Perfect Fit Research Articles

Synthesis, Structural and Magnetic Characterization of Superparamagnetic Ni0.3Zn0.7Cr2−xFexO4 Oxides Obtained by Sol-Gel Method

The sol-gel process was used to produce ferrite Ni0.3Zn0.7Cr2−xFexO4 compounds with x = 0, 0.4, and 1.6, which were then subsequently calcined at several temperatures up to 1448 K for 48 h in an air atmosphere. X-ray diffraction (XRD), scanning electron microscopy (SEM), vibrating sample magnetometer (VSM), and 57Fe Mössbauer spectrometry were used to examine the structure and magnetic characteristics of the produced nanoparticles. A single-phase pure Ni0.3Zn0.7Cr2−xFexO4 nanoparticle had formed. The cubic Fd3¯m spinel structure contained indexes for all diffraction peaks. The crystallite size is a perfect fit for a value of 165 ± 8 nm. Based on the Rietveld analysis and the VSM measurements, the low magnetization Ms of Ni0.3Zn0.7Cr2−xFexO4 samples was explained by the absence of ferromagnetic Ni2+ ions and the occupancy of Zn2+ ions with no magnetic moments in all tetrahedral locations. Moreover, because of the weak interactions between Fe3+ ions in the octahedral locations, the magnetization of the current nanocrystals is low or nonexistent. According to Mössbauer analyses, the complicated hyperfine structures are consistent with a number of different chemical atomic neighbors, such as Ni2+, Zn2+, Cr3+, and Fe3+ species that have various magnetic moments. A Fe-rich neighbor is known to have the highest values of the hyperfine field at Fe sites, while Ni- and Cr-rich neighbors are responsible for the intermediate values and Zn-rich neighbors are responsible for the quadrupolar component.

Invisible, Responsible Women in Sweden – Planning Pregnancies, Choosing Contraceptives

ABSTRACT In this study I explore discourses of contraception and reproduction, which are drawn upon and reproduced in Swedish official online sources on contraceptive advice, through the theoretical frameworks of biomedicalization and reproductive justice. The analysis yielded three interwoven themes: 1) women in need of contraceptives have to balance discourses of exogenous hormones as both an “unnatural” threat to their bodies and as desirable, effective regulators of the same “naturally unruly” body; 2) in search of a “perfect contraceptive fit”, it is the woman who needs to accommodate to available methods, rather than the other way around; 3) women are made discursively invisible, while simultaneously being constructed as individually responsible for reproduction. Underpinning all these themes is the discourse of rational, responsible choices, of exerting agency by choosing the right contraceptive. In the era of biomedicalization, finding a “contraceptive fit” becomes a moral and gendered health practice demanding thorough self-surveillance. The rational woman, exercising control over her reproduction and body, by planning her pregnancy with safe contraceptives, emerges as the only possible position. Recognizing that women’s and fertile person’s reproductive choices are made amid a societal context, with differing personal resources and experiences, would bring us even closer to reproductive justice.

Shari Leventhal: Pitching in to Support CSE

Having worked at the American Society of Nephrology (ASN) for 20 years, Shari Leventhal has seen a lot of change in scholarly societies and scientific publishing. Beginning in the Communications department at ASN, Shari became a Managing Editor in 2012 for the Clinical Journal of the American Society of Nephrology (CJASN) and then the Executive Editor of the ASN portfolio of journals in March 2019. As she begins her term as the President of the Council of Science Editors, Shari spoke with Science Editor about her goals for CSE this year, the importance of accessibility, and the need to sometimes step up and get things done. Science Editor: How did you get involved in scientific editing and publishing, and what career path led to your current position? Shari Leventhal: My background was in communications, and I was working in public relations for ASN, but I didn’t really love the pressure of being put on the spot. My supervisor at the time was looking for a second Managing Editor to assume oversight for the clinical journal, and believed that my skill set would be the perfect fit to manage the journal. When she approached me with the opportunity, I was intrigued. I love managing multiple projects at once and improving efficiency. Additionally, I had worked with the Editor in Chief previously and liked him quite a bit. I thought that if I was going to move into scholarly publishing, he would be a great EIC to work with. SE: What […]

Innovate and Stockpile: Respiratory Protection for Essential Workers in a Catastrophic Pandemic.

Innovate and Stockpile: Respiratory Protection for Essential Workers in a Catastrophic Pandemic.

