bluuebunny/crossref_metadata_2025 huggingface dataset:
Women Development Related Policies in Pakistan: A Preliminary Gap Analysis
Authors: Khalid Javaria , Othman Nooraini , Wan Zakaria Wan Normeza
Published: July 2023

Women living in third-world countries, such as Pakistan, often face the perception of being less competent and less significant participants in national development. In the Pakistani context, this situation can be attributed, among other factors, to the lack of tangible policies ensuring women's access to key decision-making positions and opportunities for career development. This paper aims to examine the major policies concerning women that have been formulated over the years in the form of acts and laws. Additionally, the study highlights the inadequate attention given by Pakistani policymakers to acts or bills that would facilitate women's career development. The research reveals that the National Commission on the Status of Women (NCWS) in 2012 and subsequent initiatives in 2014, 2016, and 2018 do not fully address the issues related to women's career development. Furthermore, the study uncovers a gap between the policy measures outlined in the first national-level policy for women in 2002, which encompass social, economic, and political dimensions, and their implementation in assisting Pakistani women in their career development. Therefore, this study makes a significant contribution by promoting research on women's status, not only by reporting factors of gender discrimination and cultural restraints but also by analyzing the historical development of official policies and the implementation gap concerning women's career development in Pakistan.
Dynamic robotic tracking of underwater targets using reinforcement learning
Authors: Masmitja I. , Martin M. , O’Reilly T. , Kieft B. , Palomeras N. , Navarro J. , Katija K.
Published: July 2023

To realize the potential of autonomous underwater robots that scale up our observational capacity in the ocean, new techniques are needed. Fleets of autonomous robots could be used to study complex marine systems and animals with either new imaging configurations or by tracking tagged animals to study their behavior. These activities can then inform and create new policies for community conservation. The role of animal connectivity via active movement of animals represents a major knowledge gap related to the distribution of deep ocean populations. Tracking underwater targets represents a major challenge for observing biological processes in situ, and methods to robustly respond to a changing environment during monitoring missions are needed. Analytical techniques for optimal sensor placement and path planning to locate underwater targets are not straightforward in such cases. The aim of this study was to investigate the use of reinforcement learning as a tool for range-only underwater target-tracking optimization, whose promising capabilities have been demonstrated in terrestrial scenarios. To evaluate its usefulness, a reinforcement learning method was implemented as a path planning system for an autonomous surface vehicle while tracking an underwater mobile target. A complete description of an open-source model, performance metrics in simulated environments, and evaluated algorithms based on more than 15 hours of at-sea field experiments are presented. These efforts demonstrate that deep reinforcement learning is a powerful approach that enhances the abilities of autonomous robots in the ocean and encourages the deployment of algorithms like these for monitoring marine biological systems in the future.
Expression of the excitatory opsin ChRERα can be traced longitudinally in rat and nonhuman primate brains with PET imaging
Authors: Bonaventura Jordi , Boehm Matthew A. , Jedema Hank P. , Solis Oscar , Pignatelli Marco , Song Xiaowei , Lu Hanbing , Richie Christopher T. , Zhang Shiliang , Gomez Juan L. , Lam Sherry , Morales Marisela , Gharbawie Omar A. , Pomper Martin G. , Stein Elliot A. , Bradberry Charles W. , Michaelides Michael
Published: July 2023

Optogenetics is a widely used technology with potential for translational research. A critical component of such applications is the ability to track the location of the transduced opsin in vivo. To address this problem, we engineered an excitatory opsin, ChRERα (hChR2(134R)-V5-ERα-LBD), that could be visualized using positron emission tomography (PET) imaging in a noninvasive, longitudinal, and quantitative manner. ChRERα consists of the prototypical excitatory opsin channelrhodopsin-2 (ChR2) and the ligand-binding domain (LBD) of the human estrogen receptor α (ERα). ChRERα showed conserved ChR2 functionality and high affinity for [
18
F]16α-fluoroestradiol (FES), an FDA-approved PET radiopharmaceutical. Experiments in rats demonstrated that adeno-associated virus (AAV)–mediated expression of ChRERα enables neural circuit manipulation in vivo and that ChRERα expression could be monitored using FES-PET imaging. In vivo experiments in nonhuman primates (NHPs) confirmed that ChRERα expression could be monitored at the site of AAV injection in the primary motor cortex and in long-range neuronal terminals for up to 80 weeks. The anatomical connectivity map of the primary motor cortex identified by FES-PET imaging of ChRERα expression overlapped with a functional connectivity map identified using resting state fMRI in a separate cohort of NHPs. Overall, our results demonstrate that ChRERα expression can be mapped longitudinally in the mammalian brain using FES-PET imaging and can be used for neural circuit modulation in vivo.
Supplemental Material: Cosmogenic 3He anomaly K1 vs. the early Campanian isotopic event (ECE) as recorded in pelagic limestones of the Umbria-Marche succession (Italy)
Authors: Montanari A. , et al.
Published: July 2023

Tables S1 and S2.
Patient and professional perspectives about using in vitro fertilisation add-ons in the UK and Australia: a qualitative study
Authors: Armstrong Sarah C , Vaughan Emily , Lensen Sarah , Caughey Lucy , Farquhar Cynthia M , Pacey Allan , Balen Adam H , Peate Michelle , Wainwright Elaine
Published: July 2023

Objectives

In vitro fertilisation (IVF) add-ons are additional procedures offered alongside an IVF cycle with the aim of improving live birth rates. They are controversial because of the paucity of evidence to support their efficacy and safety, alongside the additional financial cost they often pose to patients. Despite this, they are popular. However, there is limited qualitative research regarding their use. The aims of the VALUE Study were to understand the decision-making process surrounding using or recommending add-ons; report sources of information for add-ons; and explore concerns for safety and effectiveness when considering their use.

