Miracle-dz/UniFAR-FTUs huggingface dataset:
Nano-Biofertilizer Formulations for Agriculture: A Systematic Review on Recent Advances and Prospective Applications

In the twenty-first century, nanotechnology has emerged as a potentially game-changing innovation. Essential minerals are mostly unavailable in modern cropping systems without the application of synthetic fertilizers, which have a serious negative impact on the ecosystem. This review focuses on the coupling of nanoparticles with biofertilizers to function as nano-biofertilizers (NBFs), which may ensure world food security in the face of the rising population. The inoculation of plants with NBFs improves plant development and resistance to stress. Metallic nanoparticles as well as organic components comprising polysaccharide and chitosan may be encapsulated, utilizing microbe-based green synthesis to make NBFs, which circumvents the limitations of conventional chemical fertilizers. The application of NBFs is just getting started, and shows more promise than other approaches for changing conventional farming into high-tech “smart” farming. This study used bibliographic analysis using Web of Science to find relevant papers on “nano biofertilizers”, “plants”, and “agriculture”. These subjects have received a lot of attention in the literature, as shown by the co-citation patterns of these publications. The novel use of nanotechnology in agriculture is explored in this research work, which makes use of the unique characteristics of nanoscale materials to address urgent concerns including nutrient delivery, crop protection, and sustainable farming methods. This study attempts to fill in some of the gaps in our knowledge by discussing the formulation, fabrication, and characterization of NBFs, as well as elucidating the mechanisms by which NBFs interact with plants and how this benefits the ability of the plant to withstand biotic and abiotic stress brought about by climate change. This review also addresses recent developments and future directions in farming using NBF formulations in the field.
Tell me more: Designing HRI to encourage more trust, disclosure, and companionship

Previous HRI research has established that trust, disclosure, and a sense of companionship lead to positive outcomes. We explored improving these aspects of HRI through robot behavior. Specifically, we increased the expressivity and vulnerability of a robot and measured the effects on trust, disclosure, and companionship during human-robot interaction. We engaged (N = 61) high school aged students in a 2 (vulnerability of robot: high vs. low) × 2 (expressivity of robot: high vs. low) between-subjects study where participants engaged in a short electronics learning activity with a robotic tutor. Our results show that students had more trust and feelings of companionship with a vulnerable robot, and reported disclosing more with an expressive robot. This video highlights some of the qualitative interactions students had with the robot as well as a discussion of their experiences around trust, disclosure, and companionship with the robot. The video clips of student interactions show how vulnerability and expressivity can be used to engender trust, disclosure, and companionship between a person and robot.
Characterization of clay minerals in the Brahmaputra river sediments, Assam, India

Characterization of clay minerals of the Brahmaputra river sediments within a selected stretch by X-Ray diffraction, differential thermal analysis and Fo urier transform infrared spectra has revealed the association of dominant kaolinite with subordinate amount of i llite and chlorite. The mineral assemblage, as ev idenced from the study, may find its use towards effective u nderstanding of related engineering properties and utilization in flood -management approaches, intimately connected with the lives and properties of the people of Assam.
An Improved D2GAN‐based oversampling algorithm for imbalanced data classification

To address the problems of pattern collapse, uncontrollable data generation and high overlap rate when generative adversarial network (GAN) oversamples imbalanced data, we propose an imbalanced data oversampling algorithm based on improved dual discriminator generative adversarial nets (D2GAN). First, we integrate the positive class attribute information into the generator and the discriminator to ensure that the generator only generates the samples for positive class samples, which overcomes the problem of uncontrollable data generation by the generator. Second, we introduce a classifier into D2GAN for discriminating the generated samples and the original data, which avoids the overlap among the generated samples and the negative class samples, and ensures the diversity of the generated samples, the problem of pattern collapse is solved. Finally, the performance of the proposed algorithm is evaluated on 9 datasets by using SVM and neural network classification algorithm for oversampling experiments, the results show that the proposed algorithm effectively improve the classification performance of imbalanced data.
A Longitudinal Study of a Large Clinical Cohort of Patients with Lyme Disease and Tick-Borne Co-Infections Treated with Combination Antibiotics

