bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of highly expressed genes and efficient core promoters specific to buffalo skeletal muscles
Authors: Huang Jieping , Guo Duo , Zhu Ruirui , Wang Haopeng , Yang Chunyan , Shi Deshun , Shang Jianghua
Published: January 2025

Abstract. An efficient promoter with specific transcriptional activity plays significant roles in the regulation of expression of exogenous genes. The efficient promoter specific to skeletal muscles can achieve high expression of exogenous genes in skeletal muscles. This is of great significance for the targeted improvement of livestock meat quality by combining gene editing and traditional breeding techniques. To identify efficient promoters specific to the skeletal muscles of buffalo, in the present study, a total of 14 genes, CACNG1, LRRC30, CACNG6, MYOG, VGLL2, MYOD1, KCNA7, DUPD1, PRR32, LBX1, IGFN1, ACTN3, PITX3, and MURC, were firstly screened as skeletal-muscle-specific expressed genes based on high-throughput sequencing data. Among them, only two genes – namely, VGLL2 and CACNG1 – were identified to be specifically and efficiently expressed in the skeletal muscles of buffalo by quantitative reverse transcription polymerase chain reaction (RT-qPCR). Then, the transcriptional activity of different truncated fragments of the upstream putative promoter region of VGLL2 and CACNG1 were evaluated by the dual luciferase reporter gene detection system in mouse C2C12 cells and buffalo skeletal muscle cells. As a result, both core promoters of VGLL2 and CACNG1 were identified to have specifically and efficiently transcriptional activity in skeletal muscle tissue while the transcriptional activity of the core promoters of VGLL2 was more efficient. These results provide significant information for the targeted improvement of meat quality in buffaloes and other livestock animals.
Impact of mineral dust on the global nitrate aerosol direct and indirect radiative effect
Authors: Milousis Alexandros , Klingmüller Klaus , Tsimpidi Alexandra P. , Kok Jasper F. , Kanakidou Maria , Nenes Athanasios , Karydis Vlassis A.
Published: January 2025

Abstract. Nitrate (NO3-) aerosol is projected to increase dramatically in the coming decades and may become the dominant inorganic particle species. This is due to the continued strong decrease in SO2 emissions, which is not accompanied by a corresponding decrease in NOx and especially NH3 emissions. Thus, the radiative effect (RE) of NO3- aerosol may become more important than that of SO42- aerosol in the future. The physicochemical interactions of mineral dust particles with gas and aerosol tracers play an important role in influencing the overall RE of dust and non-dust aerosols but can be a major source of uncertainty due to their lack of representation in many global climate models. Therefore, this study investigates how and to what extent dust affects the current global NO3- aerosol radiative effect through both radiation (REari) and cloud interactions (REaci) at the top of the atmosphere (TOA). For this purpose, multiyear simulations nudged towards the observed atmospheric circulation were performed with the global atmospheric chemistry and climate model EMAC, while the thermodynamics of the interactions between inorganic aerosols and mineral dust were simulated with the thermodynamic equilibrium model ISORROPIA-lite. The emission flux of the mineral cations Na+, Ca2+, K+, and Mg2+ is calculated as a fraction of the total aeolian dust emission based on the unique chemical composition of the major deserts worldwide. Our results reveal positive and negative shortwave and longwave radiative effects in different regions of the world via aerosol–radiation interactions and cloud adjustments. Overall, the NO3- aerosol direct effect contributes a global cooling of −0.11 W m−2, driven by fine-mode particle cooling at short wavelengths. Regarding the indirect effect, it is noteworthy that NO3- aerosol exerts a global mean warming of +0.17 W m−2. While the presence of NO3- aerosol enhances the ability of mineral dust particles to act as cloud condensation nuclei (CCN), it simultaneously inhibits the formation of cloud droplets from the smaller anthropogenic particles. This is due to the coagulation of fine anthropogenic CCN particles with the larger nitrate-coated mineral dust particles, which leads to a reduction in total aerosol number concentration. This mechanism results in an overall reduced cloud albedo effect and is thus attributed as warming.
Measurement Report: Changes in ammonia emissions since the 18th century in south-eastern Europe inferred from an Elbrus (Caucasus, Russia) ice-core record
Authors: Legrand Michel , Vorobyev Mstislav , Bokuchava Daria , Kutuzov Stanislav , Plach Andreas , Stohl Andreas , Khairedinova Alexandra , Mikhalenko Vladimir , Vinogradova Maria , Eckhardt Sabine , Preunkert Susanne
Published: January 2025