Design

‘VALUE’ is a qualitative semistructured interview study using inductive thematic analysis of anonymised transcriptions.

Setting

Participants were recruited from a broad geographical spread across the UK and Australia from public and private clinical settings.

Participants

Patients (n=25) and health professionals (embryologists (n=25) and clinicians (n=24)) were interviewed. A purposive sampling strategy was undertaken. The sampling framework included people having state-subsidised and private cycles, professionals working in public and private sectors, geographical location and professionals of all grades.

Results

Patients often made decisions about add-ons based on hope, minimising considerations of safety, efficacy or cost, whereas professionals sought the best outcomes for their patients and wanted to avoid them wasting their money. The driving forces behind add-on use differed: for patients, a professional opinion was the most influential reason, whereas for professionals, it was seen as patient driven. For both groups, applying the available evidence to individual circumstances was very challenging, especially in the sphere of IVF medicine, where the stakes are high.

Conclusions

There is scope to build on the quality of the discourse between patients and professionals. Patients describe valuing their autonomy with add-ons, but for professionals, undertaking informed consent will be critical, no matter where they sit on the spectrum regarding add-ons.

Trial registration

osf.io/vnyb9.
Prognostic value of spinal cord lesion measures in early relapsing-remitting multiple sclerosis
Authors: Lauerer Markus , McGinnis Julian , Bussas Matthias , El Husseini Malek , Pongratz Viola , Engl Christina , Wuschek Alexander , Berthele Achim , Riederer Isabelle , Kirschke Jan S , Zimmer Claus , Hemmer Bernhard , Mühlau Mark
Published: July 2023

Background

Spinal cord (SC) lesions have been associated with unfavourable clinical outcomes in multiple sclerosis (MS). However, the relation of whole SC lesion number (SCLN) and volume (SCLV) to the future occurrence and type of confirmed disability accumulation (CDA) remains largely unexplored.

Methods

In this monocentric retrospective study, SC lesions were manually delineated. Inclusion criteria were: age between 18 and 60 years, relapsing-remitting MS, disease duration under 2 years and clinical follow-up of 5 years. The first CDA event after baseline, determined by a sustained increase in the Expanded Disability Status Scale over 6 months, was classified as either progression independent of relapse activity (PIRA) or relapse-associated worsening (RAW). SCLN and SCLV were compared between different (sub)groups to assess their prospective value.

Results

204 patients were included, 148 of which had at least one SC lesion and 59 experienced CDA. Patients without any SC lesions experienced significantly less CDA (OR 5.8, 95% CI 2.1 to 19.8). SCLN and SCLV were closely correlated (rs=0.91, p<0.001) and were both significantly associated with CDA on follow-up (p<0.001). Subgroup analyses confirmed this association for patients with PIRA on CDA (34 events, p<0.001 for both SC lesion measures) but not for RAW (25 events, p=0.077 and p=0.22).

Conclusion

Patients without any SC lesions are notably less likely to experience CDA. Both the number and volume of SC lesions on MRI are associated with future accumulation of disability largely independent of relapses.
Early prehabilitation in suspected locally advanced and metastatic lung cancer
Authors: Phillips Iain , Petrie Rebecca , Allan Lindsey , Hall Peter , Walton Abi , McMillan Debbie , Peacock Catriona , Primrose Lorraine , Vallet Mahéva , Mencnarowksi Julie , MacDonald Neil , Mackean Melanie , Barrie Colin
Published: July 2023

Objectives

The most common treatment for locally advanced and metastatic lung cancer is best supportive care. Patients with lung cancer are often comorbid with a high symptom burden. We wanted to assess whether early prehabilitation was feasible in patients with likely lung cancer.

Methods

Patients were offered prehabilitation if they were attending the new patient respiratory clinic, had a CT scan suggesting stage III or IV lung cancer and undergoing further investigations. Patients receiving palliative care were ineligible. All prehabilitation patients were referred to a palliative medicine physician, registered dietitian and rehabilitation physiotherapist.

Results

50 patients underwent prehabilitation between June 2021 and August 2022. The median age was 72 years (range 54–89 years). 48 patients had lung cancer. 84% of patients attended all three interventions.

Half of the palliative care consultations focused on pain. Half of the patients seen had a change in medication. 25% of patients’ weights were stable, 32% required a food-first strategy and 33% required oral nutritional supplements. 57% of patients discussed managing breathlessness with the physiotherapist.

