bluuebunny/crossref_metadata_2025 huggingface dataset:
Multibody Models Generated from Natural Language
Authors: Gerstmayr Johannes , Manzl Peter , Pieber Michael
Published: November 2023

Computational models are conventionally created with input data, script files, programming interfaces, or graphical user interfaces. This paper explores the potential of expanding model generation, with a focus on multibody system dynamics. In particular, we investigate the ability of Large Language Models (LLMs), to generate models from natural language. Our experimental findings indicate that LLMs, some of them having been trained on our multibody code Exudyn, surpass the mere replication of existing code examples. The results demonstrate that LLMs have a basic understanding of kinematics and dynamics, and that they can transfer this knowledge into a programming interface. Although our tests reveal that complex cases regularly result in programming or modeling errors, we found that LLMs can successfully generate correct multibody simulation models from natural language descriptions for simpler cases, often on the first attempt (zero-shot). Next to a basic introduction into the functionality of LLMs, our Python code, and the test setups, we provide a summarized evaluation for a series of examples with increasing complexity. We start with a single mass oscillator, both in SciPy as well as in Exudyn, and include varied inputs and statistical analysis to highlight the robustness of our approach. Hereafter, systems with mass points, constraints, and rigid bodies are evaluated. In particular, we show that in-context learning can levitate basic knowledge of a multibody code into a zero-shot correct output.
Blooming and Pruning: Learning from Mistakes with Memristive Synapses
Authors: Nikiruy Kristina , Perez Eduardo , Baroni Andrea , Reddy Keerthi Dorai Swamy , Pechmann Stefan , Wenger Christian , Ziegler Martin
Published: November 2023

Blooming and pruning is one of the most important developmental mechanisms of the biological brain in the first years of life, enabling it to adapt its network structure to the demands of the environment. The mechanism is thought to be fundamental for the development of cognitive skills. Inspired by this, Chialvo and Bak proposed in 1999 a learning scheme that learns from mistakes by eliminating from the initial surplus of synaptic connections those that lead to an undesirable outcome. Here, this idea is implemented in a neuromorphic circuit scheme using CMOS integrated HfO2-based memristive devices. The implemented two-layer neural network learns in a self-organized manner without positive reinforcement and exploits the inherent variability of the memristive devices. A combined experimental and simulation-based parameter study is presented to find the relevant system and device parameters leading to a compact and robust memristive neuromorphic circuit that can handle association tasks.
Spatiotemporal projections of extreme Temperatures over Algeria using CMIP6-MME global climate models outputs
Authors: ABED Salah SAHABI , Selmane Ahmed Nour-EL-Islam
Published: November 2023

Algeria is vulnerable to climate extremes due to its large surface, growing population, and diverse valuable and fragile ecosystems. We assess in this paper the spatiotemporal projections of extreme temperatures over Algeria derived from the adjusted multi-model ensemble mean (MME) data derived from eleven daily historical simulations of CMIP6-GCMs models that participated in IPCC Sixth Assessment Report (AR6), considered the most authoritative source on climate change. We assess the projected spatial patterns of twelve extreme temperature indices defined by the Expert Team on Climate Change Detection and Indices. The evolution of the projected changes is examined for two future time periods: the mid-future 2041–2070 and the far future 2071–2100, relative to the baseline period 1985–2014, under three Shared Socio-economic Pathways (SSP) scenarios: low emission SSP1-2.6; medium emission SSP2-4.5 and high emission scenario (SSP5-8.5). The selected climate indices reflect the intensity (TXx, TNx, TXn, TNn and DTR), frequency (TX90p and TN10p) and duration (WSDI, SU, CSDI, TR, and FD) of the extreme thermal events. The MME Projections show a heightened warming. Future Climate features depict a continuous increase in the occurrence of hot days and nights and an amplification of the intensity of the extreme temperature and an extension of the heat wave duration period. These positive changes are likely to be more important by the end of the 21st century in the southern region than in the northern one and under SSP5-8.5 than in the remaining scenarios, with the exception of the occurrence of summer days (SU), where the northern region is projected to experience relatively more summer days as compared to the southern region. A stabilization of the upsurge trend is remarkably observed for most indices under SSP1-2.6 starting from the 2050s. In the last decades, Algeria has been experiencing recurrently the impacts of extreme weather leading to irreversible impacts. The projected extreme climate events in Algeria underscore the urgency of climate change mitigation and adaptation measures. The future changes depicted in this study should help to assess the distribution of the impacts across different regions of Algeria in order to enhance resilience, establish the appropriate adaptation responses and improve disaster preparedness.
Reassessment of casual association between body mass index and site-specific solid cancers: A comprehensive Mendelian randomization study
Authors: Lai Jianxiong , Xu Yuanhui , Li Jian
Published: November 2023

