bluuebunny/crossref_metadata_2025 huggingface dataset:
Cooperative nucleic acid binding by Poly ADP-ribose polymerase 1
Authors: Melikishvili Manana , Fried Michael G. , Fondufe-Mittendorf Yvonne N.
Published: March 2024

Poly (ADP)-ribose polymerase 1 (PARP1) is an abundant nuclear protein well-known for its role in DNA repair yet also participates in DNA replication, transcription, and co-transcriptional splicing, where DNA is undamaged. Thus, binding to undamaged regions in DNA and RNA is likely a part of PARP1’s normal repertoire. Here we describe analyses of PARP1 binding to two short single-stranded DNAs, a single-stranded RNA, and a double stranded DNA. The investigations involved comparing the wild-type (WT) full-length enzyme with mutants lacking the catalytic domain (∆CAT) or zinc fingers 1 and 2 (∆Zn1∆Zn2). All three protein types exhibited monomeric characteristics in solution and formed saturated 2:1 complexes with single-stranded T20 and U20 oligonucleotides. These complexes formed without accumulation of 1:1 intermediates, a pattern suggestive of positive binding cooperativity. The retention of binding activities by ∆CAT and ∆Zn1∆Zn2 enzymes suggests that neither the catalytic domain nor zinc fingers 1 and 2 are indispensable for cooperative binding. In contrast, when a double stranded 19mer DNA was tested, WT PARP1 formed a 4:1 complex while the ∆Zn1Zn2 mutant binding saturated at 1:1 stoichiometry. These deviations from the 2:1 pattern observed with T20 and U20 oligonucleotides show that PARP’s binding mechanism can be influenced by the secondary structure of the nucleic acid. Our studies show that PARP1:nucleic acid interactions are strongly dependent on the nucleic acid type and properties, perhaps reflecting PARP1’s ability to respond differently to different nucleic acid ligands in cells. These findings lay a platform for understanding how the functionally versatile PARP1 recognizes diverse oligonucleotides within the realms of chromatin and RNA biology.
Climate control on the channel morphodynamics of the Sittaung River, Myanmar
Authors: Bisson Luke Stefan , Choi Kyungsik
Published: March 2024

The spatio–temporal development of a meandering river is controlled by its channel morphodynamics. In regions of rapid channel evolution, understanding the driving factors of meander migration is crucial in forecasting the rate and extent of morphological change. Sediment supply and fluvial discharge are the primary influences on migration rate, however climate oscillations are also integral in indirectly regulating migration rate through their control of regional precipitation, as well as the monsoon season of sub-tropical Asia. Despite this, an in-depth investigation into the impact of climate oscillations on meander bend migration remains undocumented. This study presents a satellite-based analysis of multi-decadal climatic forcing on the migration rate of the Sittaung River in Myanmar, through interpretation of the El Niño Southern Oscillation (ENSO). The mode of ENSO exerts significant climatic control on the migration rate of the meandering channels of the Sittaung River, with low-to-average migration rates recorded during dry El Niño events and peak migration rates observed during wet La Niña events. However, this climatic signal may have been obscured by certain local environmental conditions. In cases where meanders faced geological basement, the basement rock inhibited their migration through extension, forcing more rapid migration by way of seaward translation. Consequently, these translating meanders developed to be more elongate, with lower curvatures. Meanders downstream of the approximate tidal limit were less downstream skewed, indicative of tidal modulation, potentially obscuring the impact of fluvially driven climate forcing. Additionally, downstream of a major confluence, the input of sediment and fluvial discharge may have been regulated by upstream anthropogenic activities such as mining and dam construction, leading to greater variability in migration rate downstream of this confluence and further obfuscation of the climate signal.
LC–MS/MS, GC–MS and molecular docking analysis for phytochemical fingerprint and bioactivity of Beta vulgaris L.
Authors: Üst Özge , Yalçin Emine , Çavuşoğlu Kültiğin , Özkan Burak
Published: March 2024