The rising prevalence of tick-borne infections (TBIs) necessitates further attention. This study retrospectively investigated the types of TBIs, symptoms, and if combination antibiotics were helpful within a patient cohort at an infectious disease clinic in Ireland. In this chart audit of 301 individuals (184 female, 117 male) tested for TBIs, 140 (46.51%) had positive antibody responses for TBIs from an ELISA (enzyme-linked immunoassay) that was based on a modified two-tiered testing protocol. A total of 93 (66.43%) patients had positive antibody responses to one TBI: 83 (59.29%) for Borrelia, 7 (5.00%) for Rickettsia, and 1 (0.71%) each for either Babesia, Bartonella, or Ehrlichia. The remaining 47 (33.57%) patients were infected with multiple TBIs. These patients were treated with combination antibiotics and monitored at two subsequent follow-ups. Only 2 of 101 patients (1.98%) had discontinued treatment by the second follow-up. In the first follow-up with 118 patients, 70 (59.32%) reported pain and 48 (40.68%) had neurological symptoms. In the next follow-up of 101 patients, 41 (40.59%) had pain while 30 (29.70%) had neurological symptoms. There were statistically significant reductions in the incidence of pain (41.43%) and neurological (37.50%) symptoms between follow-ups. Thus, our study demonstrates that combination antibiotics effectively relieve TBI symptoms with good patient tolerance.
Exploring spiking neural networks: a comprehensive analysis of mathematical models and applications

This article presents a comprehensive analysis of spiking neural networks (SNNs) and their mathematical models for simulating the behavior of neurons through the generation of spikes. The study explores various models, including LIF and NLIF, for constructing SNNs and investigates their potential applications in different domains. However, implementation poses several challenges, including identifying the most appropriate model for classification tasks that demand high accuracy and low-performance loss. To address this issue, this research study compares the performance, behavior, and spike generation of multiple SNN models using consistent inputs and neurons. The findings of the study provide valuable insights into the benefits and challenges of SNNs and their models, emphasizing the significance of comparing multiple models to identify the most effective one. Moreover, the study quantifies the number of spiking operations required by each model to process the same inputs and produce equivalent outputs, enabling a thorough assessment of computational efficiency. The findings provide valuable insights into the benefits and limitations of SNNs and their models. The research underscores the significance of comparing different models to make informed decisions in practical applications. Additionally, the results reveal essential variations in biological plausibility and computational efficiency among the models, further emphasizing the importance of selecting the most suitable model for a given task. Overall, this study contributes to a deeper understanding of SNNs and offers practical guidelines for using their potential in real-world scenarios.
Normalizing Property Graphs

Normalization aims at minimizing sources of potential data inconsistency and costs of update maintenance incurred by data redundancy. For relational databases, different classes of dependencies cause data redundancy and have resulted in proposals such as Third, Boyce-Codd, Fourth and Fifth Normal Form. Features of more advanced data models make it challenging to extend achievements from the relational model to missing, non-atomic, or uncertain data. We initiate research on the normalization of graph data, starting with a class of functional dependencies tailored to property graphs. We show that this class captures important semantics of applications, constitutes a rich source of data redundancy, its implication problem can be decided in linear time, and facilitates the normalization of property graphs flexibly tailored to their labels and properties that are targeted by applications. We normalize property graphs into Boyce-Codd Normal Form without loss of data and dependencies whenever possible for the target labels and properties, but guarantee Third Normal Form in general. Experiments on real-world property graphs quantify and qualify various benefits of graph normalization: 1) removing redundant property values as sources of inconsistent data, 2) detecting inconsistency as violation of functional dependencies, 3) reducing update overheads by orders of magnitude, and 4) significant speed ups of aggregate queries.
Parental Satisfaction towards Care Given at Neonatal Intensive Care Unit and Associated Factors in Comprehensive and Referral Hospitals of Southern Ethiopia