Purpose
Previous Mendelian randomization (MR) studies on association between body mass index (BMI) and cancer only focused on several common cancers, and the genetic instruments varied, making the effect of BMI on other cancers unclear and direct comparison across all cancer types difficult. Our comprehensive MR aims to reinforce the established evidence of the association.
Methods
We conducted a unified MR analysis to reassess the association between BMI and 19 site-specific solid cancers. Genetic instruments for BMI were extracted from genome-wide association studies (GWAS) of 806,834 European individuals and 86,757 East Asian individuals, respectively. The associations of genetic instruments with 19 site-specific solid cancer (sub)types extracted from the FinnGen study, the Biobank Japan (BBJ) project, and international consortia were examined by using various MR methods.
Results
For lung, endometrial and breast cancers in the FinnGen study, estimation of the MR analysis aids the triangulation of the positive or inverse association between genetically predicted BMI and these (sub)types. In several large consortia in the European population, our results strengthen confidence in previously established positive findings for lung, ovarian, endometrial and breast cancer and null findings for prostate cancer. In the BBJ project, no causal association was found between BMI and cancers, although a possible increased risk for endometrial cancer may exist.
Conclusion
Our comprehensive MR estimates reinforce the causal role of BMI in some solid cancers in the European population but cannot rule out a possible causal role in some other cancer (sub)types and in other populations.
A piezoelectric sensor with high accuracy and reduced measurement error
Authors: Ghemari Zine , Belkhiri Salah , Saad Salah
Published: November 2023

In this work, the main focus is on studying the effects of piezoelectric materials and exploring the functionality of piezoelectric sensors. The physical behavior of the sensor is thoroughly examined and a mathematical formula relating the accuracy of the sensor to relative movement or vibratory displacement is derived. The developed model is verified through simulations and experimental tests. By carefully selecting the appropriate damping rate, it is possible to enhance the parameters of the piezoelectric sensor and advance the technique of vibratory analysis. Overall, this research aims to enhance our understanding of piezoelectric materials and sensors, and how they can be effectively utilized in various applications involving vibratory analysis. The findings from this study can contribute to better design and implementation of piezoelectric sensors, improving their accuracy and effectiveness in capturing and analysing vibratory movements.
End-to-End Modeling of the TDM Readout System for CMB-S4
Authors: Goldfinger David C. , Ahmed Zeeshan , Barron Darcy R. , Doriese W. Bertrand , Durkin Malcolm , Filippini Jeffery P. , Haller Gunther , Henderson Shawn W. , Herbst Ryan , Hubmayr Johannes , Irwin Kent , Reese Benjamin , Sapozhnikov Leonid , Thompson Keith L. , Ullom Joel , Vissers Michael R.
Published: November 2023

The CMB-S4 experiment is developing next-generation ground-based microwave telescopes to observe the Cosmic Microwave Background with unprecedented sensitivity. This will require an order of magnitude increase in the 100 mK detector count, which in turn increases the demands on the readout system. The CMB-S4 readout will use time division multiplexing (TDM), taking advantage of faster switches and amplifiers in order to achieve an increased multiplexing factor. To facilitate the design of the new readout system, we have developed a model that predicts the bandwidth and noise performance of this circuity and its interconnections. This is then used to set requirements on individual components in order to meet the performance necessary for the full system. We present an overview of this model and compare the model results to the performance of both legacy and prototype readout hardware.
The effect of psychoactive substances used on clinical outcomes in injured drivers referred to emergency medicine; case-control study
Authors: Tavakoli Nader , Mousavi Zahra , Amanollahi Alireza , Babeveynezhad Tannaz
Published: November 2023

Objective
The use of psychoactive substances increases the risk of accidents. This study evaluated the relationship between the type of psychoactive substances among traffic injured admitted to the medical center.
Methods
Injured drivers (100 used drugs), (260 control group), who were transferred to 7-Tir Hospital from April 2021 to March 2022 were studied. The information related to the accident scene, personal characteristics, and the substance used was collected from the police and the medical center documents. We used multiple logistic regression to find the important factor in outcomes.
Results
The mean age of the case group (37.49 ± 13.61) compared to the control group (34.18 ± 14.05) was significant (p = 0.044). The most common substances in the case group were opioids which had the highest mean age (41.90 ± 13.541). Injured who used sedatives had higher signs of head trauma than the others. Also, being guilty had a remarkable difference in the groups (94.6 vs 62.4 p = < 0.001). Motorcyclist drivers were 185(65%) responsible for the accident, in addition, 69(69%) were in the case group. Head trauma, type of accident, and level of triage had a significant effect on the death of the injured.
Conclusion
Using sedatives causes increased head trauma. Driving under the effect of psychoactive drugs is more common among motorcycle drivers, and a large percentage of them are guilty of accidents.
Risk factors of renal survival in patients with microscopic polyangiitis and severe renal injury in 6 months
Authors: Wang Xiaoying , Hao Weiwei , Dong Fang , Liu Rui , Zhang Lie , Li Wei , Liu Shengyun
Published: November 2023