Abstract. Atmospheric ammonia (NH3) is a key transboundary air pollutant that contributes to the impacts of nitrogen and acidity on terrestrial ecosystems. Ammonia also contributes to the atmospheric aerosol that affects air quality. Emission inventories indicate that NH3 was predominantly emitted by agriculture over the 19th and 20th centuries but, up to now, these estimates have not been compared to long-term observations. To document past atmospheric NH3 pollution in south-eastern Europe, ammonium (NH4+) was analysed along an ice core extracted from Mount Elbrus in the Caucasus, Russia. The NH4+ ice-core record indicates a 3.5-fold increase in concentrations between 1750 and 1990 CE. Remaining moderate prior to 1950 CE, the increase then accelerated to reach a maximum in 1989 CE. Comparison between ice-core trends and estimated past emissions using state-of-the-art atmospheric transport modelling of submicron-scale aerosols (FLEXPART (FLEXible PARTicle dispersion) model) indicates good agreement with the course of estimated NH3 emissions from south-eastern Europe since ∼ 1750 CE, with the main contributions from south European Russia, Türkiye, Georgia, and Ukraine. Examination of ice deposited prior to 1850 CE, when agricultural activities remained limited, suggests an NH4+ ice concentration related to natural soil emissions representing ∼ 20 % of the 1980–2009 CE NH4+ level, a level mainly related to current agricultural emissions that almost completely outweigh biogenic emissions from natural soil. These findings on historical NH3 emission trends represent a significant contribution to the understanding of ammonia emissions in Europe over the last 250 years.
Atmospheric oxidation of 1,3-butadiene: influence of seed aerosol acidity and relative humidity on SOA composition and the production of air toxic compounds
Authors: Jaoui Mohammed , Nestorowicz Klara , Rudzinski Krzysztof J. , Lewandowski Michael , Kleindienst Tadeusz E. , Torres Julio , Bulska Ewa , Danikiewicz Witold , Szmigielski Rafal
Published: January 2025

Abstract. This study investigated the effect of relative humidity (RH) on the chemical composition of gas and particle phases formed from the photooxidation of 1,3-butadiene (13BD) in the presence of NOx under acidified and non-acidified seed aerosol. The experiments were conducted in a 14.5 m3 smog chamber operated in a steady-state mode. Products were identified by high-performance liquid chromatography, gas chromatography–mass spectrometry, and ultrahigh-performance liquid chromatography coupled with high-resolution mass spectrometry. More than 50 oxygenated products were identified, including 33 oxygenated organics, 10 organosulfates (OSs), PAN, APAN, glyoxal, formaldehyde, and acrolein. Secondary organic aerosol (SOA) mass and reaction products formed depended on RH and on the acidity of the seed aerosol. Based on the Extended Aerosol Inorganics Model (E-AIM), the seed aerosol originated from the acidified and non-acidified solutions was found to exist under aqueous and solid phases, respectively. Although the terms “acidified” and “non-acidified” are true for the solutions from which the seeds were atomized, there are far more fundamental differences between the phase states in which species partition to or from (aqueous/solid), which considerably affects their partitioning and formation mechanisms. SOA mass and most SOA products (i) were higher under acidified seed conditions, where the aerosol particles were deliquescent, than under non-acidified seed conditions, where the aerosol particles did not contain any aqueous phase; (ii) increased with the acidity of the aerosol aqueous phase in the experiments under acidified seed conditions; and (iii) decreased with increasing RH. Glyceric acid, threitols, threonic acids, four dimers, three unknowns, and four organosulfates were among the main species measured under either acidified or non-acidified conditions across all RH levels. Total secondary organic carbon and carbon yield decreased with increasing RH under both acidified and non-acidified seed conditions. The photochemical reactivity of 13BD in our systems decreased with increasing RH and was faster under non-acidified than acidified seed conditions. To determine the contribution of 13BD products to ambient aerosol, we analyzed PM2.5 samples collected at three European monitoring stations located in Poland. The occurrence of several 13BD SOA products (e.g., glyceric acid, tartronic acid, threonic acid, tartaric acid, and OSs) in the field samples suggests that 13BD could contribute to ambient aerosol formation.
Contrasting seasonal patterns in particle aggregation and dissolved organic matter transformation in a sub-Arctic fjord
Authors: Digernes Maria G. , Bodur Yasemin V. , Amargant-Arumí Martí , Müller Oliver , Hawkes Jeffrey A. , Kohler Stephen G. , Dietrich Ulrike , Reigstad Marit , Paulsen Maria L.
Published: January 2025