The plants that we consume in our daily diet and use as a risk preventer against many diseases have many biological and pharmacological activities. In this study, the phytochemical fingerprint and biological activities of Beta vulgaris L. leaf extract, which are widely consumed in the Black Sea region, were investigated. The leaf parts of the plant were dried in an oven at 35 °C and then ground into powder. The main constituents in B. vulgaris were identified by LC–MS/MS and GC–MS analyses. Phenolic content, betaxanthin and betacyanin levels were investigated in the extracts obtained using three different solvents. The biological activity of the extract was investigated by anti-microbial, anti-mutagenic, anti-proliferative and anti-diabetic activity tests. Anti-diabetic activity was investigated by in vitro enzyme inhibition and in-silico molecular docking was performed to confirm this activity. In the LC–MS analysis of B. vulgaris extract, a major proportion of p_coumaric acid, vannilin, protecatechuic aldehyde and sesamol were detected, while the major essential oils determined by GC–MS analysis were hexahydrofarnesyl acetone and phytol. Among the solvents used, the highest extraction efficiency of 2.4% was obtained in methanol extraction, and 36.2 mg of GAE/g phenolic substance, 5.1 mg/L betacyanin and 4.05 mg/L betaxanthin were determined in the methanol extract. Beta vulgaris, which exhibited broad-spectrum anti-microbial activity by forming a zone of inhibition against all tested bacteria, exhibited anti-mutagenic activity in the range of 35.9–61.8% against various chromosomal abnormalities. Beta vulgaris extract, which did not exhibit mutagenic, sub-lethal or lethal effects, exhibited anti-proliferative activity by reducing proliferation in Allium root tip cells by 21.7%. 50 mg/mL B. vulgaris extract caused 58.9% and 55.9% inhibition of α-amylase and α-glucosidase activity, respectively. The interactions of coumaric acid, vanniline, hexahydrofarnesyl acetone and phytol, which are major compounds in phytochemical content, with α-amylase and α-glucosidase were investigated by in silico molecular docking and interactions between molecules via various amino acids were determined. Binding energies between the tested compounds and α-amylase were obtained in the range of − 4.3 kcal/mol and − 6.1 kcal/mol, while for α-glucosidase it was obtained in the range of − 3.7 kcal/mol and − 5.7 kcal/mol. The biological activities of B. vulgaris are closely related to the active compounds it contains, and therefore studies investigating the phytochemical contents of plants are very important. Safe and non-toxic plant extracts can help reduce the risk of various diseases, such as diabetes, and serve as an alternative or complement to current pharmaceutical practices.
Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment
Authors: Khalighi Sirvan , Reddy Kartik , Midya Abhishek , Pandav Krunal Balvantbhai , Madabhushi Anant , Abedalthagafi Malak
Published: March 2024

This review delves into the most recent advancements in applying artificial intelligence (AI) within neuro-oncology, specifically emphasizing work on gliomas, a class of brain tumors that represent a significant global health issue. AI has brought transformative innovations to brain tumor management, utilizing imaging, histopathological, and genomic tools for efficient detection, categorization, outcome prediction, and treatment planning. Assessing its influence across all facets of malignant brain tumor management- diagnosis, prognosis, and therapy- AI models outperform human evaluations in terms of accuracy and specificity. Their ability to discern molecular aspects from imaging may reduce reliance on invasive diagnostics and may accelerate the time to molecular diagnoses. The review covers AI techniques, from classical machine learning to deep learning, highlighting current applications and challenges. Promising directions for future research include multimodal data integration, generative AI, large medical language models, precise tumor delineation and characterization, and addressing racial and gender disparities. Adaptive personalized treatment strategies are also emphasized for optimizing clinical outcomes. Ethical, legal, and social implications are discussed, advocating for transparency and fairness in AI integration for neuro-oncology and providing a holistic understanding of its transformative impact on patient care.
Foundation metrics for evaluating effectiveness of healthcare conversations powered by generative AI
Authors: Abbasian Mahyar , Khatibi Elahe , Azimi Iman , Oniani David , Shakeri Hossein Abad Zahra , Thieme Alexander , Sriram Ram , Yang Zhongqi , Wang Yanshan , Lin Bryant , Gevaert Olivier , Li Li-Jia , Jain Ramesh , Rahmani Amir M.
Published: March 2024

Generative Artificial Intelligence is set to revolutionize healthcare delivery by transforming traditional patient care into a more personalized, efficient, and proactive process. Chatbots, serving as interactive conversational models, will probably drive this patient-centered transformation in healthcare. Through the provision of various services, including diagnosis, personalized lifestyle recommendations, dynamic scheduling of follow-ups, and mental health support, the objective is to substantially augment patient health outcomes, all the while mitigating the workload burden on healthcare providers. The life-critical nature of healthcare applications necessitates establishing a unified and comprehensive set of evaluation metrics for conversational models. Existing evaluation metrics proposed for various generic large language models (LLMs) demonstrate a lack of comprehension regarding medical and health concepts and their significance in promoting patients’ well-being. Moreover, these metrics neglect pivotal user-centered aspects, including trust-building, ethics, personalization, empathy, user comprehension, and emotional support. The purpose of this paper is to explore state-of-the-art LLM-based evaluation metrics that are specifically applicable to the assessment of interactive conversational models in healthcare. Subsequently, we present a comprehensive set of evaluation metrics designed to thoroughly assess the performance of healthcare chatbots from an end-user perspective. These metrics encompass an evaluation of language processing abilities, impact on real-world clinical tasks, and effectiveness in user-interactive conversations. Finally, we engage in a discussion concerning the challenges associated with defining and implementing these metrics, with particular emphasis on confounding factors such as the target audience, evaluation methods, and prompt techniques involved in the evaluation process.
A MOF-supported Pd1–Au1 dimer catalyses the semihydrogenation reaction of acetylene in ethylene with a nearly barrierless activation energy
Authors: Ballesteros-Soberanas Jordi , Martín Nuria , Bacic Matea , Tiburcio Estefanía , Mon Marta , Hernández-Garrido Juan Carlos , Marini Carlo , Boronat Mercedes , Ferrando-Soria Jesús , Armentano Donatella , Pardo Emilio , Leyva-Pérez Antonio
Published: March 2024