Objective.
Patients with life-threatening microscopic polyangiitis (MPA) with kidney involvement have poor prognosis. This study aimed to identify the risk factors of progressing to end-stage renal disease (ESRD) in 6 months for patients with MPA and kidney involvement.
Methods.
Inpatients with MPA and kidney involvement and at least one follow-up in 6 months after therapy were included and divided to the ESRD or non-ESRD groups according to outcome at 6 months after therapy. Baseline clinical characteristics, immunosuppressive therapies and clinical and biological data prospectively collected during follow-up visits were analysed.
Results.
Patients were divided into the ESRD (N = 73) and non-ESRD groups (N = 89) according to outcomes. More female patients were included in the ESRD group than in the non-ESRD group (64% vs 48%, p = 0.041). Patients in the ESRD group showed decreased cell count in blood routine examination, elevated levels of proteinuria over a 24 h period, lowered C3 levels, decreased lymphocyte counts (especially T and CD4 + lymphocytes), higher rates of cardiovascular and nerve system involvement according to BVAS value criteria and lower frequency of glucocorticoid (GC) or cyclophosphamide (CTX) treatment than those in the non-ESRD group (all p < 0.05). After adjustment for potential confounders, non-ESRD survival was shown to be negatively associated with cardiovascular involvement (HR 0.563, 95% CI 0.323 to 0.981, p = 0.043) and positively associated with GCs (HR 2.041, 95% CI 1.079 to 3.861, p = 0.028) and CTX treatment (HR 1.913, 95% CI 1.027 to 3.565, p = 0.041).
Conclusions
Amongst patients with MPA and active kidney involvement, GCs and CTX therapy were protective factors of progressing to ESRD within 6 months, whereas cardiovascular involvement was an aggravating factor.
Transferability of a European-derived Alzheimer’s Disease Genetic Risk Score across Multi-Ancestry Populations.
Authors: Lambert Jean-Charles
Published: November 2023

We built a genetic risk score (GRS) from the most complete landscape of the Alzheimer disease (AD) genetics. We extended its analysis in 16 European countries and observed a consistent association of this GRS with AD risk, age at onset and cerebrospinal fluid (CSF) AD biomarker levels regardless of the Apolipoprotein E (APOE) genotype. This GRS was also associated with AD risk (independently of APOE) with a decreasing order of magnitude in those with an European-American, North-African, East-Asian, Latin-American, African-American sub-Saharan African and Indian background respectively. No association of the GRS to AD was seen in sub-Saharan African and Indian populations. This GRS captures information specific to AD as its association decreases as the diagnosis broadens. In conclusion, a simple GRS captures shared genetic information specific to AD between multi-ancestry populations. However, more population diversity is needed to better understand the AD genetic complexity across populations.
Effectiveness of the Forest Pests and Diseases Control Methods on the Amount of Industrial Wood Production: A Deep Learning Analysis
Authors: Sevinç Volkan
Published: November 2023

Industrial wood production is a critical component of many countries, providing raw materials for a range of products like construction materials, paper, and pulp. However, the industry faces various challenges, including the impact of forest pests and diseases on timber quality and yield. These threats can lead to significant economic losses for the wood products industry. Thus, effective pest and diseases control strategies are crucial for ensuring sustainable industrial wood production. These strategies typically involve a combination of preventative and control measures, including the use of mechanical, chemical, biotechnical, and biological control methods. The constructed deep learning model shows that all methods have enhancer effects on the amount of industrial wood, albeit at different levels. Thus, the most effective methods in terms of increasing industrial wood production are chemical control methods, while the second most effective methods are mechanical control methods. The third effective methods, on the other hand, are biological control methods. However, biotechnical methods were found to be the least effective methods compared to the other ones.
AMP-RNNpro: A two-stage approach for identification of antimicrobials using probabilistic features
Authors: Shaon Md. Shazzad Hossain , Karim Tasmin , Hasan Md. Zahid , Moustafa Ahmed , Sultan Md. Fahim
Published: November 2023

Background
The necessity to detect antimicrobial peptides (AMPs) using machine learning and deep learning arises from the need for efficiency, accuracy, and the ability to process and analyze large and complex datasets. These tools can complement experimental approaches, accelerate the discovery of AMPs, and contribute to developing effective antimicrobial therapies, especially in the face of increasing antibiotic resistance.
Results
This study introduced AMP-RNNpro based on Recurrent Neural Network (RNN), an innovative and efficient model for detecting AMPs, which has been constructed based on eight feature encoding methods that are selected according to four criteria: amino acid compositional, grouped amino acid compositional, autocorrelation, and pseudo-amino acid compositional to represent the protein sequences for efficient identification of AMPs by computational methods. In our framework, two-stage predictions have been conducted. At first, an analysis is performed using 33 baseline machine-learning models based on these features. Six models have been selected for further study through performance comparisons using rigorous performance metrics. In the second stage, probabilistic features are generated by deploying these models based on each feature and they are aggregated to be fed into our final meta-model, leading to the precise and time-effective prediction of AMPs. The top 20 features that played greater importance in our model's outcome included AAC, ASDC, and CKSAAGP features that were significantly related to detection and drug discovery. Compared to other state-of-the-art methods, the proposed framework, AMP-RNNpro excels in the indentation of novel AMPs in accuracy and precision, achieving 97.15% accuracy, 96.48% sensitivity, and 97.87% specificity.
Conclusions
Consequently, our approach can identify AMPs more accurately and rapidly, along with identifying features that could influence the effectiveness of potential treatment discoveries. We built a user-friendly website for the accurate prediction of AMPs based on the proposed approach which can be accessed at AMP-RNNproWebsite.
Analyzing CO2 Emissions Effect of Financial Development while Accounting for Common Factors in the GCC. Is the Effect Asymmetric?
Authors: Hasanov Fakhri J. , Shannak Sa’d , Mukhtarov Shahriyar , Suleymanov Elchin
Published: November 2023