Abstract. Particulate (POM) and dissolved (DOM) organic matter in the ocean are important components of the Earth's biogeochemical cycle. The two are in a constant state of dynamic change as a result of physical and biochemical processes; however, they are mostly treated as two distinct entities, separated operationally by a filter. We studied the seasonal transition of DOM and POM pools and their drivers in a sub-Arctic fjord by means of monthly environmental sampling and by performing experiments at selected time points. For the experiments, surface water (5 m) was either pre-filtered through a GF/F filter (0.7 µm) or left unfiltered, followed by 36 h incubations. Before and after incubation, samples were collected for dissolved and particulate organic carbon concentrations (DOC, POC), extracellular polymeric substances (EPSs), microbial community (flow cytometry), and molecular composition of DOM (high-performance liquid chromatography coupled to high-resolution mass spectrometry – HPLC-HRMS). During the biologically productive period, when environmental POC concentrations were high (April, June, September), the filtered water showed an increase in POC concentrations. While POC concentrations increased in September, DOM lability decreased based on changes in the average hydrogen saturation and aromaticity of DOM molecules. In contrast, during the winter period (December and February), when environmental POC concentrations were low, lower concentrations of POC were measured at the end of the experiments compared to at the start. The change in POC concentrations was significantly different between the biologically productive period and the winter period (t test; p<0.05). Simultaneously, the DOM pool became more labile during the incubation period, as indicated by changes in the average hydrogen saturation, aromaticity, and oxygen saturation, with implications for carbon cycling. The change in POC was not directly associated with an antagonistic change in DOC concentrations, highlighting the complexity of organic matter transformations, making the dynamics between POC and DOC difficult to quantify. However, in both periods, bacterial activity and EPS concentrations increased throughout the incubations, showing that bacterial degradation and physical DOM aggregation drive the transformations of POM and DOM in concert but at varying degrees under different environmental conditions.
Spatial and temporal variability in sea surface temperatures and monsoon dynamics in the northwestern Arabian Sea during the last 43 kyr
Authors: Maier Jan , Burdanowitz Nicole , Schmiedl Gerhard , Gaye Birgit
Published: January 2025

Abstract. In this study, we present the first well-dated, high-resolution alkenone-based sea surface temperature (SST) record from the northeastern Oman margin (Gulf of Oman) in the northwestern Arabian Sea. The SST reconstructions from core SL167 span the last 43 kyr and reveal temperature fluctuations of around 7 °C (ranging from 20.1 to 27.4 °C). Thus, this region has a higher sensitivity to climate variations compared to other core locations in the Arabian Sea and fills a gap in a previously unstudied region. SSTs were lowest during Heinrich event 4 (H4) and were comparatively low during H3, H2, the Younger Dryas, and the early and late Holocene. Comparatively higher SST occurred during some Dansgaard–Oeschger interstadials (D–O 11 and D–O 4–9), the Bølling–Allerød (B–A), and the mid-Holocene. The SST was predominantly influenced by the SW monsoon during warmer periods and the NE monsoon during cold intervals. Importantly, the Last Glacial Maximum stands out owing to the absence of intense cooling at the core site which clearly diverges from previously known SST patterns. We speculate that this pattern was caused by stronger NW winds and an eastward shift in the SST gradient in the Gulf of Oman, resulting in a brief and moderate cooling period. Strong SW winds during the early Holocene transported cold-water masses from the Oman upwelling into the Gulf of Oman, lowering SSTs. A rapid temperature increase of approx. 2 °C during the mid-Holocene was likely induced by the weakening of SW winds and an abrupt eastward shift in the SST gradient.
Ice-proximal sea ice reconstruction in the Powell Basin, Antarctica, since the Last Interglacial
Authors: Khoo Wee Wei , Müller Juliane , Esper Oliver , Xiao Wenshen , Stepanek Christian , Gierz Paul , Lohmann Gerrit , Geibert Walter , Hefter Jens , Mollenhauer Gesine
Published: January 2025