The removal of acetylene from ethylene streams is key in industry for manufacturing polyethylene. Here we show that a well-defined Pd1–Au1 dimer, anchored to the walls of a metal–organic framework (MOF), catalyses the selective semihydrogenation of acetylene to ethylene with ≥99.99% conversion (≤1 ppm of acetylene) and >90% selectivity in extremely rich ethylene streams (1% acetylene, 89% ethylene, 10% H2, simulated industrial front-end reaction conditions). The reaction proceeds with an apparent activation energy of ∼1 kcal mol–1, working even at 35 °C, and with operational windows (>100 °C) and weight hourly space velocities ($$66{,}000\,{\mathrm{ml}}\,{\mathrm{g}}^{-1}_{\mathrm{cat}}\,{\mathrm{h}}^{-1}$$

66
,
000

ml

g

cat

−
1

h

−
1

) within industrial specifications. A combined experimental and computational mechanistic study shows the cooperativity between both atoms, and between atoms and support, to enable the barrierless semihydrogenation of acetylene.
Learning to stand with sensorimotor delays generalizes across directions and from hand to leg effectors
Authors: Rasman Brandon G. , Blouin Jean-Sébastien , Nasrabadi Amin M. , van Woerkom Remco , Frens Maarten A. , Forbes Patrick A.
Published: March 2024

Humans receive sensory information from the past, requiring the brain to overcome delays to perform daily motor skills such as standing upright. Because delays vary throughout the body and change over a lifetime, it would be advantageous to generalize learned control policies of balancing with delays across contexts. However, not all forms of learning generalize. Here, we use a robotic simulator to impose delays into human balance. When delays are imposed in one direction of standing, participants are initially unstable but relearn to balance by reducing the variability of their motor actions and transfer balance improvements to untrained directions. Upon returning to normal standing, aftereffects from learning are observed as small oscillations in control, yet they do not destabilize balance. Remarkably, when participants train to balance with delays using their hand, learning transfers to standing with the legs. Our findings establish that humans use experience to broadly update their neural control to balance with delays.
Omics-based construction of regulatory variants can be applied to help decipher pig liver-related traits
Authors: Ling Ziqi , Li Jing , Jiang Tao , Zhang Zhen , Zhu Yaling , Zhou Zhimin , Yang Jiawen , Tong Xinkai , Yang Bin , Huang Lusheng
Published: March 2024

Genetic variants can influence complex traits by altering gene expression through changes to regulatory elements. However, the genetic variants that affect the activity of regulatory elements in pigs are largely unknown, and the extent to which these variants influence gene expression and contribute to the understanding of complex phenotypes remains unclear. Here, we annotate 90,991 high-quality regulatory elements using acetylation of histone H3 on lysine 27 (H3K27ac) ChIP-seq of 292 pig livers. Combined with genome resequencing and RNA-seq data, we identify 28,425 H3K27ac quantitative trait loci (acQTLs) and 12,250 expression quantitative trait loci (eQTLs). Through the allelic imbalance analysis, we validate two causative acQTL variants in independent datasets. We observe substantial sharing of genetic controls between gene expression and H3K27ac, particularly within promoters. We infer that 46% of H3K27ac exhibit a concomitant rather than causative relationship with gene expression. By integrating GWAS, eQTLs, acQTLs, and transcription factor binding prediction, we further demonstrate their application, through metabolites dulcitol, phosphatidylcholine (PC) (16:0/16:0) and published phenotypes, in identifying likely causal variants and genes, and discovering sub-threshold GWAS loci. We provide insight into the relationship between regulatory elements and gene expression, and the genetic foundation for dissecting the molecular mechanism of phenotypes.
Origin of charge density wave in topological semimetals SrAl4 and EuAl4
Authors: Wang Lin-Lin , Nepal Niraj K. , Canfield Paul C.
Published: March 2024

Topological semimetals in BaAl4-type structure show many interesting behaviors, such as charge density wave (CDW) in SrAl4 and EuAl4, but not the isostructural and isovalent BaAl4, SrGa4, and BaGa4. Here using Wannier functions based on density functional theory, we calculate the susceptibility functions with millions of k-points to reach the small q-vector and study the origin and driving force behind the CDW. Our comparative study reveals that the origin of the CDW in SrAl4 and EuAl4 is the strong electron-phonon coupling interaction for the transverse acoustic mode at small q-vector along the Γ-Z direction besides the maximum of the real part of the susceptibility function from the nested Fermi surfaces of the Dirac-like bands, which explains well the absence of CDW in the other closely related compounds in a good agreement with experiment. We also connect the different CDW behaviors in the Al compounds to the macroscopic elastic properties.
Noise-resilient single-pixel compressive sensing with single photon counting
Authors: Li Lili , Kumar Santosh , Sua Yong Meng , Huang Yu-Ping
Published: March 2024

The fast expansion of photon detection technology has fertilized the rapid growth of single-photon sensing and imaging techniques. While promising significant advantages over their classical counterparts, they suffer from ambient and quantum noises whose effects become more pronounced at low light levels, limiting the quality of the acquired signal. Here, we study how photon-counting noises degrade a single-pixel optical classifier via compressive sensing, and how its performance can be restored by using quantum parametric mode sorting. Using modified National Institute of Standards and Technology (MNIST) handwritten digits as an example, we examine the effects of detector dark counts and in-band background noises and demonstrate the effectiveness of mode filtering and upconversion detection in addressing those issues. We achieve 94% classification accuracy in the presence of 500 times stronger in-band noise than the signal received. Our results suggest a robust and efficient approach to single photon sensing in a practical environment, where sunlight, ambient, and multiscattering noises can easily dominate the weak signal.
Invalid SMILES are beneficial rather than detrimental to chemical language models
Authors: Skinnider Michael A.
Published: March 2024

