Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Drip Irrigation and Phosphorus Fertilization on the Growth of Peanut Plants Grown on Sandy Calcareous Soils

IELD experiments were carried out at the Experimental Farm of . Arab ElAwammer Research Station, Agriculture Research Center, Assuit, Egypt, during the two successive growth summer seasons of 2010 and 2011, to study the effect of two levels of phosphorus fertigation (23 and 31 kg P2O5/ fed) divided into different doses (3, 6 and 9 doses) under different irrigation regimes (80 and 100% from pan evaporation). Water consumptive use, irrigation water use efficiency (IWUE), peanut yield and yield components were evaluated. The obtained results could be summarized as follows:
Vehicle–Bridge Interaction Modelling Using Precise 3D Road Surface Analysis

Uneven road surfaces are the primary source of excitation in the dynamic interaction between a bridge and a vehicle and can lead to errors in bridge weigh-in-motion (B-WIM) systems. In order to correctly reproduce this interaction in a numerical model of a bridge, it is essential to know the magnitude and location of the various roadway irregularities. This paper presents a methodology for measuring the 3D road surface using static terrestrial laser scanning and a numerical model for simulating vehicle passage over a bridge with a measured road surface. This model allows the evaluation of strain responses in the time domain at any bridge location considering different parameters such as vehicle type, lateral position and speed, road surface unevenness, bridge type, etc. Since the time domain strains are crucial for B-WIM algorithms, the proposed approach facilitates the analysis of the different factors affecting the B-WIM results. The first validation of the proposed methodology was carried out on a real bridge, where extensive measurements were performed using different sensors, including measurements of the road surface, the response of the bridge when crossed by a test vehicle and the dynamic properties of the bridge and vehicle. The comparison between the simulated and measured bridge response marks a promising step towards investigating the influence of unevenness on the results of B-WIM.
SPCM: A Machine Learning Approach for Sentiment-Based Stock Recommendation System

Recommendation systems play a pivotal role in delivering user preference information. However, they often face the challenge of information cocoons due to repeated content delivery, particularly prevalent in stock recommendations that are susceptible to investor sentiment. In response to the information cocoons, we propose the Sentiment and Price Combined Model (SPCM), which leverages sentiment features and price factors to predict stock price movements. This novel framework combines collective sentiment analysis with state-of-the-art BERT transformer models and advanced machine learning techniques. Over a three-year period, we collected 40 million stock comments from the Guba platform, extracting investor sentiment conveyed in text information and investigating the impact of metrics such as homophily on stock recommendations. Experimental results indicate that both the volume of posts and the agreement index affect the effectiveness of investor sentiment, while homophily reduces the accuracy of participants’ stock price judgments. The recognition accuracy of the BERT-based sentiment analysis model reaches an impressive 84.12%, and the portfolio constructed by SPCM yields a cumulative return four times that of the industry benchmark. Furthermore, homogeneous quantitative metrics also enhance diversification in stock selection.
Searchable encryption: A survey on privacy‐preserving search schemes on encrypted outsourced data

Outsourcing confidential data to cloud storage leads to privacy challenges that can be reduced using encryption. However, with encryption in place, the utilization of the data is reduced, which leads to reduced quality of experience of the users. To overcome this, searchable encryption (SE) schemes are utilized, which allow the end users to retrieve the relevant documents from the cloud, for which various researchers have worked utilizing different techniques. Despite the popularity of the searchable encryption schemes, most of the surveys either do not provide or present an incomplete taxonomy of SE schemes. Hence, in this paper, we attempt to present a complete taxonomy/classification of the searchable encryption schemes in terms of the type of search, type of index, results retrieved, implementation type, multiplicity of users, and the technique used. From the literature, it is observed that inner product similarity is widely adopted by researchers to compute the similarity of the query and the document index as it provides both conjunctive and disjunctive searching (ie, have better search capability) but requires high search time (ie, have lower search efficiency). On the other hand, schemes based on binary comparisons exist, which require less search time (ie, have better search efficiency) but support only conjunctive searching (ie, have limited search capability). Thus, a major conclusion drawn from our work is that there is an imbalance between search capability and search efficiency, ie, in the existing schemes, search capability can be improved at the cost of search time only. Therefore, we suggest that one direction where researchers should work on is to provide a balance between search capability and search efficiency.
Changes in Immune Response during Pig Gestation with a Focus on Cytokines