Abstract. In Antarctica, the presence of sea ice not only plays a critical role in the climate system but also contributes to enhancing the stability of the floating ice shelves. Hence, investigating past ice-proximal sea ice conditions, especially across glacial–interglacial cycles, can provide crucial information pertaining to sea ice variability and deepen our understanding of ocean–ice–atmosphere dynamics and feedback. In this study, we apply a multiproxy approach, in combination with numerical climate modeling, to explore glacial–interglacial environmental variability. We analyze the novel sea ice biomarker IPSO25 (a di-unsaturated highly branched isoprenoid (HBI)), open-water biomarkers (tri-unsaturated HBIs; z-/e-trienes), and the diatom assemblage and primary productivity indicators in a marine sediment core retrieved from the Powell Basin, NW Weddell Sea. These biomarkers have been established as reliable proxies for reconstructing near-coastal sea ice conditions in the Southern Ocean (SO), where the typical use of sea-ice-related diatoms can be impacted by silica dissolution. We present the first continuous sea ice records, in close proximity to the Antarctic continental margin, since the penultimate deglaciation. Our data shed new light on the (seasonal) variability in sea ice in the basin and reveal a highly dynamic glacial–interglacial sea ice setting characterized by significant shifts from perennial ice cover to seasonal sea ice cover and an open marine environment over the last 145 kyr. Our results also unveil a stronger deglacial amplitude and warming during the Last Interglacial (LIG; Marine Isotope Stage (MIS) 5e) compared to the current one (Holocene). A short-term sea ice readvance also occurred towards the end of each deglaciation. Finally, despite similar findings between the proxy and model data, notable differences persist between both interglacials – emphasizing the necessity for different Antarctic ice sheet configurations to be employed and more robust paleoclimate data to enhance climate model performance close to the Antarctic continental margin.
Place-based science from Okinawa: 18th-century climate and geology recorded in Ryukyuan classical music
Authors: Higa Justin T. , Uyeunten June Y. , Odo Kenton A.
Published: January 2025

Abstract. Indigenous knowledge can record scientific observations of specific “places” that may be difficult to preserve in the geologic record. Such place in place-based science highlights issues local to a learner for engaging audiences with the scientific problems relevant to their communities. Here, we focus on a repertoire of indigenous Ryukyuan classical music to examine place-based observations of 18th-century climate and geology in the Ryukyu Islands (21st-century Okinawa Prefecture, Japan). Comparing environmental conditions recorded in songs with 20th–21st-century studies, we find that surface winds, ocean currents, typhoons, and volcanism from lyrics parallel their respective observations in the scientific record. This novel perspective of art and science highlights the relevancy of Ryukyuan classical music in teaching contemporary issues such as climate change and natural hazards. Thus, Ryukyuan indigenous knowledge can play an innovative role in science engagement for 21st-century Okinawans in Okinawa Prefecture and their diasporic kinsfolk worldwide.
Orbital-scale variability in the contribution of foraminifera and coccolithophores to pelagic carbonate production
Authors: Cornuault Pauline , Beaufort Luc , Pälike Heiko , Bickert Torsten , Baumann Karl-Heinz , Kucera Michal
Published: January 2025

Abstract. Throughout the Cenozoic, calcareous nannoplankton and planktonic foraminifera have been the main producers of pelagic carbonate preserved on the seafloor. While past variability in pelagic carbonate production has been previously studied, relatively little is known about the variability in the relative contribution of the two components. This is important because the responses of the two groups to environmental forcing could be different such that they could amplify or reduce the magnitude of fluctuations in total carbonate production. Here we present new data from the tropical Atlantic that allow us to quantify changes in the relative contribution of the two groups to the total pelagic carbonate burial flux on orbital scales and between different climate states since the Miocene. We find that the composition of the deposited pelagic carbonate remained similar on long time scales, with foraminifera making up about 30 % of the deposited carbonate, but varied by up to a factor of two on orbital time scales. We show that the relative contribution of planktonic foraminifera and coccoliths did not correlate with the total pelagic carbonate production, neither in the Pliocene, when its dominant cyclicity was in the precession band and in phase with orbital parameters modulations, nor in the Miocene, when its predominant cyclicity was in the eccentricity band and in antiphase with orbital parameters modulations. The observed variability in tropical pelagic carbonate productivity between foraminifera and coccolithophores suggests that the two main groups of pelagic calcifiers responded fundamentally differently to orbital forcing and associated oceanographic changes in the tropical ocean, but the resulting changes in their proportions did not drive changes in overall pelagic carbonate deposition neither on geological nor on orbital time scales.
Accelerated pseudo-transient method for elastic, viscoelastic, and coupled hydromechanical problems with applications
Authors: Alkhimenkov Yury , Podladchikov Yury Y.
Published: January 2025