Generative machine learning models have attracted intense interest for their ability to sample novel molecules with desired chemical or biological properties. Among these, language models trained on SMILES (Simplified Molecular-Input Line-Entry System) representations have been subject to the most extensive experimental validation and have been widely adopted. However, these models have what is perceived to be a major limitation: some fraction of the SMILES strings that they generate are invalid, meaning that they cannot be decoded to a chemical structure. This perceived shortcoming has motivated a remarkably broad spectrum of work designed to mitigate the generation of invalid SMILES or correct them post hoc. Here I provide causal evidence that the ability to produce invalid outputs is not harmful but is instead beneficial to chemical language models. I show that the generation of invalid outputs provides a self-corrective mechanism that filters low-likelihood samples from the language model output. Conversely, enforcing valid outputs produces structural biases in the generated molecules, impairing distribution learning and limiting generalization to unseen chemical space. Together, these results refute the prevailing assumption that invalid SMILES are a shortcoming of chemical language models and reframe them as a feature, not a bug.
Engineering a polyvinyl butyral hydrogel as a thermochromic interlayer for energy-saving windows
Authors: Lin Zequn , Yang Zican , Gao Liang
Published: March 2024

The subtle amphiphilic of PVB makes for a well-structured network. Its design enables fast, consistent and reversible phase transitions of LCST. Overall, smart windows incorporating the gel have excellent light control capabilities.
A new paradigm for battery structural design towards interface-free, all-in-one cell configuration
Authors: Xiong Weixing , Zheng Xueying , Li Yuchen , Cao Zhang , Sun Jiayang , Wang Yan , Lv Linze , Qu Qunting , Luo Wei , Zheng Honghe
Published: March 2024

The novel all-in-one cell configuration contributes to developing batteries of extremely high rate performance and long durability by eliminating the internal interfaces and adopting a nonporous cell separator.
Defect-rich sonosensitizers based on CeO2 with Schottky heterojunctions for boosting sonodynamic/chemodynamic synergistic therapy
Authors: Zheng Haiyang , Yin Na , Lv Kehong , Niu Rui , Zhou Shijie , Wang Yinghui , Zhang Hongjie
Published: March 2024

A defect-rich hollow Schottky heterojunction sonosensitizer, constructed by defect engineering and noble metal enrichment, exhibits an amplified treatment effect for sonodynamic therapy due to the inhibition effect of electron–hole pair recombination.
Photosynthetic co‐culture system of algae and human umbilical vein endothelial cells: The effect on alleviating hypoxia and hypoxia/reoxygenation injury
Authors: Lin Donghu , Chen Yuanyuan , Tao Xinyu , Che Xin , Li Shiyu , Cheng Shiyu , Qu Shuxin
Published: March 2024

It is a developed photosynthetic co‐culture system to alleviate the hypoxia and hypoxia/reoxygenation (H/R)‐injured human umbilical vein endothelial cells (HUVECs). The algae, Chlorella vulgaris, were encapsulated to slow their growth while not affecting the photosynthetic oxygen‐producing capacity by Layer‐by‐layer (LbL) using gelatin and sodium alginate as the positive and negative charges materials, respectively. Then, the photosynthetic co‐culture system of HUVECs and self‐oxygenating alginate hydrogel (Algae‐gel) was constructed in which the optimal ratios between algae and HUVECs were 5:1 and 20:1 for a 2D or 3D co‐cultured manner, respectively. It indicated that the 3D co‐cultured manner of HUVECs needed more O2 by the production of algae than it did in a 2D co‐cultured manner. The co‐cultured Algae‐gel could alleviate hypoxia and the oxidative stress injury of hypoxia and hypoxia/reoxygenation (H/R)‐treated HUVECs in the proliferation, intracellular ROS and cellular migratory ability. In addition, the Algae‐gel could downregulate the expression of hypoxia‐inducible factors 1α (HIF‐1α) and vascular endothelial growth factor (VEGF) of hypoxia and H/R‐injured HUVECs due to the improvement of hypoxia and H/R injury. This photosynthetic co‐culture system could offer a promising approach for repairing hypoxia and H/R‐injured cells or tissue by providing safe and stable O2.
Mixed reality based teleoperation and visualization of surgical robotics
Authors: Ai Letian , Kazanzides Peter , Azimi Ehsan
Published: March 2024

Surgical robotics has revolutionized the field of surgery, facilitating complex procedures in operating rooms. However, the current teleoperation systems often rely on bulky consoles, which limit the mobility of surgeons. This restriction reduces surgeons' awareness of the patient during procedures and narrows the range of implementation scenarios. To address these challenges, an alternative solution is proposed: a mixed reality‐based teleoperation system. This system leverages hand gestures, head motion tracking, and speech commands to enable the teleoperation of surgical robots. The implementation focuses on the da Vinci research kit (dVRK) and utilizes the capabilities of Microsoft HoloLens 2. The system's effectiveness is evaluated through camera navigation tasks and peg transfer tasks. The results indicate that, in comparison to manipulator‐based teleoperation, the system demonstrates comparable viability in endoscope teleoperation. However, it falls short in instrument teleoperation, highlighting the need for further improvements in hand gesture recognition and video display quality.
Reconfigurable detuned dual‐frequency series–series compensated WPT system for high anti‐misalignment tolerance
Authors: Xu Kerui , Zhou Jing , Wang Bo , Wang Yuankui
Published: March 2024