Ignoring common factors can lead to erroneous findings and misleading policy recommendations, according to panel time-series literature. The same consequences occur if the nature of a factor’s effects is incorrectly considered. We investigated CO2 emission effects of financial development (FD) alongside income and international trade in Gulf Cooperation Council (GCC) countries. The Asymmetric Pooled Mean Group augmented with common unobserved factors - a cutting-edge method allowing to discover not only the features of the pooled panel but also the characteristics of each country - was applied to data for 1992–2021. There is no such application for GCC countries, and only one internationally to our knowledge. We show that accounting for factors common to GCC countries is important, as ignoring them makes the CO2 emissions effects of FD flawed. The effects are asymmetric: upturn of FD leads to lower emissions than its downturn. Another key finding is that CO2 emissions in GCC countries may converge to an identical relationship. In designing CO2 emissions mitigation policies, the following points should be considered: directing financial resources toward eco-friendly technologies, energy transitions, and sectors; accounting for global and regional common factors; close cooperation across the region countries due to common factors and convergence.
Study on the Inclusion Mechanism of Sarafloxacin/β-cyclodextrin Inclusion Complex
Authors: xingcan  , Bing  , Min  , Jiyu
Published: November 2023

The purpose of this study is to explore the inclusion mechanism of sarafloxacin/β- cyclodextrin inclusion complex and explain the fundamental reasons for the improvement of physical and biological properties of cyclodextrin inclusion complex. Through phase solubility analysis, continuous change techniques of chemometrics, nuclear magnetic resonance(NMR) and molecular dynamics simulation techniques, the inclusion complex of sarafloxacin/β-cyclodextrin was studied by chemometrics, molecular docking and one-dimensional and two-dimensional nuclear magnetic resonance spectroscopy. The characterization experiment proved that the inclusion complex of sarafloxacin/β-cyclodextrin was successfully prepared. Finally, the dissolution efficiency of sarafloxacin/β-cyclodextrin inclusion complex was determined in different media. According to the correlation classification, the phase solubility analysis curve is AL. in the continuous change analysis results of chemometrics, when the molar ratio of sarafloxacin is 0.5, the solubility of sarafloxacin is the highest. The result of one-dimensional nuclear magnetic resonance analysis showed that the proton integral area ratio of sarafloxacin to β-cyclodextrin was 1：1. The results showed that the stoichiometric ratio of sarafloxacin/β-cyclodextrin inclusion complex was 1：1. The results of two-dimensional nuclear magnetic resonance spectroscopy and molecular dynamics simulation show that in the structure of sarafloxacin/β-cyclodextrin inclusion complex, several hydrogen bonds are formed between the drug molecule of sarafloxacin and the inner wall of β-cyclodextrin. And sarafloxacin enters into β-cyclodextrin from the side of the larger cavity, its material structure is stable, the matching of surface hydrophobicity and electrostatic force is reasonable, and the overall repulsion is low. The dissolution efficiency of sarafloxacin/β-cyclodextrin inclusion complex in different media is significantly higher than that of its physical mixture and has excellent properties. Through the explanation of the package and mechanism, this study plays a positive role in improving the dissolution efficiency of many insoluble drugs and the promotion and application of fluoroquinolones.
Optimal Control for Fractional Order Dynamics of Tumor Growth
Authors: Nortey Solomon , Fellah Mohammed A. , Akindeinde Saheed O. , Moore Stephen E.
Published: November 2023

This paper concerns the analysis and optimal control of fractional order model of tumor cells and the body’s immunological response using Atangana-Baleanu-Caputo derivative fractional operator. The model consists of spawning cells (S), reposing cells (R) and tumor cell (T) where we have used the Hattaf-Yousfi functional response for the activation of the reposing cells in the presence of tumor cells. We investigate the model’s existence and stability and present numerical results using a modified predict-evaluate-correct-evaluate (PECE) method of Adams-Bashforth-Moulton. We also study the Fractional optimal control problem (FOCP) in order to minimize tumor cell density. The Fractional Pontryagin maximum principle (FPMP) is used to characterize the fractional optimal control problem and we implement the forward-backward PECE method to determine the extremals of the problem. We study the optimal control dynamics of tumor growth via several numerical simulations.
Stress or failure? An experimental protocol to distinguish the environmental determinants of decision-making
Authors: Vecchi Martina , Vitt Nicolai
Published: November 2023

Are economic decisions affected by short-term stress, failure, or both? Such effects have not been clearly distinguished in previous experimental research, and have the potential to worsen economic outcomes, especially in disadvantaged socioeconomic groups. We validate a novel experimental protocol to examine the individual and combined influences of stress, failure, and success. The protocol employs a 2x3 experimental design in two sessions and can be used online or in laboratory studies to analyse the impact of these factors on decisionmaking and behaviour. The stress protocol was perceived as significantly more stressful than a control task, and it induced a sizeable and significant rise in state anxiety. The provision of negative feedback (“failure”) significantly lowered participants’ assessment of their performance, induced feelings of failure, and raised state anxiety.
JEL Classification code: C9, D91.
Cu isotope fractionation between Cu-bearing phases and hydrothermal fluids: Insights from ex situ and in situ experiments
Authors: Qi Dongmei , Zhang Chao , Lazarov Marina
Published: November 2023