Abstract. The accelerated pseudo-transient (APT) method is a matrix-free approach used to solve partial differential equations (PDEs), characterized by its reliance on local operations, which makes it highly suitable for parallelization. With the advent of the memory-wall phenomenon around 2005, where memory access speed overtook floating-point operations as the bottleneck in high-performance computing, the APT method has gained prominence as a powerful tool for tackling various PDEs in geosciences. Recent advancements have demonstrated the APT method's computational efficiency, particularly when applied to quasi-static nonlinear problems using Graphical Processing Units (GPUs). This study presents a comprehensive analysis of the APT method, focusing on its application to quasi-static elastic, viscoelastic, and coupled hydromechanical problems, specifically those governed by quasi-static Biot poroelastic equations, across 1D, 2D, and 3D domains. We systematically investigate the optimal numerical parameters required to achieve rapid convergence, offering valuable insights into the method's applicability and efficiency for a range of physical models. Our findings are validated against analytical solutions, underscoring the robustness and accuracy of the APT method in both homogeneous and heterogeneous media. We explore the influence of boundary conditions, nonlinearities, and coupling on the optimal convergence parameters, highlighting the method's adaptability in addressing complex and realistic scenarios. To demonstrate the flexibility of the APT method, we apply it to the nonlinear mechanical problem of strain localization using a poro-elasto-viscoplastic rheological model, achieving extremely high resolutions – 10 0002 in 2D and 5123 in 3D – that, to our knowledge, have not been previously explored for such models. Our study contributes significantly to the field by providing a robust framework for the effective implementation of the APT method in solving challenging geophysical problems. Importantly, the results presented in this paper are fully reproducible, with MATLAB code, symbolic Maple scripts, and CUDA C codes made available in a permanent repository.
Ice speed of a Greenlandic tidewater glacier modulated by tide, melt, and rain
Authors: Sugiyama Shin , Tsutaki Shun , Sakakibara Daiki , Asaji Izumi , Kondo Ken , Wang Yefan , Podolskiy Evgeny , Jouvet Guillaume , Funk Martin
Published: January 2025

Abstract. Ice discharge from the Greenland ice sheet is controlled by tidewater glacier flow speed, which shows large variations on different timescales. Short-term speed variations are key to understanding the physical processes controlling glacial motion, but studies on Greenlandic tidewater glaciers, particularly near the calving front, are sparse. Here, we present high-frequency ice speed measurements performed at 0.5–4 km from the front of Bowdoin Glacier, a tidewater glacier in northwestern Greenland. Three global positioning system (GPS) receivers were operated for several weeks in July of 2013–2017 and 2019. Horizontal ice speed varied over timescales of hours to days, including short-term speed-up events as well as diurnal and semidiurnal variations. Frequency analysis revealed that semidiurnal signals decay upglacier, whereas diurnal signals are consistently observed over the study area. Speed-up events were associated with heavy rain, and longer-term variations were correlated with air temperature. Uplift of the glacier surface was observed during fast-flowing periods, suggesting basal separation due to elevated water pressure. These observations confirm the strong and immediate impact of meltwater and rainwater on subglacial water pressure and sliding speed. Tidally modulated ice speed peaks coincided with or slightly before low tide, which demonstrates the key role viscoelastic ice dynamics play in response to changing hydrostatic pressure acting on the glacier front. Our study results reveal details of short-term flow variations near the front of a Greenlandic tidewater glacier and provide insights into calving glacier dynamics. During the melt season, ice speed is controlled by atmospheric conditions through meltwater production and rain events, as is commonly observed in alpine glaciers, but additional complexity arises from tidal influence near the calving front.
Watershed Development Programme: A solution to ensure food, energy and climate security of the Country India
Authors: Dr.C.P.Reddy
Published: January 2025