Conclusions

Early prehabilitation is feasible alongside the investigation of locally advanced and metastatic lung cancer. Further work will aim to assess its impact on admission to the hospital, survival and treatment rates.
Sources of torsion in Poincarè gauge gravity
Authors: Wheeler James T.
Published: July 2023

We study sources for torsion in Poincarè gauge theory in any dimension, signature, and spin. We find that symmetric kinetic terms for non-Yang–Mills bosonic fields of arbitrary rank drive torsion. Our detailed discussion of spin-3/2 Rarita–Schwinger fields shows that they source all independent parts of the torsion. We develop systematic notation for spin-(2k+1)/2 fields and find the spin tensor for arbitrary k in n $$\ge $$
≥
2k+1 dimensions. For $$k>0$$

k
>
0

there is a novel direct coupling between torsion and spinor fields. We also cast the well-known gauge relation between the canonical and Belinfante–Rosenfield energy tensors in terms of different choices of independent variables.
STRONG ALLEE EFFECT AND EVOLUTIONARY DYNAMICS IN A SINGLE-SPECIES RICKER POPULATION MODEL
Authors: MOKNI KARIMA , CH-CHAOUI MOHAMED
Published: July 2023

In this paper, a discrete-time Ricker population model with the strong Allee effect is proposed, and its complex dynamic behavior is analyzed. First, the existence and asymptotic stability of the unique positive equilibrium are studied. Second, Neimark–Sacker and period-doubling bifurcations of this discrete model were carried out, and corresponding bifurcation conditions were obtained. Third, the pole placement method and the hybrid control strategy have been used to control the chaos produced by these bifurcations. Finally, we use MATLAB software to carry out some numerical simulations to analyze the rich dynamics of the system as well as to verify our theoretical results.
INTELLIGENT COMPUTING PARADIGM FOR SECOND-GRADE FLUID IN A ROTATING FRAME IN A FRACTAL POROUS MEDIUM
Authors: KANAN MOHAMMAD , ULLAH HABIB , RAJA MUHAMMAD ASIF ZAHOOR , FIZA MEHREEN , ULLAH HAKEEM , SHOAIB MUHAMMAD , AKGÜL ALI , ASAD JIHAD
Published: July 2023

The numerical methods such as the artificial neural networks with greater probability and nonlinear configurations are more suitable for estimation and modeling of the problem parameters. The numerical methods are easy to use in applications as these methods do not require costly and time-consuming tests like the experimental study. In this study, we use the Levenberg–Marquardt-based backpropagation Process (LMP) to create a computing paradigm that makes use of the strength of artificial neural networks (ANN), known as (ANN-LMP). Here we use the ANN-LMP to obtain the solution of the second-grade fluid in a rotating frame in a porous material with the impact of a transverse magnetic field. The 1000 data set points in the interval [Formula: see text] are used for the network training to determine the effect of various physical parameters of the flow problem under consideration. The experiment is executed of six scenarios with different physical paramaters. ANN-LMP is used for evaluating the mean square errors (MSE), training (TR), validation (VL), testing (TT), performance (PF) and fitting (FT) of the data. The problem has been verified by error histograms (EH) and regression (RG) measurements, which show high consistency with observed solutions with accuracy ranging from E-5 to E-8. Characteristics of various concerned parameters on the velocity and temperature profiles are studied.
An Interactive Web-Based Dashboard to Examine Trending Topics: Application to Financial Journals
Authors: Phan Ngoc , Madali Nayana Pampapura , Behpour Sahar , Xiao Ting
Published: July 2023

Understanding trends is helpful to identify future behaviours in the field, and the roles of people, places, and institutions in setting those trends. Although traditional clustering strategies can group articles into topics, these techniques do not focus on topics over limited timescales; additionally, even when articles are grouped, the generated results are extensive and difficult to navigate. To address these concerns, we create an interactive dashboard that helps an expert in the field to better understand and quantify trends in their area of research. Trend detection is performed using the time-biased document clustering method. The developed and freely available web application enables users to detect well-defined trending topics by experimenting with various levels of temporal bias — from detecting short-timescale trends to allowing those trends to spread over longer times. Experts can readily drill down into the identified topics to understand their meaning through keywords, example articles, and time range. Overall, the interactive dashboard will allow experts in the field to sift through the vast literature to identify the concepts, people, places, and institutions most critical to the field.
Generating Activity Snippets by Learning Human-Scene Interactions
Authors: Li Changyang , Yu Lap-Fai
Published: July 2023

We present an approach to generate virtual activity snippets, which comprise sequenced keyframes of multi-character, multi-object interaction scenarios in 3D environments, by learning from recordings of human-scene interactions. The generation consists of two stages. First, we use a sequential deep graph generative model with a temporal module to iteratively generate keyframe descriptions, which represent abstract interactions using graphs, while preserving spatial-temporal relations through the activities. Second, we devise an optimization framework to instantiate the activity snippets in virtual 3D environments guided by the generated keyframe descriptions. Our approach optimizes the poses of character and object instances encoded by the graph nodes to satisfy the relations and constraints encoded by the graph edges. The instantiation process includes a coarse 2D optimization followed by a fine 3D optimization to effectively explore the complex solution space for placing and posing the instances. Through experiments and a perceptual study, we applied our approach to generate plausible activity snippets under different settings.
Fluid-Solid Coupling in Kinetic Two-Phase Flow Simulation
Authors: Li Wei , Desbrun Mathieu
Published: July 2023

