incorporation of adapted fruit tree species in their farms and household premises. In order to fast track fruit tree planting activities for the purpose of reducing the impact of climate change in local farming communities, at total 2,600 of different grafted/budded (1,400) and non grafted seedlings from fruit tree species adapted to these areas were distributed and planted to three villages; Msingisi, Masenge (Gairo) and Mlimani ward (Morogoro). Most of transplanted fruit trees (72.6%) survived. Furthermore, for intensified and sustainable planting of fruit trees in the target and nearby villages, one nursery site was established and 50 farmers were trained in plant propagation and nursery establishment. A total of 1,200 Avocado rootstocks were raised and more than 80% (900 seedlings) of them have been successfully grafted. The use of fruit tree species as a strategic intervention for mitigation and adaptation to climate change in the study areas has been received positively with increasing demand for more fruit trees per village.
Response of Dissolved Trace Metals to Dust Storms, Sediment Resuspension, and Flash Floods in Oligotrophic Oceans

Trace metals (TM) delivered by atmospheric dust play a key role in oceanic biogeochemical cycles. However, the impact of short‐term environmental perturbations such as dust storms and sediment resuspension events on the oceanic water column is poorly constrained due to the low temporal sampling resolution and episodic nature of these events. The Gulf of Aqaba (GoA), Red Sea, is a highly accessible deep oligotrophic water body featuring exceptionally high atmospheric deposition fluxes that provide the main source of TMs to the GoA surface water. Here, we present a 2‐year time series of dissolved manganese, cobalt, nickel, copper, zinc, cadmium, and phosphate concentration profiles sampled in the GoA. The study focuses on daily time scale dust storms and episodes of sediment resuspension to quantify the immediate impact of these events on dissolved TM cycling. Counter‐intuitively, upper mixed layer TM inventories decrease with increasing aerosol loads, with the effects of aerosol‐induced TM scavenging and dissolution peaking 5–6 days after aerosol deposition. Dust storms promote intense TM scavenging, with TM inventories decreasing by up to 44%, but seldom lead to TM enrichment. Similarly, sediment resuspension and flash flood events triggered significant TM scavenging. These findings highlight the potential dual role of atmospheric deposition in the oceans as a long‐term source of dissolved TMs and a short‐term sink. The in situ observations presented here may be used to understand and quantify the global impact of abrupt environmental events on oceanic chemical compositions.
Application of reinforcement learning with continuous state space to ramp metering in real-world conditions

In this paper we introduce a new approach to Freeway Ramp Metering (RM) based on Reinforcement Learning (RL) with focus on real-life experiments in a case study in the City of Toronto. Typical RL methods consider discrete state representation that lead to slow convergence in complex problems. Continuous representation of state space has the potential to significantly improve the learning speed and therefore enables tackling large-scale complex problems. A robust approach based on local regression, named k nearest neighbors temporal difference (kNN-TD), is employed to represent state space continuously in the RL environment. The performance of the new algorithm is compared against the ALINEA controller and typical RL methods using a micro-simulation testbed in Paramics. The results show that RM using the kNN-TD method can reduce total network travel time by 44% compared to the do-nothing case (without RM) and by 17% compared to ALINEA.
The Extended Surgical Concepts for Hepatocellular Carcinoma in the Era of Immune Checkpoint Inhibitors

Abstract Surgical resection remains one of the most effective curative therapies for HCC. However, the majority of patients have advanced unresectable diseases upon presentation. It is of paramount importance to raise the resectability of patients with HCC. The remarkable objective response rate reported by Phase III IMbrave150 trial has led to the concept of “Atezo/Bev followed by curative conversion (ABC conversion)” for initially unresectable HCC. With this revolutionary treatment strategy, the concept of surgical resection for HCC should be amended. The current opinion illustrated three extended surgical concepts, which could be integrated into clinical practice in the era of immune checkpoint inhibitors (ICI).
Accurate Energy Efficiency Prediction in Sub-6GHz Radio Access Networks Based on Pathloss Modeling Using Kriging Methods

Radio access network (RAN) designers need to prioritize capacity and energy efficiency performance in 5G RANs to accommodate the increasing user demands. The analysis of RAN performances is substantially simplified through the application of an accurate, low computational complexity, and straightforward-to-apply pathloss model, which incorporates realistic correlated shadow fading. The work presented in this paper is based on the kriging method that generates an accurate correlated shadow fading map, which can be derived from either measured or simulated pathloss data. The new model is found to accurately predict throughput and energy efficiency in a densified urban RAN when compared with a reference data set.
Integrated aquaculture of Bonnemaisoniaceae: physiological and nutritional controls of biomass production and of halogenated metabolite content