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ANALISIS MANAJEMEN DAKWAH TERAPI PSIKORELIGIUS SOSIOPATIC DI PONDOK PESANTREN ISTIGHFAR SEMARANG
Authors: Susanto Dedy
Published: January 2025

Penelitian ini membahas analisis manajemen dakwah terapi psikoreligius dalam menangani perilaku sosiopatik di Pondok Pesantren Istighfar, Semarang. Didirikan dengan tujuan membina mantan preman, pesantren ini berupaya membantu mereka meninggalkan perilaku sosiopatik melalui pendekatan psikoterapi religius. Di bawah bimbingan Gus Tanto, santri yang berasal dari kawasan rawan seperti Barutikung, Kebon Harjo, Kaligawe, Tambaklorok, dan Purwosari mendapatkan pembinaan intensif yang menekankan nilai kasih sayang, baik di lingkungan pesantren maupun masyarakat sekitar. Keunikan pesantren ini terletak pada busana serba hitam yang dikenakan para santrinya, yang sebagian besar adalah laki-laki bertubuh gempal dan bertato. Dengan pendekatan dakwah berbasis spiritual, perilaku sosiopatik seperti kriminalitas dan kecanduan narkoba berhasil dicegah dan diatasi. Manajemen dakwah yang diterapkan mencakup tahapan perencanaan (planning), pengorganisasian (organizing), pelaksanaan (actuating), dan pengendalian (controlling). Strategi ini berperan penting dalam membentuk kembali santri menjadi individu yang baik dan bermanfaat bagi masyarakat. Penelitian ini bertujuan untuk menggali lebih dalam manajemen dakwah yang diterapkan di Pondok Pesantren Istighfar dalam upayanya mencegah dan mengobati perilaku sosiopatik, sebagai bagian dari dakwah Islam yang menyasar semua lapisan masyarakat, khususnya kelompok rentan.
PERAN GURU PAI DALAM MENINGKATKAN KEMAMPUAN MEMBACA AL-QURAN MELALUI METODE IQRO
Authors: Missouri Randitha , Alamin Zumhur , Mayada Mayada , Safitriani Nurinsa
Published: January 2025

Penelitian ini bertujuan untuk mengetahui peran guru PAI dalam meningkatkan kemampuan membaca Al-Quran melalui penerapan metode Iqro di MTs. Al-Huda Kilo-Nusa Tenggara Barat. Metode kualitatif digunakan dalam penelitian ini dengan subyek penelitian yaitu siswa kelas IX MTs. Al-Huda Kilo tahun ajaran 2024/2025. Data dikumpulkan melalui teknik wawancara, observasi, dan dokumentasi. Hasil penelitian ini menunjukkan bahwa peran guru PAI dalam meningkatkan kemampuan membaca Al-Quran sangat membantu siswa. Guru berperan sebagai pembimbing utama yang tidak hanya mengajarkan cara membaca Al-Qur'an, tetapi juga membangun fondasi kecintaan terhadap kitab suci dalam diri siswa. Guru PAI memperkenalkan metode Iqro kepada siswa, yang dimulai dari pengenalan huruf-huruf hijaiyah, tanda baca, dan harakat. Namun, cara mengajar guru PAI kurang efektif dalam meningkatkan kemampuan siswa membaca Al-Quran. Hal ini dapat dilihat dari rata-rata kemampuan siswa membaca Al-Quran belum sesuai tajwid. Hal ini disebabkan karena guru hanya menggunakan metode Iqro dalam pembelajaran Al-Quran, sehingga siswa merasa bosan mengikuti kegiatan pembelajaran Al-Quran. Peneliti menyarankan agar menggunakan metode lain dalam mempelajari Al-Quran seperti metode talaqqi, musyafahah, atau menggabungkan kedua metode tersebut agar siswa lebih semangat dan antusias mempelajari Al-Qur’an.
Determination of Forest Health using Remote Sensing Techniques in Gashaka-Gumti National Park, Northeast, Nigeria
Authors: A. Dantani,
Published: January 2025