Real-life flows exhibit complex and visually appealing behaviors such as bubbling, splashing, glugging and wetting that simulation techniques in graphics have attempted to capture for years. While early approaches were not capable of reproducing multiphase flow phenomena due to their excessive numerical viscosity and low accuracy, kinetic solvers based on the lattice Boltzmann method have recently demonstrated the ability to simulate water-air interaction at high Reynolds numbers in a massively-parallel fashion. However, robust and accurate handling of fluid-solid coupling has remained elusive: be it for CG or CFD solvers, as soon as the motion of immersed objects is too fast or too sudden, pressures near boundaries and interfacial forces exhibit spurious oscillations leading to blowups. Built upon a phase-field and velocity-distribution based lattice-Boltzmann solver for multiphase flows, this paper spells out a series of numerical improvements in momentum exchange, interfacial forces, and two-way coupling to drastically reduce these typical artifacts, thus significantly expanding the types of fluid-solid coupling that we can efficiently simulate. We highlight the numerical benefits of our solver through various challenging simulation results, including comparisons to previous work and real footage.
The Visual Language of Fabrics
Authors: Deschaintre Valentin , Guerrero-Viu Julia , Gutierrez Diego , Boubekeur Tamy , Masia Belen
Published: July 2023

We introduce text2fabric, a novel dataset that links free-text descriptions to various fabric materials. The dataset comprises 15,000 natural language descriptions associated to 3,000 corresponding images of fabric materials. Traditionally, material descriptions come in the form of tags/keywords, which limits their expressivity, induces pre-existing knowledge of the appropriate vocabulary, and ultimately leads to a chopped description system. Therefore, we study the use of free-text as a more appropriate way to describe material appearance, taking the use case of fabrics as a common item that non-experts may often deal with. Based on the analysis of the dataset, we identify a compact lexicon, set of attributes and key structure that emerge from the descriptions. This allows us to accurately understand how people describe fabrics and draw directions for generalization to other types of materials. We also show that our dataset enables specializing large vision-language models such as CLIP, creating a meaningful latent space for fabric appearance, and significantly improving applications such as fine-grained material retrieval and automatic captioning.
Robust Low-Poly Meshing for General 3D Models
Authors: Chen Zhen , Pan Zherong , Wu Kui , Vouga Etienne , Gao Xifeng
Published: July 2023

We propose a robust re-meshing approach that can automatically generate visual-preserving low-poly meshes for any high-poly models found in the wild. Our method can be seamlessly integrated into current mesh-based 3D asset production pipelines. Given an input high-poly, our method proceeds in two stages: 1) Robustly extracting an offset surface mesh that is feature-preserving, and guaranteed to be watertight, manifold, and self-intersection free; 2) Progressively simplifying and flowing the offset mesh to bring it close to the input. The simplicity and the visual-preservation of the generated low-poly is controlled by a user-required target screen size of the input: decreasing the screen size reduces the element count of the low-poly but enlarges its visual difference from the input. We have evaluated our method on a subset of the Thingi10K dataset that contains models created by practitioners in different domains, with varying topological and geometric complexities. Compared to state-of-the-art approaches and widely used software, our method demonstrates its superiority in terms of the element count, visual preservation, geometry, and topology guarantees of the generated low-polys.
Computational Exploration of Multistable Elastic Knots
Authors: Vidulis Michele , Ren Yingying , Panetta Julian , Grinspun Eitan , Pauly Mark
Published: July 2023

We present an algorithmic approach to discover, study, and design multistable elastic knots. Elastic knots are physical realizations of closed curves embedded in 3-space. When endowed with the material thickness and bending resistance of a physical wire, these knots settle into equilibrium states that balance the forces induced by elastic deformation and self-contacts of the wire. In general, elastic knots can have many distinct equilibrium states, i.e. they are
multistable
mechanical systems. We propose a computational pipeline that combines randomized spatial sampling and physics simulation to efficiently find stable equilibrium states of elastic knots. Leveraging results from knot theory, we run our pipeline on thousands of different topological knot types to create an extensive data set of multistable knots. By applying a series of filters to this data, we discover new transformable knots with interesting geometric and physical properties. A further analysis across knot types reveals geometric and topological patterns, yielding constructive principles that generalize beyond the currently tabulated knot types. We show how multistable elastic knots can be used to design novel deployable structures and engaging recreational puzzles. Several physical prototypes at different scales highlight these applications and validate our simulation.
Surface Simplification using Intrinsic Error Metrics
Authors: Liu Hsueh-Ti Derek , Gillespie Mark , Chislett Benjamin , Sharp Nicholas , Jacobson Alec , Crane Keenan
Published: July 2023

This paper describes a method for fast simplification of surface meshes. Whereas past methods focus on visual appearance, our goal is to solve equations on the surface. Hence, rather than approximate the extrinsic geometry, we construct a coarse
intrinsic triangulation
of the input domain. In the spirit of the
quadric error metric (QEM)
, we perform greedy decimation while agglomerating global information about approximation error. In lieu of extrinsic quadrics, however, we store intrinsic tangent vectors that track how far curvature "drifts" during simplification. This process also yields a bijective map between the fine and coarse mesh, and prolongation operators for both scalar- and vector-valued data. Moreover, we obtain hard guarantees on element quality via intrinsic retriangulation---a feature unique to the intrinsic setting. The overall payoff is a "black box" approach to geometry processing, which decouples mesh resolution from the size of matrices used to solve equations. We show how our method benefits several fundamental tasks, including geometric multigrid, all-pairs geodesic distance, mean curvature flow, geodesic Voronoi diagrams, and the discrete exponential map.
VideoDoodles: Hand-Drawn Animations on Videos with Scene-Aware Canvases
Authors: Yu Emilie , Blackburn-Matzen Kevin , Nguyen Cuong , Wang Oliver , Habib Kazi Rubaiat , Bousseau Adrien
Published: July 2023