A novel and efficient Wavelet Scattering Transform approach for primitive-stage dyslexia-detection using electroencephalogram signals

Dyslexia is a neurological disorder affecting reading and writing abilities. Early intervention is important for affected individuals’ social and academic development. The accuracy and objectivity limitations of traditional dyslexia detection systems based on behavioral symptoms and standard tests can pose challenges to the early detection of the condition. In response, an electroencephalogram (EEG) based detection method has been proposed to aid medical professionals in addressing these limitations. A comparison is made between the Wavelet Scattering Transform (WST) approach and three other approaches, namely Spectral Statistical Features (SSF), Connectivity Features with Autoencoders (CFA), and Hybrid Features (HF), using two datasets. These two datasets were chosen for various reasons, including the fact that they were collected during different tasks and from different countries. Another significant factor is that the age range of the participants was 7 and 12 years old, marking the beginning of their educational journey. This age range is ideal for detecting dyslexia in its primitive stages, making these datasets a perfect fit for this research. The performance evaluation of the approaches involved utilizing Support Vector Machine (SVM) classifiers with three non-linear kernels and k-fold cross-validation implementation. The findings suggest that the other three approaches could not achieve more than 80% accuracy, and their accuracy results were inconsistent with each dataset. In contrast, the WST approach achieved a high accuracy rate, with an average accuracy of 96.96% and 97.12% for dataset 1 and dataset 2, respectively, using the Radial Basis Function (RBF) kernel. The accuracy of WST features is further improved to 98.72% and 98.67% through the Majority Voting method. These findings demonstrate the effectiveness and generalization of the WST approach.

Lithium hydroxide as a high capacity adsorbent for CO2 capture: experimental, modeling and DFT simulation

In this work, the potential of monohydrate Lithium hydroxide (LiOH) as a high capacity adsorbent for CO2 capture was investigated experimentally and theoretically. The effects of operating parameters, including temperature, pressure, LiOH particle size and LiOH loading, on the CO2 capture in a fixed-bed reactor have been experimentally explored using response surface methodology (RSM) based on central composite design. The optimum conditions obtained by the RSM for temperature, pressure, mesh and maximum adsorption capacity were calculated as 333 K, 4.72 bar, 200 micron and 559.39 mg/g, respectively. The experiments were evaluated using isotherm, kinetic and thermodynamic modeling. Isotherm modeling showed that Hill model could deliver a perfect fit to the experimental data, based on the closeness of the R2-value to unity. The kinetics models showed that the process was chemical adsorption and obeyed the second order model. In addition, thermodynamic analysis results showed that the CO2 adsorption was spontaneous and exothermic in nature. In addition, based on the density functional theory, we investigated the chemical stability of LiOH atomic clusters and examined the effects of LiOH nanonization on the physical attraction of carbon dioxide.

A Perfect Fit: 3D-Printed Kit to Teach Students Principles of Antigen-Antibody Recognition and Herd Immunity

Abstract The immunological principles underlying vaccines are a critical part of understanding human health and disease, but are typically not included in general K-12 education curriculum. The COVID-19 pandemic has underscored both the power of science and the importance of science literacy for our country. Though multifactorial, vaccine hesitancy is associated with patients’ lack of information surrounding vaccine biology. Recognizing this gap, we aimed to develop innovative learning activities that would distill the complex concepts of adaptive immunity and herd immunity to make them accessible to middle and high school students. Herein, we present one such learning activity intended to help students visualize the structural features of an antibody and the specificity of antibody-antigen interactions. Each student is provided with a base 3D-printed antibody, along with three sets of exchangeable variable domains and three model pathogens. Students explore the ability of their antibody combinations to recognize different pathogens, learning the structure and specificity of the antibody and the role they play in fighting pathogens. The set of kits for a classroom are distinct, with kits sharing some, but not all, variable regions. This feature allows for modeling of herd immunity and how different infections spread through a community depending on vaccination rates. This tangible model therefore can convey to students how vaccines elicit protection against pathogens at both an individual and population level. Inclusion of this learning activity during STEM outreach events or integration into classroom curriculum provides an opportunity for early educational intervention that would promote vaccine literacy in our communities.