In the realm of wireless power transfer, considering misalignment between transmitting and receiving coils is imperative. Traditional wireless power transfer systems experience a significant decrease in output power when the coupling coefficient fluctuates. This paper proposes a reconfigurable dual‐frequency series–series (SS) topology with primary side inductive detuned and secondary side with full resonance. The proposed topology operates at two frequencies and can be transformed into two different SS topologies at each frequency. This allows the system to switch between the two SS topologies when a large misalignment occurs, thereby achieving a more stable output power level. Furthermore, a comprehensive parameter design flowchart for the proposed topology is presented, and the parameters for a 400 W prototype are designed and implemented. The prototype is tested to evaluate the performance of the topology. The frequency response analysis of the prototype validates the effectiveness of the parameter design method. The test results show that the topology can maintain output power fluctuations within 23% of the maximum power for misalignment ranging from k = 0.13 to k = 0.46. Additionally, the system maintains an efficiency of at least 80% across the entire output power flat range, peaking at a maximum efficiency of 91%.
Local Exponential Stabilization of Rogers–McCulloch and FitzHugh–Nagumo Equations by the Method of Backstepping
Authors: Chowdhury Shirshendu , Dutta Rajib , Majumdar Subrata
Published: March 2024

In this article, we study the exponential stabilization of some one-dimensional nonlinear coupled parabolic-ODE systems, namely Rogers–McCulloch and FitzHugh–Nagumo systems, in the interval (0, 1) by boundary feedback. Our goal is to construct an explicit linear feedback control law acting only at the right end of the Dirichlet boundary to establish the local exponential stabilizability of these two different nonlinear systems with a decay e−ωt, where ω ∈ (0, δ] for the FitzHugh–Nagumo system and ω ∈ (0, δ) for the Rogers–McCulloch system and δ is the system parameter that presents in the ODE of both coupled systems. The feedback control law, derived by the backstepping method forces the exponential decay of solution of the closed-loop nonlinear system in both L2(0, 1) and H1(0, 1) norms, respectively, if the initial data is small enough. We also show that the linearized FitzHugh–Nagumo system is not stabilizable with exponential decay e−ωt, where ω > δ.
The Rival Coffee Shop Problem
Authors: Casado Javier , Cuerno Manuel
Published: March 2024

In this paper, we will address a modification of the following optimization problem: given a positive integer N and a compact Riemannian manifold X, the goal is to place a point xN ∈ X in such a way that the sequence {x1, …, xN} ⊂ X is distributed as uniformly as possible, considering that {x1, …, xN−1} ⊂ X already is. This can be thought as a way of placing coffee shops in a certain area one at a time in order to cover it optimally. So, following this modelization we will denote this problem as the coffee shop problem. This notion of optimal settlement is formalized in the context of optimal transport and Wasserstein distance. As a novel aspect, we introduce a new element to the problem: the presence of a rival brand, which competes against us by opening its own coffee shops. As our main tool, we use a variation of the Wasserstein distance (the Signed Wasserstein distance presented by Piccoli et al., Commun. Math. Sci. 21 (2023) 1279–1301), that allows us to work with finite signed measures and fits our problem. We present different results depending on how fast the rival is able to grow. With the Signed Wasserstein distance, we are able to obtain similar inequalities to the ones produced by the canonical Wasserstein one.
Advancing Sustainable Agriculture through Resource Efficiency
Authors: Saxena Abhishek , R J Anandhi , Ramesh B. , Fande Ashish , Chandra Pradeep Kumar , Sethi Vandana Arora , Al-Farouni Mohammed
Published: March 2024

Efficiency in technology, distributive effectiveness, and environmental effectiveness all have the potential to be included in the general concept of "resource use efficiency in agriculture." An effective farmer distributes his resources, including labourers, water, and land, appropriately in the best possible way to enhance his revenue while minimising expenses over time. Multiple research studies, however, demonstrate that farmers frequently make inadequate use of their resources. This study presents a comprehensive analysis of various farming practices and technologies, highlighting their impact on agricultural efficiency and resource use. Also, this review investigates the incorporation of advanced technologies such as the Internet of Things (IoT) into agriculture, emphasising the significance of environmental and economic factors in achieving sustainable agricultural productivity. With a focus on the ASEAN region and specific case studies, it assesses how carbon emissions, deforestation, renewable energy, and biodiversity affect farming efficiencies. The paper underscores the value of biodiversity, including underutilized and neglected species, and the potential of IoT and associated technologies to enhance agricultural operations. Moreover, it discusses about how resource optimization models can be used to increase agricultural yields and address environmental issues. A fundamental necessity for strategic management of water resources and joint utilization of water resources to support sustainable agriculture is also emphasized in the evaluation.
IoT enabled hospital asset tracking using advanced interdisciplinary approaches
Authors: Saritha K. , Abhiram Cherukuri , Anvith Reddy Poreddy , Sai Sathwik Sundralla , Rasool Shaik Nayab , Alzubaidi Laith H. , Helena Raj Vijilius , Dutt Amit , Kumar Yadav Dinesh
Published: March 2024