We present an interactive system to ease the creation of so-called
video doodles
- videos on which artists insert hand-drawn animations for entertainment or educational purposes. Video doodles are challenging to create because to be convincing, the inserted drawings must appear as if they were part of the captured scene. In particular, the drawings should undergo tracking, perspective deformations and occlusions as they move with respect to the camera and to other objects in the scene - visual effects that are difficult to reproduce with existing 2D video editing software. Our system supports these effects by relying on planar canvases that users position in a 3D scene reconstructed from the video. Furthermore, we present a custom tracking algorithm that allows users to anchor canvases to static or dynamic objects in the scene, such that the canvases move and rotate to follow the position and direction of these objects. When testing our system, novices could create a variety of short animated clips in a dozen of minutes, while professionals praised its speed and ease of use compared to existing tools.
Forming Terrains by Glacial Erosion
Authors: Cordonnier Guillaume , Jouvet Guillaume , Peytavie Adrien , Braun Jean , Cani Marie-Paule , Benes Bedrich , Galin Eric , Guérin Eric , Gain James
Published: July 2023

We introduce the first solution for simulating the formation and evolution of glaciers, together with their attendant erosive effects, for periods covering the combination of glacial and inter-glacial cycles. Our efficient solution includes both a fast yet accurate deep learning-based estimation of highorder ice flows and a new, multi-scale advection scheme enabling us to account for the distinct time scales at which glaciers reach equilibrium compared to eroding the terrain. We combine the resulting glacial erosion model with finer-scale erosive phenomena to account for the transport of debris flowing from cliffs. This enables us to model the formation of terrain shapes not previously adequately modeled in Computer Graphics, ranging from U-shaped and hanging valleys to fjords and glacial lakes.
Guided Linear Upsampling
Authors: Song Shuangbing , Zhong Fan , Wang Tianju , Qin Xueying , Tu Changhe
Published: July 2023

Guided upsampling is an effective approach for accelerating high-resolution image processing. In this paper, we propose a simple yet effective guided upsampling method. Each pixel in the high-resolution image is represented as a linear interpolation of two low-resolution pixels, whose indices and weights are optimized to minimize the upsampling error. The downsampling can be jointly optimized in order to prevent missing small isolated regions. Our method can be derived from the
color line model
and
local color transformations.
Compared to previous methods, our method can better preserve detail effects while suppressing artifacts such as bleeding and blurring. It is efficient, easy to implement, and free of sensitive parameters. We evaluate the proposed method with a wide range of image operators, and show its advantages through quantitative and qualitative analysis. We demonstrate the advantages of our method for both interactive image editing and real-time high-resolution video processing. In particular, for interactive editing, the joint optimization can be precomputed, thus allowing for instant feedback without hardware acceleration.
A Secure and Efficient Framework for Outsourcing Large-scale Matrix Determinant and Linear Equations
Authors: Luo Yuling , Zhang Shiqi , Zhang Shunsheng , Liu Junxiu , Wang Yanhu , Yang Su
Published: July 2023

Large-scale matrix determinants and linear equations are two basic computational tools in science and engineering fields. However, it is difficult for a resource-constrained client to solve large-scale computational tasks. Cloud computing service provides additional computing resources for resource-constrained clients. To solve the problem of large-scale computation, in this article, a secure and efficient framework is proposed to outsource large-scale matrix determinants and linear equations to a cloud. Specifically, the proposed framework contains two protocols, which solve large-scale matrix determinant and linear equations, respectively. In the outsourcing protocols of large-scale matrix determinants and linear equations, the task matrix is encrypted and sent to the cloud by the client. The encrypted task matrix is directly computed by using LU factorization in the cloud. The computed result is returned and verified by the cloud and the client, respectively. The computed result is decrypted if it passes the verification. Otherwise, it is returned to the cloud for recalculation. The framework can protect the input privacy and output privacy of the client. The framework also can guarantee the correctness of the result and reduce the local computational complexity. Furthermore, the experimental results show that the framework can save more than 70% of computing resources after outsourcing computing. Thus, this article provides a secure and efficient alternative for solving large-scale computational tasks.
A Novel Ti3C2/CoNP-NCNTHP Electrochemical Sensor for the Detection of Paracetamol and 4-Aminophenol Simultaneously
Authors: Zhang Jinjin , Liu Wenjing , Wang Qi , Qu Jianying
Published: July 2023