Cu isotope ratios have been widely applied to fingerprinting metal sources, tracking fluid pathways, and tracing mineralization processes, for which knowledge of isotope fractionation is required. This paper presents new experimental calibration data of Cu isotope fractionation between Cu-bearing minerals (native Cu and cuprite) and Cl-bearing hydrothermal fluids at 25–800 °C and 0.1–200 MPa. The experiments were performed either using a polytetrafluoroethylene (Teflon) beaker on a hotplate, a rapid heat/rapid quench argon cold seal pressure vessel (RH/RQ Ar-CSPV), or a large volume fluid reactor, which enabled fluid sampling ex situ (the former two) and in situ (the latter). Three setups were designed to investigate Cu isotope fractionation (Δ65Cufluid-mineral): (1) associated with Cu(I) dissolution, Cu(I) disproportionation as well as oxidation of Cu(0) (native copper) and Cu(I) in Cu ± Cu2O + HCl systems at temperatures of up to 800 °C and pressures of up to 200 MPa; (2) related to Cu-Au alloying processes in the Cu + NaCl/HCl system at 600 °C and 150 MPa; (3) to evaluate the influences of different sampling techniques (ex situ vs. in situ) and superimposed cooling processes. The selected system is Cu2O + NaCl + 0.2 m HAc/NaAc (pH-buffer), and runs were conducted at 200–250 °C and 20 MPa.

Δ 65Cufluid-mineral shows the least variation during solid separation from source fluids, generally <0.16 ± 0.03‰. Positive Δ65Cufluid-mineral values are found in most runs, excluding cuprite dissolution in NaCl/HCl solutions at 200–250 °C, 20 MPa, and 800 °C, 200 MPa. Cu oxidative leaching into Cu(I) results in decreasing Δ65CuCu(I)-Cu(0) values from 0.12 ± 0.05‰ to 0.07 ± 0.05‰, and –0.30 ± 0.03‰ at 25, 50, and 200 °C, respectively. In contrast, Cu dissolution at high temperatures (600–800 °C) leads to Cu(I)-containing quench fluids and subsequent native Cu precipitates. Both products are enriched in heavy isotopes by up to 5‰, caused by preferential enrichment of 65Cu at the surface layer during the alloying-induced diffusion transport process. Cuprite oxidative leaching in HCl leads to fluids enriched in Cu(II), and the corresponding Δ65CuCu(II)-Cu(I) increases from 0.52 ± 0.04‰ at 25 °C to 0.89 ± 0.02‰ at 50 °C. Fluids are enriched with light isotopes (63Cu) during cuprite dissolution at 200, 250, and 800 °C, i.e., 0–0.55 ± 0.04‰ lower than the precursor. At 250–300 °C, Cu(I) disproportionation into Cu(II) and Cu(0) dominates the observed isotope fractionation, yielding Δ65Cufluid-Cu2O up to 0.59 ± 0.03‰ and Δ65CuCu(0)-Cu2O up to –0.28 ± 0.02‰.

Rapid cooling (3–25 K s–1) relative to slow cooling (0.014 K s–1) can cause phase separation as well as significant isotope fractionation, particularly if fluids cool from an intermediate high temperature to ambient temperature (e.g., from 200–300 to 25 °C), which highlights the importance of kinetic processes that may potentially alter the isotope composition of natural ore-forming fluids.
Design and application of soft sensors in rural sewage treatment facilities
Authors: Li Bing , Mao Siyuan , Tian Tuo , Bi Huaibin , Tian Yuxin , Ma Xueyan , Qiu Yong
Published: November 2023

Recently, with the growing demand for water quality monitoring, soft measurement sensors have drawn public attention, which can overcome the drawbacks of high cost and long time needed in traditional measurement methods. In this study, a machine learning-based soft monitoring sensor was developed to simultaneously monitor four water quality indicators including COD, NH4+-N, NO3--N, PO43--P. Firstly, specialized experimental equipment and calibration methods were developed to generate a matching dataset that collected over 94,000 data points. Secondly, five models including Multiple Linear Regression, Ridge Regression, AdaBoost, Decision Tree Regression, and Bagging Regression were constructed and compared. The learning accuracy of the models ranged from 0.8860 to 0.9999, among which the predicted value of Bagging Regression is highly fit to the true value. Subsequently, the fuzzy grade method was adopted to reduce the prediction error and strike a balance between efficiency and accuracy. Finally, the designed soft sensor was used for real-time monitoring at three monitoring points in Changzhou, China from September to October 2020, and the results proved the feasibility of the soft sensor in practical application. This study provided a fast and accurate method for water quality measurement, which is of great significance for the management of rural sewage treatment facilities.
Reservoir capacity loss and sedimentation assessment of Dholbaha dam located in Punjab, India using remote sensing and bathymetric survey techniques
Authors: Singh Mahesh Chand , Prashar Avishek , Singh Jaswinder , Kumar Sukhdeep
Published: November 2023