The red seaweed Asparagopsis armata (Harvey; Rhodophytae, Bonnemaisoniaceae) produces biologically active secondary metabolites that are valuable natural ingredients for cosmetics and medicine and its cultivation may therefore be a profitable venture. The tetrasporophyte of this species (Falkenbergia rufolanosa) was successfully tank-cultivated as a continuous biofilter for the effluent of a commercial fish farm in southern Portugal. Optimal stocking density for highest biomass yield and a low level of other algal species in winter and late spring was 5 g centrifuged fresh weight L. The effect of total ammonia nitrogen supply (TAN flux) on biofiltration and biomass yield was investigated in winter and spring. Results revealed that A. armata is currently the seaweed-biofilter with the highest TAN removal of up to 90 μmol L h at a TAN flux of about 500 μmol L h. In the tanks used, this is equivalent to a removal of up to 14.5 g TAN m d. At a lower TAN flux of about 40 μmol L h, TAN removal by A. armata is more than double to what is reported at this flux for another successful seaweed biofilter, the genus Ulva. Monthly variation of A. armata biomass yield peaked in May and was lowest in January. At TAN fluxes between 15 * This chapter is published in Aquaculture 252 (2006) 3-11 Asparagopsis armata as a seaweed biofilter 300 and 400 μmol L h, an average water temperature of 21.7 °C and a total daily photon flux density of 47 mol m, seaweed yield was over 100 g DW m d with a recorded maximum of 119 g. During spring, autumn and early summer, the biomass of A. armata within the experimental tanks doubled every week. A model for the up scaling of this finfish integrated aquaculture of A. armata varies the investment in biofilter surface area and estimates the return in biofiltration and biomass yield. Highest TAN removal efficiencies will only be possible at low TAN fluxes and a very large biofilter area, resulting in a low production of biomass per unit area. To remove 50 % of TAN from the effluent (1 mt Sparus aurata; 21 °C), 28 m of biofilter, designed to support a water turnover rate of 0.8 Vol h would be necessary. This system produces 6.1 kg FW (1.5 kg DW) of A. armata per day and has the potential to turn biofiltration into an economically sustained, beneficial side effect.
A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability

This review surveys the basic theories, observational methods, satellite algorithms, and land surface models for terrestrial evapotranspiration, E (or λE, i.e., latent heat flux), including a long‐term variability and trends perspective. The basic theories used to estimate E are the Monin‐Obukhov similarity theory (MOST), the Bowen ratio method, and the Penman‐Monteith equation. The latter two theoretical expressions combine MOST with surface energy balance. Estimates of E can differ substantially between these three approaches because of their use of different input data. Surface and satellite‐based measurement systems can provide accurate estimates of diurnal, daily, and annual variability of E. But their estimation of longer time variability is largely not established. A reasonable estimate of E as a global mean can be obtained from a surface water budget method, but its regional distribution is still rather uncertain. Current land surface models provide widely different ratios of the transpiration by vegetation to total E. This source of uncertainty therefore limits the capability of models to provide the sensitivities of E to precipitation deficits and land cover change.
A new remote sensing electro-optical system on low-light target

In view of the application of optical remote sensing disaster emergency rescue under the complex environment of low illumination at night, the optical remote sensing imaging technology under the condition of low illumination and low signal-to-noise ratio was studied. The compressed sensing technology of thin film diffraction grating primary mirror is used to realize large-aperture optical acquisition. The sensing ability of large dynamic range is increased by Geiger pattern imaging technology, and the dim and weak targets are identified by semantic sensing algorithm. The system realizes target recognition under the condition of extremely low image signal-to-noise ratio through the design of the new system's main mirror flattening and the aliasing compression and decoupling of spatial information and spectral information. The technology has completed space-based scheme design and desktop principle verification tests, and the spectral resolution reaches 5nm, realizing fast target search and recognition.
Fast Cycle Multiple Entry PBFT Consensus

Practical Byzantine Fault Tolerance (PBFT) is widely used despite its limitations. In this paper we extend a previously described multiple entry version of PBFT with fast cycle capability. In this approach, multiple data blocks are proposed by different nodes or replicas, but instead of choosing only one to undergo the consensus procedure, replicas collect and order the proposals which are then accepted through a simplified consensus cycle. We analyze the operation of this scheme using a probabilistic model and show that consensus performance actually improves over that of the original PBFT as the traffic load increases. In this manner, the proposed scheme appears to be well suited for blockchain-based Internet of Things (IoT) applications.
Emigration From Post-Communist Central Europe After 1989 Interpreted Within the Aspirations/Capabilities Framework