In this paper, composites of Ti3C2/ZIF-8/ZIF-67 were obtained through in situ growing ZIF-8/ZIF-67 on Ti3C2 with two-dimensional structure prepared by etching MXene using HF. Furtherly, novel materials of Ti3C2 modified with hollow polyhedrons composed of Co nanoparticles and N-doped carbon nanotube (Ti3C2/CoNP-NCNTHP) was got through derivation with high temperature calcination. The materials were combinations of two-dimensional nanosheets and three-dimensional hollow polyhedras, which were characterized by SEM, TEM, XRD, XPS and EIS. Based on this, a new electrochemical sensor of Ti3C2/CoNP-NCNTHP/GCE was constructed to detect paracetamol (PA) and 4-aminophenol (4-AP) simultaneously. Under optimal conditions, the linear ranges for detection of PA and 4-AP were 0.50–350.00 μM and 0.50–200.00 μM with the limits of detection of 0.05 μM and 0.07 μM, respectively. This proposed sensor has lower detection limits and good linear ranges, which was successfully applied for river water and acetaminophen tablets with good accuracy and has potential prospects for practical applications.
Modeling the Impact of Electrolyte Flow on Heat Management in a Li-Ion Convection Cell
Authors: Gao Weiran , Drake Javit , Brushett Fikile R.
Published: July 2023

In response to challenges in the thermal management of lithium-ion batteries (LIBs), we investigate the concept of circulating electrolyte through the porous electrodes and separator to facilitate effective, uniform, and real-time temperature regulation. We show, through physics-based electrothermal modeling and dimensional analysis of a single, planar LIB cell, that electrolyte convection can simultaneously draw heat from the cell and suppress heat generation from entropy change, charge-transfer, and ohmic losses, and that the cell temperature rise can be effectively mitigated when heat removal matches or exceeds heat generation. These findings distinguish internal convection from external surface cooling approaches used in conventional thermal management that often lead to a tradeoff between heat and mass transport. In a simulated exemplary 5.7-C case, a LIB cell with stationary electrolyte must stop discharging at only 54% of its capacity due to cell temperature rise to an upper threshold (325 K); with sufficient electrolyte flow (∼1 μm s−1 for a single cell, or a residence time of ∼200 s), the cell can be maintained below 315 K while delivering 98% of its capacity. Finally, to illustrate the potential for dynamic temperature regulation, we simulate scenarios where cells already experiencing self-heating can instantly arrest temperature rise with the onset of convection.
Skin type and nerve effects on cortical tactile processing: a somatosensory evoked potentials study
Authors: Guidotti Marco , Beaurieux Clément , Marionnaud Pierre , Bonnet-Brilhault Frédérique , Wardak Claire , Latinus Marianne
Published: July 2023

The current paper highlights the influences of stimulated skin type (glabrous/hairy) and nerve (median/radial) on cortical somatosensory evoked potentials. Mechanical stimulations were applied over four territories of the right hand in 18 adults. Four middle-latency components were identified: P50, N80, N130, and P200. A larger N80 was found after glabrous skin stimulations than after hairy skin ones, regardless of the nerve being stimulated. P50 and N80 were larger after median than radial nerve stimulations.
Enhancing Intranasal Delivery and Bioavailability of Dihydroergotamine Utilizing Chitosan Nanoparticles
Authors: Alastal Ahmed , Kwaik Amani D. Abu , Malkawi Azzam A. , Baltzley Sarah , Al-Ghananeem Abeer M.
Published: July 2023

Objective. Dihydroergotamine (DHE) is used for acute migraine treatment. Oral DHE is extensively metabolized; therefore, it must be given by a nonoral route. The aim of this study was to investigate the potential use of chitosan nanoparticles as a system for improving the systemic absorption of dihydroergotamine (DHE) following nasal administration. Methods. DHE-loaded chitosan nanoparticles (CS-NPs) were prepared by a modified ionotropic gelation method with sodium tripolyphosphate. The resulting nanoparticles were evaluated for size, drug loading, and in vitro release. DHE was administered at a dose of 0.5 mg/kg to male Sprague–Dawley rats intravenously, as an intranasal solution, or intranasal nanoparticles (n = 3 in each group). A special surgical procedure was performed to ensure that the drug solution was held in the nasal cavity. Blood samples were collected at appropriate times for 90 min. An HPLC-fluorescence detection method was employed to determine DHE in the plasma. Results. DHE chitosan nanoparticles with 20% loading had 95 ± 13% encapsulation efficiency and a particle size of 395 ± 59 nm. In vitro DHE release studies showed an initial burst followed by a slow release of DHE. DHE intranasal nanoparticles demonstrated significantly increased absolute bioavailability (82.5 ± 12.3%) over intranasal DHE solution administration (53.2 ± 7.7%). Conclusion. Taking in consideration the limitations of delivering DHE, the results of the present study demonstrate that DHE CS-NPs have a great potential for nasal DHE administration (55% increase in bioavailability) compared to intranasal solution with effective systemic absorption.
Some Further Results Using Green’s Function for
s
-Convexity
Authors: Yildiz Çetin , Akgün Levent , Khan Muhammad Adil , Rehman Nasir
Published: July 2023

For s-convex functions, the Hermite–Hadamard inequality is already well-known in convex analysis. In this regard, this work presents new inequalities associated with the left-hand side of the Hermite–Hadamard inequality for s-convexity by utilizing a novel technique based on Green’s function. Also, Hölder, Young, and power-mean inequalities are used to obtain these new inequalities. Finally, some applications to special means of real numbers are provided. In conclusion, we think that the methodology used in this work will encourage more research in this field.
Evaluation of the Physicochemical Characteristics of a Blend Fruit Juice Powder Mixed with Lactiplantibacillus plantarum: A Comparison of Spray Drying and Freeze Drying
Authors: Aryaee Hadis , Ariaii Peiman , Zare Davood , Mirdamadi Saeed , Naghizadeh Raeisi Shahram
Published: July 2023