As the healthcare landscape embraces the revolutionary power of digitalization, improving inventory systems has become a top priority. Hospital asset tracking primarily focuses on monitoring various assets within a healthcare facility. These assets encompass human resources, medical equipment, vehicles, and other essential resources crucial for seamless hospital operations. Tracking assets in a hospital setting can range from monitoring individual medical devices to overseeing entire fleets of equipment and staff resources. The central objective is to maintain real-time records of asset status, and location to optimize productivity while minimizing costs. This project tracks the assets within the hospital using RFID sensors and outside the hospital using GPS. Radio frequency identification system (RFID) is an automatic technology and is used to identify objects, and record data through radio waves. Hospital asset management and tracking has become one of the main priorities in healthcare as it saves hospitals both money and time. Hospitals are under constant pressure to persistently track their medical equipment and supplies to make sure that they are properly utilized. This enhances financial performance and ensures the delivery of high-quality patient care. These are the advanced approaches to improve hospital asset management through real-time tracking and data analysis.
Microwave-Assisted Cladding of Ni-BaTiO3 Mixture onto SS-304 for Enhancing the Wear Resistance and Surface Hardness
Authors: A Kakoli Rao , Parashar Ashish Kumar , Ginni Nijhawan , Banoth Ramesh , Balan Gunapriya , Hameed Ali Abdulhussein
Published: March 2024

The present study focuses on achieving precise deposition of a Ni and 15% BaTiO3 particle mixture onto SS-304 substrates through meticulous preparation steps. Thorough cleaning of the SS-304 substrate eliminated contaminants, ensuring optimal adhesion. Simultaneously, the Ni-BaTiO3 mixture underwent preheating at 1200°C for 20 hours in a muffle furnace to eliminate moisture content, crucial for preventing coating defects. A uniform and crack-free cladding layer enhances the substrate’s resistance to wear, corrosion, and mechanical stresses, thereby extending its service life and improving overall functionality. The surface hardness of SS-304 experienced a substantial improvement of 39.90% following the cladding process with Ni and 15% BaTiO3. A sliding speed of 2 m/s was meticulously selected to replicate typical velocities encountered in practical applications, ensuring a realistic assessment of frictional behavior and wear resistance. Similarly, the sliding distance of 1000 m and an axial load of 5 N were precisely calibrated to simulate the mechanical stresses experienced during sliding contact, facilitating a thorough examination under relevant conditions. These carefully chosen parameters enabled the determination of key tribological properties essential for evaluating the performance of the cladded surface of SS 304 with Ni + 15% BaTiO3. The wear rate, measured at 0.0016 mm3/m, serves as a critical indicator, revealing the volume of material lost per unit distance of sliding. This parameter provides invaluable insights into the surface’s wear resistance and durability, crucial for assessing the longevity and performance of the cladded surface under abrasive conditions. Additionally, the coefficient of friction, determined to be 0.255, offers a quantitative measure of the surface’s frictional behavior during sliding contact.
Advanced interdisciplinary techniques for revolutionized government ration dispensing system using IoT
Authors: Machikuri Santoshi Kumari , Valluri Bhavith Kumar , Bathula Johnson , Pasha Saleem , Zabibah Rahman S. , R J Anandhi , Singh Navdeep , Kalra Ravi
Published: March 2024

The Indian Government is providing grains to those in need at affordable prices through a process known as the Public Distribution System. However, the current distribution methods employed in the public distribution system rely on manual processes, which may lead to errors, be time-consuming, and foster corruption. To address these issues, the proposed work employs Advanced Interdisciplinary Techniques such as RFID cards and readers to authenticate ration cardholders and ensure precise ration dispensing, significantly reducing inaccuracies and fraudulent activities. Furthermore, it incorporates a GSM-based mechanism with OTP authentication, adding an extra layer of security and efficiency. The GSM module sends a one-time password (OTP) to the user’s registered mobile number before dispensing rations, ensuring that only authorized individuals receive their entitled goods. Customers can select the goods they need from the allocation provided by the Government, and the amount will be automatically deducted from their RFID card based on the goods selected. A microcontroller manages the motor and relay to dispense items, while an alarm system alerts in cases of incorrect OTP entries, effectively deterring unauthorized access to rations. This system promises to make the ration distribution process more efficient, transparent, and accountable. Incorporating Advanced Interdisciplinary Techniques for Revolutionized Government Ration Dispensing System Using IoT.
Promoting sustainable living: IoT-integrated smart homes for elderly people
Authors: Ediga Poornima , Gullapelly Pravalika , Edukulla Tejaswi , Nunna Kaavya , Al-Farouni Mohammed , V Revathi , Singh Navdeep , Kumar Ashwani
Published: March 2024