Simple Summary Immunity during pig pregnancy has been especially studied during the periimplantation period, in which there is an important relationship between sex steroids and cytokines. Although part of the abundant embryonic/fetal deaths in pigs occur in more advanced periods of gestation, there are few studies that analyze these stages. This review analyzes the changes in the immune response, emphasizing the local response and cytokines, throughout pig gestation. The very great variations that occur throughout the periimplantation period and the complexity of the response at the time of placental remodeling (60–70 dpc) when increase anti and proinflammatory cytokines. Abstract Pigs have the highest percentage of embryonic death not associated with specific diseases of all livestock species, at 20–45%. During gestation processes, a series of complex alterations can arise, including embryonic migration and elongation, maternal immunological recognition of pregnancy, and embryonic competition for implantation sites and subsequent nutrition requirements and development. Immune cells and cytokines act as mediators between other molecules in highly complex interactions between various cell types. However, other non-immune cells, such as trophoblast cells, are important in immune pregnancy regulation. Numerous studies have shed light on the crucial roles of several cytokines that regulate the inflammatory processes that characterize the interface between the fetus and the mother throughout normal porcine gestation, but most of these reports are limited to the implantational and peri-implantational periods. Increase in some proinflammatory cytokines have been found in other gestational periods, such as placental remodeling. Porcine immune changes during delivery have not been studied as deeply as in other species. This review details some of the immune system cells actively involved in the fetomaternal interface during porcine gestation, as well as the principal cells, cytokines, and molecules, such as antibodies, that play crucial roles in sow pregnancy, both in early and mid-to-late gestation.
Money demand in Mexico: a nonlinear ARDL approach

This paper examines the relationship between Mexican money demand and three economic factors: real income, inflation rate and exchange rate, and the relationship between exchange rate and money demand is the most concerned. Using the quarterly data of Mexico from 2000 to 2022, we explore whether the exchange rate will symmetrically affect the demand for money in the short and long term. The results show that in the long run, the impact of real income and inflation rate on money demand is the same as the conjecture, both are positive. However, the present paper does not find an asymmetric effect of the exchange rate, possibly due to the lack of research data or the short time span.
EFFECT OF STORAGE CONTAINER ON KENAF SEED QUALITIES

Kenaf seeds lose their ability to germinate during storage, leading to a lack of quality seeds compared to planting requirements, hindering the expansion of kenaf cultivation in Bangladesh. The effects of different storage containers on the germination, field emergence moisture content and 100 seed weight of kenaf seeds of three varieties were studied during a 4-month storage period from mid-January 2022 to mid-May 2022 in a room. Four different containers viz. C1=A plastic pot, C2=a polythene bag, C3=a cloth bag and C4=an earthen pot are used to store kenaf seeds. Three varieties, V1=HC-95, V2=HC-2 and V3=BJRI Kenaf-3 were used in this experiment. This experiment revealed that the percentage of germination and field emergence of all three varieties were reduced with increasing the storage time. On the other hand moisture content and 100-seed weight of three selected varieties were increased with increasing the storage period. Among the four containers it was observed that after 120 days of storage germination percentage was maximum for plastic pot (81.6%) followed by polythene bag (80.6%), cloth bag (58.6%) and minimum for earthen pot (56.0%). Similarly in field emergence the highest result found for plastic pot (72.3%) and lowest for earthen pot (53.3%). On the other hand the highest moisture content and 100 seed weight were recorded in cloth bag (21.1%) and 4.7g in earthen pots respectively and the lowest moisture content (10.4%) and 100 seed weight (3.26%) in plastic pots. Germination rate at 120 DAS was recorded maximum in HC-95 (70.2%) and minimum in BJRI Kenaf-3 (67.7%). The highest filed emergence at 120 DAS was found in HC-2 (63.0%) and lowest in BJRI Kenaf-3 (61.3%). The highest moisture content and 100-seed weight at 120 DAS were obtained in HC-2 (15.8%) and BJRI kenaf-3 (4.04%) respectively. The results reveal that the quality of kenaf seeds decrease with increase the storage time.
A Deep CNN-Based Detection Method for Multi-Scale Fine-Grained Objects in Remote Sensing Images