A Republic of the Imagination: In Conversation with Azar Nafisi

A Republic of the ImaginationIn Conversation with Azar Nafisi Daniel Simon (bio) and Azar Nafisi (bio) Click for larger view View full resolution [End Page 31] Click for larger view View full resolution PHOTO BY YOUSEF AL-ABDULLAH Fiction, storytelling, is the bearer, the carrier of empathy. Click for larger view View full resolution With her latest book of essays, Read Dangerously: The Subversive Power of Literature in Troubled Times (2022), Iranian American writer Azar Nafisi offers a "resistance reading list" that the Washington Post hails as offering "a new canon for the tyrannies of the present and the dystopian possibilities of the future." Over Zoom, we discussed the power of storytelling embodied by Scheherazade and Alice in Wonderland; the intergenerational threads that connect readers; and the role of writers and readers in preserving memory and defending truth. [End Page 32] Daniel Simon: We're talking today about your newest book, Read Dangerously, which I really love—thank you so much for writing it. I think it's a perfect fit for the theme of our May issue, which is called "The Future of the Book." And it's an opportune moment to speak with you about your own passion for reading, writing, and books and how they've played such a large part in your life. In the epistolary genre consisting of letters to "Baba," your late father, you write beautifully in Read Dangerously about the intergenerational thread that connects teachers and readers, such as your parents, Nezhat and Ahmad, to your own children and now your grandchildren; Professor James Yoch here at the University of Oklahoma and your student Razieh in Tehran; even your own reading of writers from Plato to James Baldwin, Toni Morrison, and Margaret Atwood during the 1970s and then again more recently as you are composing these letters. If a student in Norman or Tehran were to ask you what it means to read dangerously in 2023, what would you tell them? Azar Nafisi: Well, this book is partly a response to the trend I had noticed, especially in the US, where we use books as comfort food. We read them not in order to be disturbed or find something new, but we read them in order for them to confirm what we already know, at times to confirm our prejudices: "Why don't they speak what I want them to?" So, there's no challenge—we're uncomfortable with challenge. We want to eliminate rather than create an exchange. And so, for me, reading dangerously means that we take that risk to read in order to be disturbed. As James Baldwin says, artists are here to disturb the peace. Writers are not here to warm the cockles of your heart. For me, the best example of a good reader or a reader who takes risks is Alice in Wonderland. Out of millions of little girls, there's this one little girl who is bored with the routine of her life, and she's after something different. What makes Alice so exceptional is the fact that she has what Nabokov calls the third eye of the imagination. She sees not just reality in terms of appearances, but she also sees beyond reality, the magic of reality. And she sees not only a white rabbit but a white rabbit who talks and wears a waistcoat and a watch. She runs after that white rabbit, not saying, like some of our readers, that this is not how rabbits act. She risks going into the world of the white rabbit. And when she jumps into that hole, she doesn't say, Am I going to survive this? What's going to happen to me next? And her reward, of course, is the world—everything, every creature in that world, has a sign of being in her real life, but she's now seeing them in a new light. Her vision of reality is changing as she goes from one person to another. The last thing that I want to say about Alice, which I think is really important, is that like all good stories, it challenges and questions, not just the world outside but the reader...

Optimization of Landing Gear Mechanism using Generative Design

Abstract: Combining evolutionary algorithms with additive manufacturing (AM) techniques, new material approaches, in aerospace and industrial applications can result in advanced design procedures. This combination adds extra degrees of flexibility to the final design concept, enabling multifunctional designs. Aerospace, which is heavily focused on customised production, is a perfect fit for AM due to its effects on economies of scale and scope. These technologies are prepared to be included within the generative design process for safety-critical contexts, including the aerospace, thanks to novel structural materials and advanced AM processes. The three primary phases of conventional aircraft design are conceptual design, preliminary design, and detailed design. Multidisciplinary optimization processes are currently being developed to support designer in assessing the optimal solution. Generative Design is a novel form-finding process that takes into account structural performance, material properties and ergonomic demand. Evolutionary design approaches limits to numerical optimization, while Topology Optimization seeks to find an optimal structural configuration within a given design domain for specified objectives, constraints, loads and boundary conditions. This paper focuses on creating appropriate generative design models which can sustain same amount of stresses as of the original model. In the current study the optimization of Boeing 747’s nose landing gear is depicted using solidworks and fusion 360. Static structural analysis is utilized to evaluate the effects of stresses and failure mode produced by various materials, in order to figure out a materials characteristic as well as for material selection. Additionally, this paper examines original and generative design models

Fitting Type Ia Supernova Data to a Cosmological Model Based on Einstein–Newcomb–De Sitter Space