Background Patient satisfaction is an important aspect of the quality of care in the inpatient setting. In neonatal intensive care units, parents' satisfaction and their experiences are fundamental to assessing clinical practice and improving the quality of care delivered to infants. Hence then, it reduces infant mortality rates globally. In Ethiopia, few studies address the level of parental satisfaction towards care given at neonatal intensive care unit and no single study was done in the study area. Therefore, this study is aimed at assessing parental satisfaction towards care given at neonatal intensive care unit and associated factors in comprehensive and referral hospitals of southern Ethiopia. Methods An institutional-based cross-sectional study was conducted among 401 parents who visited neonatal intensive care from March 28 to April 28, 2022. The data were assorted via a structured interviewer-administered questionnaire using ODK collect version and exported to SPSS window version 25 for further cleaning and analysis. Bivariate and multivariate logistic regressions were used to identify factors associated with parental satisfaction with care given at the neonatal intensive care unit. The adjusted odds ratio with 95% CI was used to show the strength of the association, and a P value < 0.05 was used to declare the cutoff point to determine the level of significance. Results In this study, 63% (95% CI: 58%, 68%) of the parents were satisfied with the care given at the neonatal intensive care unit. Factors associated with parental satisfaction towards care given at neonatal intensive care unit were parents with no formal education (AOR: 0.15; 95% CI: 0.07-0.31), availability of necessary information using direction indicator (AOR: 3.14; 95% CI: 1.85-5.31), and availability of enough chairs in waiting area (AOR: 3.26; 95% CI: 1.81-5.87). Conclusion Nearly two-thirds of the parents were satisfied with the care given at the neonatal intensive care unit. The availability of enough chairs in the waiting area and the creation of direction indicators are key issues to improve parental satisfaction towards their neonatal care.
Diagnosing the Ice Crystal Enhancement Factor in the Tropics

Recent modeling studies have revealed that ice crystal number concentration is one of the dominant factors in the effect of clouds on radiation. Since the ice crystal enhancement factor and ice nuclei concentration determine the concentration, they are both important in quantifying the contribution of increased ice nuclei to global warming. In this study, long-term cloud-resolving model (CRM) simulations are compared with field observations to estimate the ice crystal enhancement factor in tropical and midlatitudinal clouds, respectively. It is found that the factor in tropical clouds is ~10 3-104 times larger than that of mid-latitudinal ones, which makes physical sense because entrainment and detrainment in the Tropics are much stronger than in middle latitudes. The effect of entrainment/detrainment on the enhancement factor, especially in tropical clouds, suggests that cloud microphysical parameterizations should be coupled with subgrid turbulence parameterizations within CRMs to obtain a more accurate depiction of cloud-radiative forcing.
LAMP‐based molecular sexing in a gonochoric marine bivalve (Macoma balthica rubra) with divergent sex‐specific mitochondrial genomes