The global population is rapidly aging, creating a demand for innovative solutions to support elderly individuals in maintaining their independence and well-being. This shift has led to the integration of Internet of Things (IoT) technology into smart homes as a transformative approach to elderly care. By utilizing continuous monitoring and real-time data collection, IoT-based solutions offer personalized support tailored to the unique needs of seniors. A wearable device, incorporating Arduino Uno microcontroller, ESP01, DHT11, ADXL335, and pulse sensor, provides crucial real-time information on vital signs, particularly beneficial for those with conditions like Alzheimer’s. These technologies not only detect falls but also facilitate immediate alerts to caregivers, promoting safety and rapid response. Moreover, IoT-integrated smart homes promote sustainability by optimizing energy usage and reducing waste, contributing to a more ecofriendly future. Unlike traditional methods, these IoT solutions offer proactive interventions and remote connectivity, enhancing communication between seniors, caregivers, and healthcare professionals while minimizing healthcare costs. This holistic approach prioritizes the autonomy and privacy of the elderly while harnessing technological advancements to improve their quality of life.
Aluminum-Alumina Composite Manufacturing: Unlocking Potential with Friction Stir Processing
Authors: Q Mohammad , K Gopal , E Poornima , Singh Navdeep , Arora Sethi Vandana , Kumari Vandna
Published: March 2024

This study investigates the manufacturing of Aluminum-Alumina composites through Friction Stir Processing (FSP) and explores the resultant enhancements in mechanical properties. A key focus lies on achieving a uniform distribution of Al2O3 particles within the composite matrix, crucial for optimizing material performance. These dispersed particles act as effective strengthening agents, impeding dislocation movement and grain boundary migration, consequently improving mechanical attributes such as hardness, strength, and wear resistance. Experimental findings underscore the efficacy of FSP in enhancing various mechanical properties of the composite. Notably, significant improvements were observed, including a 23.56% increase in tensile strength, a 37.9% enhancement in hardness, a 25.5% improvement in fatigue strength, and a notable 30.12% increase in wear resistance. These results underscore the potential of Aluminum-Alumina composites manufactured via FSP to unlock new opportunities for high-performance materials in industries requiring superior mechanical properties and wear resistance, such as aerospace, automotive, and manufacturing sectors.
Advancing Aluminum-Based Composite Manufacturing: Leveraging WC Reinforcement through Stir Casting Technique
Authors: Abood Ahmed Salam , Jayanthi Muthuswamy , M Anjaneyulu , Thethi H. Pal , Singh Shivani , Chahuan Neeraj
Published: March 2024

This study explores the advancement of aluminum-based composite manufacturing by leveraging tungsten carbide (WC) reinforcement through the stir casting technique. Aluminum alloy served as the matrix material, enriched with ceramic reinforcement particles. The alloy underwent complete melting in a muffle furnace, maintaining a temperature of about 700°C. Ceramic particles were methodically introduced into the molten alloy, ensuring homogeneous dispersion through continuous stirring at 400 rpm for 10 minutes. The resulting composite exhibited a uniform distribution of WC particles, seamlessly integrated throughout the alloy matrix. Remarkably, the addition of 7% WC reinforcement led to substantial enhancements in mechanical properties: a 22.67% improvement in tensile strength, a remarkable 37.9% increase in hardness, a notable 25.80% enhancement in fatigue strength, and a significant 27.67% improvement in wear resistance. These findings underscore the efficacy of the stir casting technique in optimizing the properties of aluminum-based composites, offering promising avenues for the development of high-performance materials for diverse engineering applications.
An IoT-based animal detection system using an interdisciplinary approach
Authors: Mamidi Kiran Kumar , Valiveti Sai Nishwanth , Vutukuri Guru Charan , Dhuda Ashwin Kumar , Alabdeli Haider , Chandrashekar Rakesh , Lakhanpal Sorabh , Praveen
Published: March 2024

Nowadays, educational institutions particularly colleges, engaged with students and staff, frequently confront various security challenges in their day-to-day activities. One prominent concern involves the threat of animal bites on the campus. In response to this issue, campus management has traditionally resorted to human patrols and physical barriers to deter animals. To address this multifaceted security challenge, the proposed method “An IoT-based Animal Detection System Using Interdisciplinary Approaches” introduces an innovative solution that leverages the power of IoT technology to enhance campus safety and security significantly. The system deploys a surveillance robot equipped with ultrasonic sensors and ESP32 cameras, employingthe machine learning technique R-CNN for Animal Detection. This proposed method uses an interdisciplinary approach to develop an animal detection system capable of identifying and classifying various species. This proposed method aims to revolutionize campus security by seamlessly integrating advanced technology, mitigating risks proactively, streamlining processes through automation, and presenting a cost-effective alternative to traditional security approaches. Beyond the traditional methods, the proposed system achieves an impressive accuracy rate of animal detection approximately 97.6% enabling real-time alerts through push notifications to security personnel upon detection.
Industry Monitoring System Using IoT through Interdisciplinary Approaches
Authors: Sruthi P. , Dunna Lokesh Varma , Mukkera Aditya Reddy , Dusanapudi Aditya , Al-Farouni Mohammed , Manjunatha  , Jain Alok , Pratap Bhishm
Published: March 2024

Now-a-days in dynamic industrial landscape, the need for real-time monitoring, data-driven decision making, and operational optimization has become paramount. The Industry Monitoring System using IoT emerges as a transformative solution that leverages the capabilities of interconnected devices and sensors to provide comprehensive visibility into industrial processes and assets. This innovative system deploys a network of sensors and IoT devices strategically with in industrial facilities to capture critical data parameters, ranging from environmental conditions to equipment performance metrics. These sensors communicate seamlessly through wired or wireless connections, transmitting data to a centralized hub or cloud-based platform. This proactive approach not only enhances equipment reliability but also reduces downtime and maintenance costs. Furthermore, the integration of IoT in industry monitoring facilitates data-driven decision-making, fostering a more agile and responsive industrial ecosystem.
Developments in Biomedical Materials: From Conventional Implantation to State-of-the-Art Pharmaceutical Uses
Authors: V Revathi , Rajitha Akula , Meghe Dheeraj , Yadav Dinesh Kumar , Sharma Shekhar , Zabibah Rahman S. , Awasthi Ankita
Published: March 2024