Einstein–Newcomb–de Sitter (ENdS) space is de Sitter’s modification of spherical space used by Einstein in his first cosmological model paper published in 1917. The modification by de Sitter incorporated the topological identification of antipodal points in space previously proposed by Newcomb in 1877. De Sitter showed that space topologically modified in this way (called elliptical or projective space) satisfies Einstein’s field equations. De Sitter also found that in a space with constant positive curvature, spectral lines of remote galaxies would be red-shifted (called the de Sitter effect). However, de Sitter’s formulae relating distances to red shifts do not satisfy observational data. The likely reason for this mismatch is that de Sitter mainly focused on space curvature and ignored the identification of antipodal points. Herein, we demonstrate that it is this particular feature that allows an almost perfect fit of the ENdS-based cosmological model to observational data. We use 1701 sources from the type Ia supernovae data sample called Pantheon+, which was previously used to fit the ΛCDM model. ΛCDM and ENdS diverge in their predictions for red shifts exceeding z∼2.3. Since there are no available type Ia supernovae (SNe) data for higher red shifts, both models can be validated by using an additional sample of 193 gamma-ray bursts (GRBs) spanning red shifts up to z∼8. This validation shows that the minimum χ2 for the SNe+GRBs sample is about 2.7% smaller for the ENdS space model than for the ΛCDM model.

Fe-Gd Ferromagnetic Cyclic Coordination Cluster [FeIII4GdIII4(teaH)8(N3)8(H2O)] with Magnetic Anisotropy─Theory and Experiment.

The synthesis, structural, and magnetic characterization of [FeIII4LnIII4(teaH)8(N3)8(H2O)] (Ln = Gd and Y) and the previously reported isostructural Dy analogue are discussed. The commonly held belief that both FeIII and GdIII can be regarded as isotropic ions is shown to be an oversimplification. This conclusion is derived from the magnetic data for the YIII analogue in terms of the zero-field splitting seen for FeIII and from the fact that the magnetic data for the new GdIII analogue can only be fit employing an additional anisotropy term for the GdIII ions. Furthermore, the Fe4Gd4 ring shows slow relaxation of magnetization. Our analysis of the experimental magnetic data employs both density functional theory as well as the finite-temperature Lanczos method which finally enables us to provide an almost perfect fit of magnetocaloric properties.

IOT Based Smart Cart System

The use of trolleys in the shopping industry has always been very popular, especially among customers who frequently stop by the mall or supermarket to shop for their necessities. People need trolleys to make it easier for them to carry their groceries and other luggage. There are various types of trolleys according to their respective uses. Still, the trolleys in the shopping industry commonly used today can only help users carry goods from one place to another. However, this traditional type of trolley is still lacking in being a perfect fit in the shopping industry. It does not help reduce the crowds and the enormous queue in terms of inconvenience. In metro cities purchasing and shopping at super shops, big malls is a daily activity. At the billing counter the customer will prepare the bill using bar code reader which is a time-consuming process and will creates the long queues at billing counters. By implementing this smart machine, it will minimize human efforts and also automate the billing procedure. So, in our prototype we are using RFID technology for identification of the purchased product and it reduces the scanning time of the consumer. Key Word: Customers, Billing, Time Consuming, Smart Machine, Scanning Time.

A review on 3D printed implant for oral and maxillofacial surgery

The oral and maxillofacial disorder can cause discomfort and affects the quality of life. Different implants and prosthetics were studied that provide restoration of form and function, reduction of pain and maintenance of jaw bone height. The study focuses on different 3D printed implants and clinical indications used to treat oral and maxillofacial disorders and along with different prosthetics used in surgery, made with the help of additive manufacturing techniques. Biocompatible materials like titanium and poly ether ether ketone (PEEK) are used for 3D printing and their effects on surrounding bone were studied. With the advancement in technology 3D printing gave a perfect fit in method with reduced time and complications. Computer-aided design software helps to diagnose problems along with the possible solutions through design and developments in dentistry. 3D printing is an innovative technology that helps to build patient-specific implants using biocompatible material and helps in planning before the surgery. 3D printing is a cheap and fast technology where advanced biocompatible materials are used to manufacture patient specific implants which are light in weight, complex in geometry, and produced faster than the traditional method. 3D printing technology and 3D printed implants are highly demanded all across the world.

In silico analysis of ACE2 from different animal species provides new insights into SARS-CoV-2 species spillover.