A study was undertaken to assess the live storage capacity of the Dholbaha reservoir located in Punjab, India using remote sensing and bathymetric survey techniques. The primary objectives included comparing the estimated capacity with findings from a bathymetric survey, refining the elevation-area-capacity curve, and determining the rate of capacity loss due to sediments deposition. This analysis utilized water elevation data spanning from 1987 to 2022 and satellite imageries from Landsat 7, 8 & 9. The satellite data was processed using software tools such as Erdas Imagine and ArcGIS. The water extent of the reservoir was calculated using Modified Normalized Difference Water Index (MNDWI). Over the course of 34 years, the reservoir experienced reductions in its dead, active, and total storage capacities by 81.5%, 19.7%, and 28.9%, respectively. These changes correspond to annual depletion rates of 2.40%, 0.58%, and 0.85%, respectively. The sediment yield from the surrounding catchment area was determined to be approximately 1203.56 m3/km2/year. The findings demonstrate substantial declines in Dholbaha reservoir storage capacities over a 34-year period (1987-2022) attributable to sedimentation. This underscores the critical need for sustainable water management and provides key insights for monitoring and strategic planning. The study advocates immediate, targeted interventions within the catchment area to mitigate sedimentation in the Dholbaha reservoir, highlighting the importance of ongoing sedimentation rate monitoring and collaboration with stakeholders for informed reservoir management and sustainable solutions to maintain water capacity for the region.
Laboratory study of the effect of vegetation and gravel on runoff parameters under variable rainfall intensities
Authors: Ghazvinian Hamidreza , Karami Hojat
Published: November 2023

The present study aims to evaluate the performance of the impervious surface as a control (O), sandy loam substrate (SL), gravel (G), gravel with geocell layer (GGE), rosemary (R), rosemary with geocell layer (RRE), turf (T), and turf with geocell layer (TGE) in the reduction of runoff volume, time-to-start runoff (TR), runoff coefficient (C), time-to end runoff (TER), peak flow rate (PF), time to peak (TP), and time base (TB) in the laboratory dimension under three different scenarios of rainfall intensity and two different slopes using a rainfall simulator. The results revealed a significant difference between the data at the level of 5% in all cases. Generally, three rainfall scenarios for all hydrological parameters TR, TER, TP, TB, C, and PF were classified into different groups. In all cases, GGE treatment performed better than that of the rest of the test groups in reducing runoff and cumulative volume. Further, treatments O and GGE experienced the highest and lowest flow rates, respectively. For a specific scenario of rainfall intensity and slope, the value of C is the lowest for GGE treatment. Finally, the implementation of geocell in the pavements was able to delay the time to start runoff.
Potentiality of Nucleoside as Antioxidant by Analysis on Oxidative Susceptibility, Drug Discovery, and Synthesis
Authors: Liu Zai-Qun
Published: November 2023

Nucleosides are sensitive sites towards oxidations caused by endogenous and
exogenous oxidative resources, and a large number of the produced DNA lesions behave
as pathogenesis eventually. We herein analyze oxidative modes of nucleosides and structure-
activity relationships of some clinical nucleoside drugs. Together with our previous
findings on the inhibitory effects of nucleoside derivatives against DNA oxidation, all these
results imply a possibility for nucleoside to be a new member in the family of antioxidants.
Then, some novel synthetic routines of nucleoside analogs are collected to reveal
the applicability in the construction of nucleoside antioxidants. Therefore, it is reasonable
to envision that the nucleoside antioxidant will be a novel topic in the research
of both nucleosides and antioxidants.
Overview of Natural Supplements for the Management of Diabetes and
Obesity
Authors: Singh Sonia , Shukla Arpit , Sharma Shiwangi
Published: November 2023

Bioactive compounds found in various natural sources, such as fruits, vegetables, and
herbs, have been studied for their potential benefits in managing obesity and diabetes. These
compounds include polyphenols, flavonoids, other antioxidants, fiber, and certain fatty acids.
Studies have found that these compounds may improve insulin sensitivity, regulate blood sugar
levels, and promote weight loss. However, the effects of these compounds can vary depending on
the type and amount consumed, as well as individual factors, such as genetics and lifestyle.
Nutraceutical substances have multifaceted therapeutic advantages, and they have been reported
to have disease-prevention and health-promoting properties. Several clinically used nutraceuticals have been shown to target the pathogenesis of diabetes mellitus, obesity, and metabolic syndrome and their complications and modulate various clinical outcomes favorably. This review
aims to highlight and comment on some of the most prominent natural components used as antidiabetics and in managing obesity.
Energy Management System for Distributed Energy Resources using Blockchain Technology
Authors: Kavin R. , Jayakumar J.
Published: November 2023

:

Power generation in today’s world is of utmost importance, due to which blockchain is
used for the categorization and formation of decentralized structures. This paper has proposed decentralized energy generation using a nester, i.e., energy sharing without third-party intervention.
Decentralized blockchain technology is applied to ensure power sharing between buyer and seller,
and also to achieve efficient power transmission between prosumer and consumer. Energy management is associated with controlling and reducing energy consumption. Blockchain technology
plays a major role in distributed power generation, for example, power-sharing (solar and wind
energy), price fixation, energy transaction monitoring, and peer-to-peer power-sharing. These are
operations performed by blockchain in renewable power generation. Solar power generation using
blockchain technology can obtain an impact resting upon the power generation system. Distributed ledger is the key area of blockchain technology for recording and tracking each transaction in
the distribution system to improve the efficiency of the overall transmission system. A smart contract is another important tool in the blockchain technology, which is issued to confirm an assent
between buyer and seller before starting any energy transaction without external intervention and
also to avoid time delay. Maximum power point tracking is conducted in PV cells using blockchain technology. Blockchain influences energy management systems to improve the utilization
of energy, optimize energy usage, and also to reduce the cost.
Investigation of Development of Phonology using Artificial Intelligence: A
Preliminary Study
Authors: Kumar Vijay , Jain Anjani , Saini Jitendra Kumar , Bhardwaj Leena
Published: November 2023

Background:

Investigation of the development of acquisition of phonological processes is a very important phenomenon to predict language development in
childhood. Phonological development refers to the gradual acquisition of an adult-like
speech system used to convey meaning in a language. Adequate phonological development can lead to higher speech intelligibility, essential for perception and speech
production. The test battery approach for phonological assessment includes formal as
well as informal testing modalities. Speech intelligibility is a vital parameter for the
assessment of phonological development. This is done via scoring collected audio
speech samples, followed by IPA transcription and scoring and analysis of data manually. The primary objective of the study was to investigate the speech intelligibility
score across real-timed stimuli (rhyming, storytelling, open-ended questions, and picture description tasks) across two age categories, i.e., 3-4 and 4-5 years among 40
Hindi-speaking children.

Methods:

A total of 40 children (15 girls and 25 boys) in the age range of 3 to 5 years
were randomly selected from a junior high school in New Delhi, India. Groupwise
speech intelligibility score was calculated for rhyming, storytelling, open-ended questions, and picture description tasks. Results: It was observed that the speech intelligibility score for open-ended questions was significantly higher in the 4-5 years group
(94.09 ± 3.7) than the 3-4 years (89.83 ± 8.2), t (1, 38) =2.12, p =0.04). However, no
significant improvement in rhyming task [t (1, 38) =1.14, p =0.18), storytelling [t (1,
38) =1.81, p =0.07), and picture description [t (1, 38) =1.89, p =0.06) was observed.

Conclusion:

Chances of error in conventional method of phonology assessment still
persists which may be controlled using Artificial Intelligence (AI). The target phonetic stimulus can be customized based on the linguistic experience and environment.
Artificial Intelligence (AI) in Battle Against COVID-19
Authors: Vengusamy Sivakumar , Rajendran Hegan A.L.
Published: November 2023

In Wuhan China, the world’s most dangerous virus is discovered, which is
named COVID-19 by World Health Organization. Social distancing is one of the
powerful methods to control this virus as it is realized that lockdown is not a permanent
solution. This research chapter aims to identify the major activities influencing the
transmission of the coronavirus spread using Artificial Intelligence bound models. To
conduct this research in the right direction, movement control restriction,
meteorological parameters, and air pollution levels information are collected from
various valid websites. End-to-end data pre-processing steps are carried out in detail to
handle the outliers and missing values and investigate the correlation between
dependent and independent variables. Multiple linear regression, neural networks,
decision trees, and random forests are chosen to fulfil the objective of this research by
identifying the most influential activities and other parameters. Here, the model’s
performance evaluation is done using the R2
value, mean absolute error and mean
squared error. The predicted values are plotted against the actual value to illustrate the
error patterns. Among all models, random forest and decision tree models are proven to
give the highest accuracy of 93 percent and 91 percent respectively. Prescriptive
analysis has been further analyzed by performing feature importance extraction from
the highly accurate models to identify the most impactful parameters the government
authority and healthcare front-liners focus on to mitigate the number of COVID-19
cases daily.
Potential Applications of AI and IoT Collaborative Framework for Health Care
Authors: Jacob Lija , Thomas K.T. , Shukla Samiksha
Published: November 2023

Digital technology has infiltrated the entire planet. Artificial Intelligence
(AI) and the Internet of Things (IoT) are the two buzzwords that became popular in the
current digital world, especially in recent decades. Both these technologies have their
contribution in various domains. The existing frameworks will benefit from the AI-IoT
collaborative system, which will assist them in having more intelligent or smart
responses. Furthermore, these collaborative systems can provide improved devices with
better decision-making capacity to facilitate the users. AI can work with IoT to increase
functional precision in the healthcare domain by automating and tracking, monitoring,
managing, optimizing, and predicting processes in 24x7 mode. Health professionals are
the people involved in activities whose primary commitment is to improve the
wellbeing of the community. They are a group of people who face various obstacles,
including their health and safety concerns, especially during pandemic outbreaks. This
book chapter aims to illustrate the impact of AI and IoT on the health care domain and
the challenges that healthcare professionals face, especially when dealing with such an
pandemic and suggests some potential health care advancements through AI and IoT.
Role of Social Media Platforms to Maintain Social Distancing in COVID-19 Pandemic
Authors: Vengusamy Sivakumar , Visvanathan Danapriya
Published: November 2023