This study was conducted in order to determine the health status of forest vegetation in Gashaka-Gumti National Park. Landsat images were downloaded from the USGS website. The images were pre-processed using radiometric correction since the reflectance values were needed for computing spectral indices, the digital numbers were converted to radiance and reflectance, and analysis was carried out using a raster calculator. The range of NDVI, GNDVI, ARVI and MSI were used for health assessment. Utilizing NDVI, GNDVI, ARVI, and MSI as assessment tools revealed moderate to good health in most forest regions, with higher ARVI, GNDVI, and NDVI indicating healthier vegetation and elevated MSI values suggesting areas under moisture stress. the average values of NDVI, GNDVI, ARVI, and MSI over three decades indicate a potential decline in overall vegetation health, reduced green vegetation, changes in vegetation conditions, and a decrease in moisture stress, suggesting a potential increase in greening and photosynthetic activities in plants. These trends highlight the dynamic nature of the forest ecosystem over the studied period. Positive correlations between ARVI, GNDVI, and NDVI across years indicate a consistent vegetation pattern, while negative correlations with MSI suggest potential inverse relationships, providing valuable insights into forest health dynamics. Higher values of ARVI, GNDVI, and NDVI generally signify healthier vegetation, whereas elevated MSI values may indicate areas experiencing moisture stress, emphasizing the importance of monitoring these indices for sustainable forest management. The study recommends the sustained use of NDVI, GNDVI, ARVI, and MSI for forest health monitoring in the study area, implementing integrated pest management based on identified stress conditions, utilize spatial maps for strategic timber harvest planning, developing climate-resilient management considering moisture stress, and invest in research for enhanced assessment precision and understanding of ecosystem dynamics.
Synthesis, Characterization and Antimicrobial Studies of Transition Metal Complexes with Triazine-5-hydrazones of o-anisaldehyde
Authors: Onyedikachi Eberendu Kizito , Edozie Otuokere Ifeanyi
Published: January 2025

A series of complexes of the type [ML2Cl2], where L=6-tert-butyl-4-{[1-(2-methoxyphenyl)ethylidene]amino}-3-(methylsulfanyl)-1,2,4-triazin-5(4H)-one (TBMO) and 4-{[(E)-(2-methoxyphenyl)methylidene]amino}-3-methyl-6-phenyl-1,2,4-triazin-5(4H)-one (MMAO), M=Cu(II), Co(II), Ni(II) and Zn(II), have been synthesized and characterized on the basis of elemental analysis, thermal analysis, molar conductivity, magnetic moment, electronic, infrared, 1H-NMR spectral studies. The findings are in accordance with bidentate chelation of the ligand using nitrogen donors from rings and azomethine. These Hydrazones and their complexes have also been screened for their antibacterial (Bacillus subtilis, Bacillus stearothermophilus, Escherichia coli and Salmonella typhi) and antifungal activities (Aspergillus niger and Aspergil- lus flavus).
ПСИХОЛІНГВІСТИЧНІ МЕХАНІЗМИ МАНІПУЛЯЦІЇ У СУЧАСНОМУ ІНФОРМАЦІЙНОМУ ПРОСТОРІ: СТРАТЕГІЇ ВПЛИВУ ТА ПРОТИДІЇ
Authors: ГУДЗЕНКО О. Г. , ПАСТРИК Т. В. , ЛАЗЬКО А. М. , ГАЛЬЧУН Н. П.
Published: January 2025

Стаття присвячена аналізу психолінгвістичних механізмів маніпуляції, які активно використовуються у сучасному інформаційному просторі. Застосовано міждисциплінарний підхід, що включає когнітивно-прагматичний, контент-аналіз і порівняльний аналіз маніпулятивних стратегій у різних видах дискурсу, таких як політичний, медійний та рекламний. У роботі розглядаються ключові мовні засоби, зокрема метафори, евфемізми, директиви та емоційно забарвлена лексика, що сприяють прихованому впливу на свідомість і поведінку реципієнтів. Автори пропонують аналіз маніпулятивних стратегій, спрямованих на вплив на свідомість і поведінку в умовах інформаційного перенасичення. Дослідження показує, що маніпулятивний вплив базується на створенні когнітивних та емоційних бар’єрів, використанні стереотипів і штучної мотивації, що дозволяє маніпуляторам досягати власних цілей. Зазначається, що маніпуляція може мати як негативний, так і конструктивний характер, залежно від етичних норм і контексту застосування. Особлива увага приділяється розробці рекомендацій щодо формування медіаграмотності та критичного мислення для протидії маніпулятивним стратегіям. Робота базується на теоретичних і практичних напрацюваннях у психолінгвістиці, когнітивній науці та соціальній психології, що дозволяє комплексно дослідити механізми впливу. Знання механізмів маніпуляції сприяє кращому розумінню прихованих намірів у комунікації, а також зменшує ризики потрапляння під вплив маніпуляторів. Крім того, подальші дослідження у цій галузі можуть забезпечити інструментарій для більш ефективного аналізу інформаційного контенту та сприяти формуванню стійкості до маніпулятивних впливів.
Mathematical Modeling and Protocol Optimization in VANETs: Enhancing Reliability with Advanced Communication Technologies
Authors: Vinod Kumar
Published: January 2025