Aim: This study aimed to analyze the phylogenetic relationships between the ACE2 of humans and other animals and investigate the potential interaction between SARS-CoV-2 RBD and ACE2 of different species. Materials & methods: The phylogenetic construction and molecular interactions were assessed using computational models. Results & conclusion: Despite the evolutionary distance, 11 species had a perfect fit for the interaction between their ACE2 and SARS-CoV-2 RBD (Chinchilla lanigera, Neovison vison, Rhinolophus sinicus, Emballonura alecto, Saccopteryx bilineata, Numida meleagris). Among them, the avian N. meleagris was reported for the first time in this study as a probable SARS-CoV-2 host due to the strong molecular interactions. Therefore, predicting potential hosts for SARS-CoV-2 for understanding the epidemiological cycle and proposal of surveillance strategies.

Computed tomography texture analysis combined with preoperative clinical factors serve as a predictor of early efficacy of transcatheter arterial chemoembolization in hepatocellular carcinoma.

To investigate a pre-therapeutic radiomics nomogram to accurately predict hepatocellular carcinoma (HCC) lesion responses to transcatheter arterial chemoembolization (TACE). This retrospective study from January 2012 to 2022 included 92 TACE-treated patients who underwent liver contrast-enhanced CT scan 7days before treatment, having complete clinical information. We extracted quantitative texture parameters and clinical factors for the largest tumors on the baseline arterial and portal venous phase CT images. An adaptive least absolute shrinkage and selection operator (LASSO)-penalized logistic regression identified independent predictors of tumor activity after TACE. We fitted an adaptive LASSO regression model to narrow down the texture features and clinical risk factors of the tumor activity status. The selected texture features were used to construct radiomic scores (RadScore), which demonstrated superior performance in predicting tumor activity on both the training (area under the curve (AUC): 0.881, 95% CI: 0.799-0.963) and testing sets (AUC: 0.88, 95% CI: 0.726-1). A logistic regression-based nomogram was developed using RadScore and four selected clinical features. In the testing set, nomogram total points were significant predictors (P = 0.034), and the training set showed no departure from perfect fit (P = 0.833). Internal validation of the nomogram was obtained for the training (AUC: 0.91, 95% CI: 0.837-0.984) and testing (AUC: 0.889, 95% CI: 0.746-1) sets. We propose a nomogram to predict the early response of HCC lesions to TACE treatment with high accuracy, which may serve as an additional criterion in multidisciplinary decision-making treatment.

APPLICATION OF GEOELECTRICAL METHOD TO STUDY GROUNDWATER POTENTIAL IN ISARA, REMO NORTH MUNICIPAL AREA OF OGUN STATE, NIGERIA.

Fifteen (15) Vertical Electrical Sounding (VES) and three (3) Constant Separation Traversing (CST) data were acquired within the study area using Pasi Terrameter (model 16GL). The Schlumberger electrode array was deployed for the VES while Wenner array was used for the 2-D CST. Both qualitative and quantitative approach were used for the VES measurements. The raw data were Curve-matched and inversion of the data using WinResist (1.0) to create a model of perfect fit indicating layer thickness and resistivity values for individual layers while the 2D resistivity data were processed using Res2Dinv software. The 2D resistivity structures revealed the lateral and the vertical variations of the subsurface information having resistivity values ranging from 81.8 to 5250 Ωm. The geoelectric sections revealed five to six geoelectric layers, which correspond to the topsoil, clayey sand, lateritic clayey sand and sand. The topsoil is characterized by resistivity values ranging from 29.8 to 358.5 Ωm and layer thickness of 0.6 to 0.8 m. The clayey sand had resistivity and layer thickness values ranging from 81.4 to 278.0 Ωm and 2.4 to 7.1 m respectively. The lateritic clayey sand had resistivity values ranging from 782.0 to 2414.1 Ωm. and layer thickness of 5.4 to 61.2 m. The sand in the third layer in VES 1 to 7, 9 and 10 has resistivity values ranging from 398.6 to 600.7 Ωm and layer thickness of 2.3 to 25 3 m is characterized as seasonal aquifer. The result of this study has further highlighted the capabilities of the electrical resistivity techniques in groundwater investigation