The physicochemical properties and the survival of Lactiplantibacillus plantarum mixed with blend of fruit juice powders dried by spray and freeze drying methods were investigated. A formula containing maltodextrin 14% and malt extract 6% as a carrier and juices of red grape 20.4%, mulberry 75.6%, and strawberry 4.0% along with the bacterium (Lpb. plantarum) with

3
×

10

9

 CFU/mL were dried by spray drying and freeze drying methods, separately. The physicochemical properties including color attribute, nutritional properties of the powders such as antioxidant, and phenolic content were measured. Drying efficiency of freeze-dried was 80.48%, which was higher than the spray-dried powders (50.84%). The higher antioxidant (87.95) and total phenolic content (3032.6 mg GAE/L) was achieved by freeze drying technique; however, lower moisture content and flowability as well as higher solubility and bulk density were obtained for spray-dried powders. The survival of probiotics in freeze-dried powders was higher than the spray-dried powders which can be related to mild conditions. The study indicated that the juice powders are suitable carriers for Lpb. plantarum and constitute good alternatives to highly acidic fruit juices.
Spatial-Temporal Dynamics in Potable Water Quality: A Case Study of Mizan-Aman Town, Southwest, Ethiopia
Authors: Tadesse Zelalem , Dananto Mihret , Kassa Henok , Ingale Lalit
Published: July 2023

Surface water is one of the sources of global potable water. However, the quality of surface water has been degrading due to an increase in human activities. Hence, the present study was conducted to evaluate the spatial and temporal variability in drinking water physico-chemical and bacteriological characteristics from the different sources in Mizan-Aman, Ethiopia. The physico-chemical characteristics of water at the Kosokol site were found to be statistically different (

p
<
0.05

) from the other sites (Gacheb, Tsit, Reservoir 1, and Reservoir 2 sites). The dry and wet season temperature (27.1 and 23.8°C), turbidity (37.4 and 54.8 NTU), pH (7.6 and 8.1), biological oxygen demand (18.1 and 20.7 mg/l), phosphate (2.4 and 3.5 mg/l), and ammonia (2.2 and 4.8 mg/l) of the water were beyond the acceptable limit set for drinking water by both Ethiopian standards (temperature: <15°C; turbidity: 7 NTU; pH: 6.5–8.5; BOD: 10 mg/l; phosphate: 0.02 mg/l; and ammonia: 1.5 mg/l) and the WHO standards (temperature: <15°C; turbidity: 5 NT U; pH: 6.5–8.5; BOD: 5 mg/l; phosphate: 0.01 mg/l; and ammonia: 1.5 mg/l). The total coliform (366.5 and 494.3 CFU/100 ml) and fecal coliform (209.5 and 278.3 CFU/100 ml) contents of the water in the dry and wet seasons are beyond the acceptable limits for drinking water by Ethiopian standards (total and fecal coliform: 0) and the WHO standards (total and fecal coliform: 0). The physico-chemical and bacteriological characteristics of the water in the wet season were found significantly higher than those (

p
<
0.05

) in the dry season. In general, the water quality changes on a spatial and temporal basis in the study area. Thus, it is important to encourage water quality management works at the upper source sites of the catchment. Furthermore, the city water authority should reinforce safeguarding treatment processes, continuous monitoring of water quality as well as risk assessment and management practices.
Ultrasonographic Characteristics in the Fingers and Other Superficial Glomus Tumours
Authors: Takanashi Noboru , Asai Satomi , Ogase Yoko , Fujii Akiko , Atsumi Haruyo , Doi Mika , Kumaki Nobue , Mabuchi Tomotaka , Miyachi Hayato
Published: July 2023

Glomus tumours are painful superficial tumours, and ultrasonography is an extremely useful and noninvasive diagnostic technique for superficial organs. In this study, we retrospectively examined glomus tumours using ultrasonography. Among 18 patients histopathologically diagnosed with glomus tumours via ultrasonography, we observed five different development sites: subungual areas or those surrounding the nail bed (12), other areas on the finger surface (3), abdominal wall (1), upper arm (1), and forearm (1). The ultrasonographic images revealed significant differences in tumour size, indicating that tumours on other body surfaces tended to be smaller than those on patients’ fingers (

p

 < 0.01). The depth/width ratios of tumours on the other body surfaces were significantly higher than those on the fingers (

p

 < 0.05). The tumours showed a regular shape (72.2%) and clear border (100%). Furthermore, most tumours were low-echo tumours with a diameter of up to 15 mm, clear margins, and no lateral shadows. Abundant blood flow and vessels in and out of the tumours were also observed. In conclusion, our study describes the ultrasonographic characteristics of glomus tumours and reveals that they cannot be ruled out when diagnosing small painful subcutaneous tumours.
Balloon-Atrioseptostomy in Small Children Using an Embolectomy Catheter: Preliminary Data
Authors: Dalla Pozza R. , Hermann M. , Haas N. A.
Published: July 2023