Abstract Taking advantage of the unique system of doubly uniparental inheritance (DUI) of mitochondria, we developed a reliable molecular method to sex individuals of the marine bivalve Macoma balthica rubra. In species with DUI (~100 known bivalves), both sexes transmit their mitochondria: males bear both a male‐ and female‐type mitogenome, while females bear only the female type. Male and female mitotypes are sufficiently divergent to reliably PCR‐amplify them specifically. Loop‐mediated isothermal amplification (LAMP) is a precise, economical and portable alternative to PCR for molecular sexing and we demonstrate its application in this context. We used 154 individuals sampled along the Atlantic coast of France and sexed microscopically by gonad examination to test for the congruence among gamete type, PCR sexing and LAMP sexing. We show an exact match among the sexing results from these three methods using the male and female mt‐cox1 genes. DUI can be disrupted in inter‐specific hybrids, causing unexpected distribution of mitogenomes, such as homoplasmic males or heteroplasmic females. To our knowledge, DUI disruption at the intra‐specific scale has never been tested. We applied our sexing protocol to control for unexpected heteroplasmy caused by hybridization between divergent genetic lineages and found no evidence of disruption in the mode of mitochondrial inheritance in M. balthica rubra. We propose LAMP as a useful tool to accelerate eco‐evolutionary studies of DUI. It offers the opportunity to investigate the potential role of, previously unaccounted‐for, sex‐specific patterns such as sexual selection or sex‐specific dispersal bias in the evolution of free‐spawning benthic species.
CLAIMS MANAGEMENT PRACTICES AND FIRM PROFITABILITY OF LISTED INSURANCE COMPANIES IN NIGERIA

The insurance sector provides financial protection for policyholders by pooling and investing premiums from which those who experience unforeseen losses are compensated. As a result, an efficient and timely claims settlement by insurance companies has been identified as a measure with the potential to boost the industry's growth and profitability. However, many insurance companies struggle to consistently improve their claims operations due to a poor claims process and unrecognized claims department staff, which Chief executive officers hinder their performance. This study examined the effect of Claim management practices and firm profitability of listed insurance companies in Nigeria. Survey research design was adopted. The target population of the study are the full-time top management employees of the listed insurance companies in Nigeria with a total population of 2183. Sample size of 776 was determined using Kerjcie and Morgan (1970). Proportionate stratified sampling technique was adopted. A validated questionnaire was used to collect data. Cronbach’s alpha reliability coefficients for the constructs ranged from 0.772 to 0.857. The response rate was 86.5%. Data were statistically analysed using descriptive and inferential statistics. Findings revealed that claims management practices have significant effect on profitability of the selected insurance companies in Lagos State Nigeria (Adj.R2 = 0.840; F (5, 655) = 695.900, p<0.05). 17.928, p < 0.05). The study concluded that Claims management practices dimensions have significant effect on firm profitability of listed insurance companies in Lagos State, Nigeria. The management of insurance companies in Nigeria should develop a policy to link claims management ancillaries and departments in order to make the sector profitable and sustainable in the long run. Such a policy would be the anchor of actions adopted by or proposed by the firms in matters pertaining to market dominance.
Role of Leptin and Adiponectin in Carcinogenesis

Simple Summary The involvement of leptin and adiponectin with receptors in the formation of many types of cancer as well as their impact on the clinical course of cancer patients are well established; however, the mechanisms of action of these adipokines are difficult to understand and thus need to be clarified. This review comprehensively presents in a systematized manner the implication of leptin and adiponectin in different stages of cancer development, focusing on interactions with the tumor microenvironment and its components in addition to their impact on the epithelial–mesenchymal transition and angiogenesis. A solid insight into these mechanisms is essential for the future potential use of these adipokines in cancer diagnostics and therapeutics. Abstract Hormones produced by adipocytes, leptin and adiponectin, are associated with the process of carcinogenesis. Both of these adipokines have well-proven oncologic potential and can affect many aspects of tumorigenesis, from initiation and primary tumor growth to metastatic progression. Involvement in the formation of cancer includes interactions with the tumor microenvironment and its components, such as tumor-associated macrophages, cancer-associated fibroblasts, extracellular matrix and matrix metalloproteinases. Furthermore, these adipokines participate in the epithelial–mesenchymal transition and connect to angiogenesis, which is critical for cancer invasiveness and cancer cell migration. In addition, an enormous amount of evidence has demonstrated that altered concentrations of these adipocyte-derived hormones and the expression of their receptors in tumors are associated with poor prognosis in various types of cancer. Therefore, leptin and adiponectin dysfunction play a prominent role in cancer and impact tumor invasion and metastasis in different ways. This review clearly and comprehensively summarizes the recent findings and presents the role of leptin and adiponectin in cancer initiation, promotion and progression, focusing on associations with the tumor microenvironment and its components as well as roles in the epithelial–mesenchymal transition and angiogenesis.
The PyMVPA BIDS-App: a robust multivariate pattern analysis pipeline for fMRI data