An application of virtual twins for fit prediction: case study of women jackets

PurposeThe purpose of this paper is to present a fit prediction case study of virtual twins of women jacket. For this reason, several basic principles of clothes fit prediction were developed and verified.Design/methodology/approachTo develop the principles of fit prediction, the women's jacket sleeve was selected as the study object. The study objects were categorized into three types: the patterns and two virtual sleeves generating on full avatar from Clo3D and on dummy (arm partly removed). Through series of subjective and objective evaluation experiments, the relationship between the similar indexes of the patterns and the virtual sleeves was built, including fit criteria range, the categorization of the indexes in terms of its sensitiveness, and the linear regressions to predict several indexes of virtual sleeves after its pattern parameterization. The results obtained were verified in case study by the virtual and real sleeves generating.FindingsThe proposed principles of clothing fit prediction based on parallel research of the flat patterns and its virtual 3D shapes. The principles include the choosing of virtual twins of human body for virtual try-on, the establishing of indexes common schedule for patterns and virtual sleeves, the creation of criteria and its ranges for perfect fit and poor fit evaluation, and the application of existing relations between the patterns and the sleeves for predicting indexes responsible for fit.Research limitations/implicationsThe authors propose and verify the validity of the principles to predict several parameters of virtual 3D sleeve of women's jacket which are forming the level of fit. The result of this study can be used to convenient fit prediction and to find the misfit reasons.Practical implicationsThis study developed basic principles for predicting the fit of the clothing through the virtual simulation and the statistical analysis. Through studying the jacket sleeve, the several related ranges, the row of more sensitive indexes, and the equations were presented and verified, which certified the validity of proposed principles.Social implicationsThe results can effectively predict the sleeve fit before sewing, which reduce the time and materials cost and the operator's skill requirements.Originality/valueThe authors propose and verify the validity of the principles to predict several parameters of virtual 3D sleeve of women's jacket which form the level of fit. The result of this study can be used for convenient fit prediction and to find the misfit reasons.

Development of Nanostructured Bi2Te3 with High Thermoelectric Performance by Scalable Synthesis and Microstructure Manipulations

Nanostructuring of thermoelectric (TE) materials leads to improved energy conversion performance; however, it requires a perfect fit between the nanoprecipitates' chemistry and crystal structure and those of the matrix. We synthesize bulk Bi2Te3 from molecular precursors and characterize their structure and chemistry using electron microscopy and analyze their TE transport properties in the range of 300-500 K. We find that synthesis from Bi2O3 + Na2TeO3 precursors results in n-type Bi2Te3 containing a high number density (Nv ∼ 2.45 × 1023 m-3) of Te-nanoprecipitates decorating the Bi2Te3 grain boundaries (GBs), which yield enhanced TE performance with a power factor (PF) of ∼19 μW cm-1 K-2 at 300 K. First-principles calculations validate the role of Te/Bi2Te3 interfaces in increasing the charge carrier concentration, density of states, and electrical conductivity. These optimized TE coefficients yield a promising TE figure of merit (zT) peak value of 1.30 at 450 K and an average zT of 1.14 from 300 to 500 K. This is one of the cutting-edge zT values recorded for n-type Bi2Te3 produced by chemical routes. We believe that this chemical synthesis strategy will be beneficial for future development of scalable n-type Bi2Te3 based devices.

Development and validation of a predictive nomogram for sarcopenia among older people in China.

Development and validation of a predictive nomogram for sarcopenia among older people in China.

The interplay between spatiotemporal overlap and morphology as determinants of microstructure suggests no ‘perfect fit’ in a bat-flower network

Plant–pollinator interactions in diverse tropical communities are often predicted by a combination of ecological variables, yet the interaction drivers between flower-visiting bats and plants at the community level are poorly understood. We assembled a network between Neotropical bats and flowering plants to describe its macrostructure and to test the role of neutral and niche variables in predicting microstructure. We found a moderately generalized network with internally nested modules comprising functionally similar plant and bat species. Modules grouped bats and plants with matching degrees of specialization but had considerable overlap in species morphologies and several inter-module interactions. The spatiotemporal overlap between species, closely followed by morphology, and not abundance, were the best predictors of microstructure, with functional groups of bats also interacting more frequently with plants in certain vegetation types (e.g., frugivores within forests) and seasons (e.g., long-snouted nectarivores in the dry season). Therefore, flower-visiting bats appear to have species-specific niche spaces delimited not only by their ability to exploit certain flower types but also by preferred foraging habitats and the timing of resource availability. The prominent role of resource dissimilarity across vegetation types and seasons likely reflects the heterogeneity of Neotropical savannas, and further research in biomes beyond the Cerrado is needed to better understand the complexity of this system.