The detection of fine-grained objects in remote sensing images has been recognized as a challenging issue, which cannot be well addressed by the existing deep learning-based methods due to their inadaptability to multi-scale objects, slow convergence speed, and limitations to scarce datasets. To cope with the above issue, we propose a deep convolutional neural network (CNN)-based detection method for multi-scale fine-grained objects in complex remote sensing scenarios. Specifically, we adopt a deep CNN with a residual structure as the backbone network, to extract deep-level details from the image. Besides, we introduce a multi-scale region generation network to overcome the limitations of fixed receptive field convolution kernels and enable multi-scale object detection. Lastly, we replace fully connected layers in the fully convolutional region classification network with $1\times 1$ convolutional layer to enhance detection efficiency and detection speed. To overcome the limitation of scarce datasets, we conducted experiments on the FAIR1M dataset, which is currently the largest fine-grained object detection dataset in the remote sensing field. Simulation results show that the proposed detection method achieves the highest average precision (35.86%) among all benchmarks and outperforms the classic Faster R-CNN-based method by 3.44%. Furthermore, our method demonstrates significantly improved detection speed compared to the Faster R-CNN-based methods.
Photobiomodulation Using Light-Emitting Diode (LED) for Treatment of Retinal Diseases

Abstract Photobiomodulation (PBM) is a type of phototherapy that employs light-emitting diodes (LEDs) or low-power lasers to selectively administer specific wavelengths of visible light, ranging from 500 to 1000 nm, including near-infrared (NIR) wavelengths. LEDs are advantageous compared to lasers due to their ability to treat large areas at a lower cost, lack of tissue damage potential in humans, and reduced risk of eye-related accidents. The ophthalmology community has recently taken interest in PBM as a promising novel approach for managing various retinal conditions such as age-related macular degeneration, retinopathy of prematurity, retinitis pigmentosa, diabetic retinopathy, Leber’s hereditary optic neuropathy, amblyopia, methanol-induced retinal damage, and potentially others. This review critically assesses the existing body of research on PBM applications in the retina, focusing on elucidating the underlying mechanisms of action and evaluating the clinical outcomes associated with this therapeutic modality.
Association between Psoriasis and Renal Functions: An Integration Study of Observational Study and Mendelian Randomization

Psoriasis is an autoimmune-mediated disease with several comorbidities in addition to typical skin lesions. Increasing evidence shows the relationships between psoriasis and renal functions, but the relationship and causality remain unclear. We aimed to investigate the associations and causality between psoriasis and four renal functions, including the estimated glomerular filtration rate (eGFR), blood urea nitrogen (BUN), urine albumin to creatinine ratio (UACR), and chronic kidney disease (CKD). For the population-based study, we analyzed the National Health and Nutrition Examination Survey (NHANES) data from five cycles (2003–2006 and 2009–2014) on psoriasis and renal functions. Subgroup analyses were conducted among different categories of participants. Meanwhile, a bidirectional two-sample Mendelian randomization (TSMR) study in European populations was also performed using summary-level genetic datasets. Causal effects were derived by conducting an inverse-variance weighted (MR-IVW) method. A series of pleiotropy-robust MR methods was employed to validate the robustness. Multivariable MR (MVMR) was conducted to complement the result when five competing risk factors were considered. A total of 20,244 participants were enrolled in the cross-sectional study, where 2.6% of them had psoriasis. In the fully adjusted model, participants with psoriasis had significantly lower eGFR (p = 0.025) compared with the healthy group. Individuals who are nonoverweight are more likely to be affected by psoriasis, leading to an elevation of BUN (Pint = 0.018). In the same line, TSMR showed a negative association between psoriasis and eGFR (p = 0.016), and sensitive analysis also consolidated the finding. No causality was identified between psoriasis and other renal functions, as well as the inverse causality (p > 0.05). The MVMR method further provided quite consistent results when adjusting five confounders (p = 0.042). We detected a significant negative effect of psoriasis on eGFR, with marginal association between BUN, UACR, and CKD. The adverse of psoriasis on the renal should merit further attention in clinical cares.
Network Synchronization with Uncertain Dynamics