Interventional treatment of restrictive atrial septal defects in complex heart disease is considered state-of-the-art therapy up to date. Nevertheless, dedicated balloons are lacking so far, as several products have been withdrawn from the market. We report on off-label use of a balloon embolectomy catheter used successfully in a preterm patient and discuss whether this device might be used in other patients as well as it seems to be promising due to its shape and versatility.
Supplementary Figure 2 from Hospitalizations and Cost of Inpatient Care for Physical Diseases in Survivors of Childhood Cancer in Western Australia: A Longitudinal Matched Cohort Study
Authors: Abdalla Tasnim , Walwyn Thomas , White Daniel , Choong Catherine S. , Bulsara Max , Preen David B. , Ohan Jeneva L.
Published: July 2023

The mean cumulative count of hospitalisations for any physical-health disease by attained age, in childhood cancer survivors and their matched comparisons.
Data from Hospitalisations and Cost of Inpatient Care for Physical Diseases in Survivors of Childhood Cancer in Western Australia: a Longitudinal Matched Cohort Study.
Authors: Abdalla Tasnim , Walwyn Thomas , White Daniel , Choong Catherine S. , Bulsara Max , Preen David B. , Ohan Jeneva L.
Published: July 2023

Abstract
Background. The long-term effects of childhood cancer are unclear in the Australian context. We examined hospitalisation trends for physical diseases and estimated the associated inpatient care costs in all 5-year childhood cancer survivors (CCS) diagnosed in Western Australia (WA) from 1982-2014.

Methods. Hospitalisation records for 2,938 CCS and 24,792 comparisons were extracted from 1987- 2019 (median follow-up=12 years, min=1, max=32). The adjusted hazard ratio (aHR) of hospitalisation with 95% confidence intervals (CI) was estimated using the Andersen-Gill model for recurrent events. The cumulative burden of hospitalisations over time was assessed using the mean cumulative count method. The adjusted mean cost of hospitalisation was estimated using the generalised linear models.

Results. We identified a higher risk of hospitalisation for all-cause (aHR=2.0, 95%CI= 1.8-2.2) physical disease in CCS than comparisons, with the highest risk for subsequent malignant neoplasms (aHR=15.0, 95%CI 11.3-19.8) and blood diseases (aHR=6.9, 95%CI 2.6-18.2). Characteristics associated with higher hospitalisation rates included female gender, diagnosis with bone tumours, cancer diagnosis age between 5-9 years, multiple childhood cancer diagnoses, multiple comorbidities, higher deprivation, increased remoteness, and Indigenous status. The difference in the mean total hospitalisation costs for any disease was significantly higher in survivors than comparisons (publicly funded $11,483 United States Dollar, p<0.05).

Conclusions. The CCS population face a significantly higher risk of physical morbidity and higher cost of hospital-based care than the comparisons.

Impact. Our study highlights the need for long-term follow-up healthcare services to prevent disease progression and mitigate the burden of physical morbidity on patients and hospital services.
Preclinical Efficacy of LP-184, a Tumor Site Activated Synthetic Lethal Therapeutic, in Glioblastoma
Authors: Lal Bachchu , Kulkarni Aditya , McDermott Joseph , Rais Rana , Alt Jesse , Wu Ying , Lopez-Bertoni Hernando , Sall Sophie , Kathad Umesh , Zhou Jianli , Slusher Barbara S. , Bhatia Kishor , Laterra John
Published: July 2023

Purpose:

Glioblastoma (GBM) is the most common brain malignancy with median survival <2 years. Standard-of-care temozolomide has marginal efficacy in approximately 70% of patients due to MGMT expression. LP-184 is an acylfulvene-derived prodrug activated by the oxidoreductase PTGR1 that alkylates at N3-adenine, not reported to be repaired by MGMT. This article examines LP-184 efficacy against preclinical GBM models and identifies molecular predictors of LP-184 efficacy in clinical GBM.

Experimental Design:

LP-184 effects on GBM cell viability and DNA damage were determined using cell lines, primary PDX-derived cells and patient-derived neurospheres. GBM cell sensitivities to LP-184 relative to temozolomide and MGMT expression were examined. Pharmacokinetics and CNS bioavailability were evaluated in mice with GBM xenografts. LP-184 effects on GBM xenograft growth and animal survival were determined. Machine learning, bioinformatic tools, and clinical databases identified molecular predictors of GBM cells and tumors to LP-184 responsiveness.

Results:

LP-184 inhibited viability of multiple GBM cell isolates including temozolomide-resistant and MGMT-expressing cells at IC50 = approximately 22–310 nmol/L. Pharmacokinetics showed favorable AUCbrain/plasma and AUCtumor/plasma ratios of 0.11 (brain Cmax = 839 nmol/L) and 0.2 (tumor Cmax = 2,530 nmol/L), respectively. LP-184 induced regression of GBM xenografts and prolonged survival of mice bearing orthotopic xenografts. Bioinformatic analyses identified PTGR1 elevation in clinical GBM subtypes and associated LP-184 sensitivity with EGFR signaling, low nucleotide excision repair (NER), and low ERCC3 expression. Spironolactone, which induces ERCC3 degradation, decreased LP-184 IC50 3 to 6 fold and enhanced GBM xenograft antitumor responses.

Conclusions:

These results establish LP-184 as a promising chemotherapeutic for GBM with enhanced efficacy in intrinsic or spironolactone-induced TC-NER–deficient tumors.