In order to improve and restore the functions of biological tissues and organs as well as for the identification and treatment of diseases, biomedical materials a developing subject of materials science are indispensable. Materials like these are frequently employed in many different medical equipment employed in clinical settings, such as scaffolding, sutures, substitute teeth, artificial bones, and even heart replacements. Innovative methods for identifying, treating, and regaining physiological functions have been made possible by biomedical materials, which have completely changed the healthcare industry. The development, categorization, and therapeutic uses of biomedical materials are examined in this study, with a focus on metallic biomaterials, synthetic polymers, and bio ceramics in addition to their biologically derived counterparts, such as collagen, silk, chitosan, and alginate. The functionality of medical devices has been significantly advanced by bioengineering improvements, that have produced healing implants and progressive diagnostic imaging that improve patient effects. This evaluation explores the capacity of nanomaterials in biomedicine, current wound dressings, and antimicrobial methods, highlighting the limitations and destiny opportunities inside the creation of extra powerful therapy and minimally harmful diagnostic tools.
SMS-based heart attack detection system
Authors: Shamila M. , Sundala Harika , Papatla Akshitha , Ram Kumar R.P. , S Zabibah Rahman , Helena Raj Vijilius , Gupta Manish , Pratap Bhishm
Published: March 2024

Internet of Things (IoT) is described as a network of computer devices and things which can transfer data to each other. Considering the scenario, continuous monitoring of health is most important to manage emergency situations. A person’s heartbeat, or Beats Per Minute (BPM), is one of the most crucial aspects of their health. The heartbeat was previously exclusively measured in clinics and hospitals, but they have recently made their way into mobile applications. So, for monitoring a person’s Heart Rate (HR) and Oxygen saturation levels (SpO2) (works as an oximeter) MAX30102 sensor is used. The data is collected and transmitted by a patch circuit. The aim of this work is to monitor heartbeat and oxygen levels of a person and alert through a notification message if either of them are above or below required level. The levels are also displayed on the mobile app which is designed using Kodular. If the heartbeat level of a person crosses a certain threshold value, the microcontroller displays an alert message on the app and also sends an alert SMS notification to the contacts of family members and concerned medical authorities.
Synergizing ANSYS Simulations and Machine Learning for Transient Thermal Analysis in Aluminium Alloys
Authors: Mohammed Kahtan A. , Jayanthi Muthuswamy , Shamila M. , Gupta Manish , Arora Sethi Vandana , Kumar Ashwani
Published: March 2024

Time-dependent thermal analysis plays a pivotal role in the manufacturing industry as it greatly influences the overall performance of the final product. This study delves into transient thermal analysis of an aluminum alloy concerning both temperature and time. Employing ANSYS, a finite element-based software, an axisymmetric model is constructed. This model encompasses a mold made of sand and a pattern filled with aluminum alloy. The analysis focuses on temperatures ranging from 650 to 1050°C, examining the temperature changes in the mold and pattern after 1500 seconds, primarily due to the convection process. Parameters like heat flux and directional heat flux are also determined. Subsequently, machine learning models are utilized to interpret the data acquired from ANSYS, enabling the extension of the results to a broader temperature range of 1150 to 1550°C. This study is instrumental in facilitating the effective design of transient thermal analysis for various alloys at different temperatures.
Nanofertilizers: Transforming Agriculture for Sustainable Food Production
Authors: Alekhya V. , Rajalakshmi B. , Kochar Sonika , Khan Irfan , Paul Surovi , Alsalami Zaid , Arun Vanya
Published: March 2024

The world's population is expected to increase to 10 billion humans through the 12 months 2050, which poses an extreme venture to agriculture's potential to deliver the developing demand for meals in a sustainable way at the same time as minimizing unfavourable environmental outcomes. The rising need for food worldwide has led to the widespread usage of fertilisers. The widely used chemical fertilisers can improve crop production and expansion, but they are harmful to the environment, the soil, as well as the health of people. As a result, one of the most intriguing alternatives to conventional fertilisers is nanofertilizer. These synthetic materials consist of nanoparticles that are regulated in their delivery of macro-and micronutrients to the plant rhizosphere. The necessary nutrients as well as minerals are bound together either alone or in conjunction with nano-sized adsorbents in nano material-based fertilizers. Conventional fertilisation techniques have resulted in inefficiencies and environmental problems because they often rely on chemical fertilisers for phosphorus (P) and nitrogen (N). Consequently, nanotechnology-based fertilizers—also referred to as nano fertilisers, or NFs—have become a promising therapeutic option. Compared to conventional fertilisers, these NFs enhance crop yields, improve nitrogen uptake efficiency, and have a smaller negative impact on the environment. This paper explores at the evidence, applications, and benefits of NFs, focusing on how they could change farming practices and enhance the production of sustainably produced food.