Though it has been some time since the outbreak of the novel COVID-19
disease, it still poses a threat to many people worldwide. Connections have been lost
due to the practice of social distancing, both on a personal and a societal level. Due to
the global prohibitions on large-scale face-to-face meetings and activities, social media
platforms have emerged as a lifesaver for humanity. The role of social media platforms
has grown increasingly important for people to express themselves and communicate
with others. Besides, the world has also witnessed large-scale events being organized
on social media platforms, making connections and interactions with friends, family,
and the community via social media networks, as well as the transformation of
educational activities into digital activities. Thus, it is pertinent to comprehend the role
of social media platforms in maintaining social distancing and online connections
during the COVID-19 pandemic. This research aims to generate a discussion on the
importance and role of social media platforms to maintain social distancing among
individuals. It typically emphasizes three main themes: (1) the importance of social
media platforms in establishing as well as improving social distancing during the
COVID-19 crisis, (2) the role of social media platforms in maintaining social
connections and interactions among individuals during the pandemic, and (3) the
impact of Coronavirus towards the use of social media.
Role of Climate-Driven Factors on Bean Leaf Beetle, Corn Earworm and Stinkbug Populations, Control and their Effects on Soybean Growth and Productivity
Authors: Mukatuni Arinao
Published: November 2023

Soybean is a crucial crop that is recognised globally for its high-value protein, vitamins, carbohydrates, fibre, and oils. However, the production of soybeans is frequently influenced by biotic stress factors such as bean leaf beetles (Cerotoma trifurcate), grasshoppers (Schistocerca americana), corn earworms (Helicoverpa zea) and stinkbugs (Halyomorpha halys). However, these insect pests were discovered to be both beneficial and harmful to crop growth and productivity, particularly, in soybeans. According to the literature, the rise in temperature causes an increase in insect pest populations, thereby severely influencing the growth, and yield quality of many crops. Less precipitation also contributes to drought stress, and plants undergoing water-deficit stress produce fewer secondary metabolites rendering them vulnerable to attacks by these insects. Similar effects were also revealed due to the rise in atmospheric CO2 levels that led to the adverse weather effects that caused enhanced reproduction and spread of pest insects. This chapter, therefore, explores the role of climate change-induced factors, such as temperature, precipitation patterns and rising atmospheric CO2 on insects’ distribution, and reproductive patterns, as well as their subsequent influence on crop growth and productivity in soybeans. The review also briefly discusses the chemical, biological and biotechnological approaches of insect pest control that have been employed effectively to combat losses of crop production. Side effects, cost effectiveness and the ability of new biotechnological methods to target specific pests are also discussed in this chapter.
Pyometra in a red fox (Vulpes vulpes) caused by a Staphylococcus pseudintermedius infection
Authors: Caliskan N. , Vandekerckhove A. , Rolly E. , Forrez E. , Roels S.
Published: November 2023

A female adult red fox was found dead in the Flemish countryside (Belgium). At necropsy, a pronounced global distention of the uterus was noted with a prominent dilation of the upper end of the right horn and two dilations of the external wall (myometrium) of the left horn. The uterine lumen was filled with a green to yellowish pasty material. A pure culture of Staphylococcus pseudintermedius was isolated. The diagnosis of pyometra caused by S. pseudintermedius was made. Pyometra in wild canids has been rarely reported. The cause of death is suggested to be similar to the cause described in dogs, namely septic shock. To the authors’ knowledge, this is the first case report of closed pyometra with isolation of S. pseudintermedius in a red fox.
Integración del control de constitucionalidad en Latinoamérica
Authors: Cumba Narváez César Augusto
Published: November 2023

La Independencia Hispanoamericana motivada por la discusión de las Cortes de Cádiz (1810-1812) de seguir manteniendo el colonialismo, más la promulgación de la Constitución de Cádiz del 19 de marzo de 1812, la cual contenía disposiciones discriminatorias contra los americanos, propició la independencia Latinoamericana; así como el de iniciar su propio proceso constitucional, convergiendo este proceso con la influencia del sistema jurídico inglés common law y la influencia del sistema jurídico Civil Law, considerado como un rezago de la filosofía de la Revolución Francesa reinante en Europa. El proceso de constitucionalidad en Latinoamérica a mediados del siglo XIX e inicios del siglo XX trajo consigo la influencia del control de constitucionalidad instaurado en el sistema jurídico inglés, el cual propiciaba la supremacía de la Constitución o la inconstitucionalidad de las leyes federales, basados en las sentencias del juez inglés Edward Coke, en el caso “Bonham” (1610), y muy posteriormente en el caso “Marbury vs. Madison” del juez norteamericano John Marshall (1803), dentro del sistema jurídico common law; así como en el control de constitucionalidad del sistema jurídico Civil Law, el cual consistía en limitar al Poder Judicial a la aplicación de la ley, dictada únicamente por el legislador. El control de constitucionalidad latinoamericano fue impregnándose de manera paulatina en la constitución de cada país a medida que las condiciones sociales y políticas se tornaban factibles para innovar sus contenidos, es lo que este artículo analiza en las fuentes de investigación citadas.