In the period of post-communist transition, Central Europe witnessed complex and multifaceted mobility processes; permanent outmigration, of an ethnic or labour-related nature, coexisted with temporary, seasonal, or cross-border movements and an increasing influx of foreigners. To study these complex processes, we have chosen to apply a holistic and comprehensive approach, rather than limit conceptual considerations to one theory of migration determinants. We focus on eleven post-communist countries that joined the European Union (EU-11) and on the period extending from around 1989, covering the EU’s eastward enlargement, to the present. The aim of this study is twofold: first, we propose a general conceptual framework, based on the aspirations/capabilities approach, to present the main determinants of emigration from this part of the European continent. Second, in relation to each determinant, we formulate research questions postulated by selected theories of international migration and present the evidence, based on existing empirical studies, that addresses these questions. The paper contributes to the literature by providing a broad interpretation of post-transition mobility and pointing to commonly overlooked explanatory factors. We highlight the importance of economic factors that have enhanced and directed the outward migration from the EU-11 to selected EU member states and selected economic sectors; in particular, as regards capabilities, these factors include the lifting of labour market restrictions, high demand in the secondary sector of labour markets, and the roles of migration networks and the migration industry. Emphasis is also placed on aspirational factors, such as labour market failures and the substantial aspirational gap resulting from improvements in high educational attainment in the countries of origin. The aspirations/capabilities approach serves well as a general framework of migration determinants, but its explanatory power is enhanced by reference to other, more specific theories of migration. We show that a combination of the complementary approaches provides a more refined and in-depth picture of migration from the region. * This article belongs to a special issue on “Demographic Developments in Eastern and Western Europe Before and After the Transformation of Socialist Countries”.
Religion gnaws urban planning: the geography of places of worship in Kumasi, Ghana

This paper investigates spatial distribution of places of worship (PoW) and its implications on sustainable land use planning in a rapidly urbanising city of Kumasi, Ghana. Using semi-structured interviews, document reviews and agency consultations, this paper focused on three issues: (a) the location and distribution of PoW, (b) factors considered in the location of these PoW by faith groups and (c) planning implications of PoW. Findings indicate that location decisions vary according to different faith groups. However, none of the faith groups interviewed considered land use planning regulations as key decision-making factor, as proximity to members, affordability and availability of land remained dominant factors. This situation has created avoidable land use conflicts and has become an additional burden on urban planning authorities who are already faced with pervasive land use challenges such as slum development and urban sprawl.
Duck-bill dinosaurs (Hadrosauridae, Ornithischia) from the North Slope of Alaska

Hadrosaur Bones have been found on the Colville River north of Umiat on the North Slope of Alaska. This find represents the first report of dinosaur bones in Alaska and their northernmost reported occurrence. The remains are not determinable below family level but are important, nonetheless, for interpretations of the paleoclimatology and paleobiogeography of the Late Cretaceous.
Compact Models for Simulation of On-Chip ESD Protection Networks

Technology scaling and increased data rates make it near impossible to achieve historic levels of electrostatic discharge (ESD) robustness. This heightens the need for pre-Si verification that a design’s ESD level is above a critical value, below which the yield loss and the number of field returns are expected to be high. Transient simulation plays a role in ESD design verification and requires the availability of accurate compact models of the various semiconductor devices, which lie along the discharge path. The compact models included in a foundry process design kit (PDK) are not accurate at ESD current levels. This article describes compact models that have been developed in the ESD device research community. It reviews the measurements used to characterize ESD protection devices and acquire data for model parameter extraction. It is concluded that obtaining accurate measurement data is challenging and this impedes the widescale adoption of ESD compact models.
Central American Migrants and “La Bestia”: The Route, Dangers, and Government Responses, Rodrigo Dominguez Villegas, migrationpolicy.org, 10/09/2014

"Mexico has long been accused of turning a blind eye to Central American migrants traveling through the country en route to the United States. With the recent unaccompanied child migration crisis garnering major U.S. public and policymaker attention, the trains that have served as unofficial conduits for some of this migration have come under scrutiny, prompting the Mexican government to take action. As many as half a million Central American immigrants annually hop aboard freight trains co.
Comparative study of approaches to bathymetry detection in Nasser/Nubia Lake using multispectral SPOT-6 satellite imagery

Collecting and analysing bathymetric information is essential for lake management. This is particularly true regarding Lake Nasser/Nubia in Egypt, where accumulated sediment in the lake must be examined. This is typically accomplished through field measurements, which are time consuming and costly. However, remotely sensed imagery provides wide coverage, low cost, and time-saving solutions for bathymetric measurements, especially in shallow areas with high erosion or sediment accumulation, such as at the entrance of Lake Nasser/Nubia. In this study, bagging (Bag) and least square boosting (LSB) fitting algorithms that use reflectance of green and red band logarithms, green/red band logarithms ratio, and blue/red band logarithms ratio are proposed for bathymetry detection. For validation, the proposed approaches were compared with the ratio method (RM) and neural network (NN) conventional methods. Bathymetric data obtained from all methods using SPOT-6 imagery were evaluated by means of global positioning system (GPS) and echo sounder data field measurements. The Bag ensemble outperformed all methods with 0.85 m RMSE, whereas RM, LSB, and NN yielded 1.03, 0.99, and 0.97 m respectively. The results showed that the proposed approaches outperform and are more accurate than RM conventional method and the Bag approach is more accurate than the NN model when applied over shallow water depths of up to 6.5 m.