With the advent of multivariate pattern analysis (MVPA) as an important analytic approach to fMRI, new insights into the functional organization of the brain have emerged. Several software packages have been developed to perform MVPA analysis, but deploying them comes with the cost of adjusting data to individual idiosyncrasies associated with each package. Here we describe PyMVPA BIDS-App, a fast and robust pipeline based on the data organization of the BIDS standard that performs multivariate analyses using powerful functionality of PyMVPA. The app runs flexibly with blocked and event-related fMRI experimental designs, is capable of performing classification as well as representational similarity analysis, and works both within regions of interest or on the whole brain through searchlights. In addition, the app accepts as input both volumetric and surface-based data. Inspections into the intermediate stages of the analyses are available and the readability of final results are facilitated through visualizations. The PyMVPA BIDS-App is designed to be accessible to novice users, while also offering more control to experts through command-line arguments in a highly reproducible environment.
Review of visitor research for the Department of Conservation

This report presents information relevant to the proposed Visitor Research Strategy for the Department of Conservation (DOC). It identifies the state of knowledge for visitor research by reviewing the New Zealand outdoor recreation research literature and selected international literature reviews. In particular, it highlights research gaps. The implications of these research deficiencies for DOC are discussed. To achieve these goals, the Visitor Research Framework is presented to define the scope of visitor research relevant to DOC and to structure the discussion. Analysis of the research literature and assessment of management information requirements highlights the need for a Visitor Research Strategy by concluding that a wide array of gaps in knowledge about recreation, its effects and management is evident. Disparate methods throughout the research literature have compounded the problem of comparison across studies and inhibited trend analysis. DOC documents fail to delimit and prioritise visitor research in a cohesive framework. Direction is required to coalesce effort and better integrate interests across the broad range of recreation researchers.
“GeSn Rule-23”—The Performance Limit of GeSn Infrared Photodiodes

Group-IV GeSn photodetectors (PDs) compatible with standard complementary metal–oxide-semiconductor (CMOS) processing have emerged as a new and non-toxic infrared detection technology to enable a wide range of infrared applications. The performance of GeSn PDs is highly dependent on the Sn composition and operation temperature. Here, we develop theoretical models to establish a simple rule of thumb, namely “GeSn−rule 23”, to describe GeSn PDs’ dark current density in terms of operation temperature, cutoff wavelength, and Sn composition. In addition, analysis of GeSn PDs’ performance shows that the responsivity, detectivity, and bandwidth are highly dependent on operation temperature. This rule provides a simple and convenient indicator for device developers to estimate the device performance at various conditions for practical applications.
The Architecture of Perceptual Spatial

Lateral interactions between spatial filters were explored with a lateral masking paradigm. Contrast sensitivity (two-alternative forced-choice) for a Gabor signal in the presence of two flanking high contrast Gabor signals (masks) was measured. When the target to mask distance was less than 2 target wavelengths the contrast sensitivity decreased up to a factor of two relative to a no mask condition. At larger separations, up to eight wavelengths, an increase in contrast sensitivity occurred. This increase was maximal at separation distances of 2-3 wavelengths, where sensitivity increased by a factor of two. However, the enhancement magnitude and range was dependent on tie offset between the Gabor signal orientation and the direction defined by the virtual line connecting the two masks (global orientation). Maximal effects occurred when this offset was zero (100% increase in sensitivity) and 90 deg (50% increase). A 45 deg offset yielded only a small enhancement (20%). The enhancement dependence on spatial arrangement was found to be invariant across different global orientations (meridian). This pattern of interactions may be involved in grouping collinear line segments into smooth curves.