Synchronization of network-coupled dynamical units is important to a variety of natural and engineered processes including circadian rhythms, cardiac function, neural processing, and power grids. Despite this ubiquity, it remains poorly understood how complex network structures and heterogeneous local dynamics combine to either promote or inhibit synchronization. Moreover, for most real-world applications it is impossible to obtain the exact specifications of the system, and there is a lack of theory for how uncertainty affects synchronization. We address this open problem by studying the Synchrony Alignment Function (SAF), which is an objective measure for the synchronization properties of a network of heterogeneous oscillators with given natural frequencies. We extend the SAF framework to analyze network-coupled oscillators with heterogeneous natural frequencies that are drawn as a multivariate random vector. Using probability theory for quadratic forms, we obtain expressions for the expectation and variance of the SAF for given network structures. We conclude with numerical experiments that illustrate how the incorporation of uncertainty yields a more robust theoretical framework for enhancing synchronization, and we provide new perspectives for why synchronization is generically promoted by network properties including degree-frequency correlations, link directedness, and link weight delocalization.
Primary-Frequency-Tuning and Secondary-Impedance-Matching IPT Converter With Programmable Constant Power Output and Optimal Efficiency Tracking Against Variation of Coupling Coefficient

For inductive power transfer (IPT) systems, load conditions and coupling coefficient are subject to change, and affect system power and efficiency. Aiming at addressing this issue, this article proposes a two-loop control scheme based on a single-stage power-source IPT converter. The proposed IPT converter utilizes a series compensation structure on the primary side and employs a switched-controlled capacitor (SCC) in series with a semiactive rectifier (SAR) on the secondary side. The secondary SCC and the SAR cooperate via an inner control loop to emulate a null secondary impedance and an optimal load resistance, whereas the operating frequency is responsible for the output power regulation via an outer control loop. The operating principle enables programmable constant power (CP) output and optimal efficiency tracking against variations of coupling coefficient and load condition, and all power switches are designed to facilitate soft-switching to reduce switching losses. Moreover, compared with conventional IPT systems that have a constant current or constant voltage output characteristic, programmable CP output characteristics can maximize the output power capability of this IPT converter, which is suitable for battery or supercapacitor charging applications. Finally, simulations and experiments validate the proposed model and method for correctness and feasibility.
Growth, Yield and Economic Advantage of Onion (Allium cepa L.) Varieties in Response to NPSB Fertilizer and Planting Pattern

Haphazard and low soil fertility, low yielding verities and poor agronomic practices are among the major factors constraining onion production in the central rift valley of Ethiopia. Therefore, a field experiment was conducted in East Showa Zone of Adami Tulu Jido Combolcha district in central rift valley areas at ziway from October 2021 to April 2022 to identify appropriate rate of NPSB fertilizer and planting pattern of onion varieties. The experiment was laid out in split plot design of factorial arrangement in three replications. The main effect of NPSB blended fertilizer rates and varieties (red coach and red king) significantly (p<0.01) influenced plant height, leaf length, leaf diameter, leaf number and fresh leaf weight, shoot dry matter per plant, and harvest index. Total dry biomass, bulb diameter, neck diameter, average fresh bulb weight, bulb dry matter, marketable bulb yield, and total bulb yield were significantly (p<0.01) influenced only by the main effect of NPSB blended fertilizer rates. In addition, unmarketable bulb yield was statistically significantly affected (p≥0.05) by the blended fertilizer rates and planting pattern. Moreover, days to 90% maturity of onion was affected by the main factor of NPSB fertilizer rate, variety and planting pattern. The non-fertilized plants in the control treatment were inferior in all parameters except unmarketable bulb yield and harvest index. Significantly higher marketable bulb yield (41 t ha-1) and total bulb yield (41.33 t ha-1) was recorded from 300 kg ha-1 NPSB blended fertilizer rate applied. Double row planting method and hybrid red coach onion variety had also gave higher growth and yields. The study revealed that the highest net benefit of Birr, 878,894 with lest cost of Birr 148,006 by the combinations of 150 kg blended NPSB ha-1 with double row planting method (40cm*20cm*7cm) and red coach variety which can be recommendable for higher marketable bulb yield and economic return of hybrid onion for small scale farmers in the study area. Also, for resource full producers (investors), highest net benefit of Birr 1,205,372 with higher cost (159,628 Birr) by application of 300 kg NPSB ha-1 is recommended as a second option. However, the research should be replicated both in season and areas to more verify the recommendations.
MATEKG: A Large-scale Multi-class Equipment Knowledge Graph for Military Auxiliary Tasks

In the era of rapid advances in artificial intelligence, the digitization of armed forces around the world has seen unprecedented growth. A wealth of military information and knowledge is available on the Internet. The task of harnessing and analyzing this vast amount of data, and structuring the existing information to facilitate the development of information-centric weapons, has emerged as a prominent area of research. Knowledge graphs, which encapsulate and represent human knowledge in a format that machines can understand, are essential for performing tasks such as information retrieval, data analysis and inference. The creation of a knowledge graph specific to military equipment is a cornerstone in the process of military digitization. In this paper, a military equipment dataset is first constructed through structured data collection and processing based on the globally popular open data websites on equipment. Then, based on this military equipment dataset, a large-scale multi-class equipment knowledge graph for military auxiliary tasks is constructed by the proposed entity recognition method and relational triple extraction method. The experimental results show that the proposed BERT-enhanced BiLSTM and SPN achieve 90.43% and 93% F1 scores, respectively, proving the effectiveness of the proposed methods on the military equipment data.
Comparison of Modified Shock Index and Shock Index for Predicting Massive Transfusion in Women with Primary Postpartum Hemorrhage: A Retrospective Study

Background The modified shock index (MSI) is calculated as the ratio of heart rate (HR) to mean arterial pressure (MAP) and has been used to predict the need for massive transfusion (MT) in trauma patients. This retrospective study from a single center aimed to compare the MSI with the traditional shock index (SI) to predict the need for MT in 612 women diagnosed with primary postpartum hemorrhage (PPH) at the Emergency Department (ED) between January 2004 and August 2023. Material/Methods The patients were divided into the MT group and the non-MT group. The predictive power of MSI and SI was compared using the areas under the receiver operating characteristic curve (AUC). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value were calculated. Results Out of 612 patients, 105 (17.2%) required MT. The MT group had higher median values than the non-MT group for MSI (1.58 vs 1.07, P<0.001) and SI (1.22 vs 0.80, P<0.001). The AUC for MSI, with a value of 0.811 (95% confidence interval [CI], 0.778–0.841), did not demonstrate a significant difference compared to the AUC for SI, which was 0.829 (95% CI, 0.797–0.858) (P=0.066). The optimal cutoff values for MSI and SI were 1.34 and 1.07, respectively. The specificity and PPV for MT were 77.1% and 40.2% for MSI, and 83.2% and 45.9% for SI. Conclusions Both MSI and SI were effective in predicting MT in patients with primary PPH. However, MSI did not demonstrate superior performance to SI.