Vehicular Ad Hoc Networks (VANETs) are a specialized type of Mobile Ad Hoc Networks (MANETs) that play a crucial role in enhancing traffic safety, efficiency, and providing infotainment services to passengers. VANETs involve highly dynamic and mobile nodes (vehicles) which communicate with each other (V2V), with roadside infrastructure (V2I), and with other network entities (V2X). This paper presents a comprehensive analysis of various protocols and configurations in VANETs, focusing on key performance metrics such as latency and packet delivery ratio (PDR) under different node densities and network conditions. The study investigates the performance of the Intermittent Forwarding Protocol (IFP) with varying ????values, the Self-Distributing Beacon (SDB) protocol with different maximum waiting times (MaxWT), and the Scheduled Pseudonym Beaconing (SPB) protocol with different scheduling intervals (Ns). The analysis includes scenarios with and without mmWave technology and gain to understand the impact of high-frequency communication on network performance. Overall, the study underscores the importance of optimizing protocol parameters to enhance network performance in VANETs. IFP emerges as the most efficient protocol, demonstrating better scalability and reliability compared to SDB and SPB. The use of mmWave technology, while beneficial, requires careful tuning to avoid network congestion and maintain optimal performance.This research provides valuable insights into the design and implementation of effective communication protocols for VANETs, highlighting the critical need for adaptive and resilient protocols to handle the unique challenges posed by high mobility and dynamic network topologies. Future work should focus on further refining these protocols and exploring new technologies to enhance VANET performance and reliability, ultimately contributing to safer and more efficient transportation systems.
Optimized Deep learning for Energy Efficient Low-powered FPGAs
Authors: Abirami B
Published: January 2025

This paper comprehensively evaluates the performance of Field-Programmable Gate Arrays (FPGAs) against conventional hardware such as GPUs and CPUs in deep learning tasks. The evaluation focuses on several key metrics, including efficiency, accuracy, processing time, Mean Squared Error (MSE), precision, F1 score, hardware utilization, and resource consumption. We tested both BERT for text classification and Convolutional Neural Networks for image classification, providing insights into how these hardware platforms handle diverse deep learning workloads.Our results indicate that FPGAs, while more challenging to implement, offer significant benefits in scenarios where low latency, power efficiency, and high precision are critical. Specifically, they excel in applications requiring optimized performance per watt and fine-grained control over hardware resources. However, GPUs remain the preferred choice for general-purpose deep learning, due to their superior raw computational power, larger ecosystem, and ease of development. The findings underscore the potential of FPGAs in niche applications where energy constraints and specialized tasks take precedence, while GPUs continue to dominate in mainstream deep learning environments.
An Efficient Analytical Technique for Solving Fractional Order Biological Population Model
Authors: Hassan Kamil Jassim
Published: January 2025

This article uses the natural homotopy permutation technique to solve the fractional-order biological population model (FOBPM). The fractional derivative is defined using the Atangana-Baleanu operator (ABO). The proposed approach offers a series of solutions for FOBPM. The NHPM method is recognized as one of the best analytical procedures for solving fractional-order, nonlinear PDEs, particularly the FOBPM, since it involves fewer calculations and has a higher rate of convergence than other analytical approaches.
Seismic Protection of Multistorey Buildings Through Base Isolation Techniques
Authors: Ali Abdulraheem Abdullah Ali
Published: January 2025

This study deal with the performance of base isolation techniques in reducing the seismic response of multi-storey buildings. For symmetric and asymmetric building models by using finite element method in ETABS v21, the response of these models under seismic load using nonlinear time analysis methods was investigated. The study showed that the use of base isolation gives an increased the core fundamental time period, increasing from 0.75 seconds to 2.015 seconds for symmetric buildings, and from 0.74 seconds to 1.93 seconds for asymmetric buildings. this result helps avoid the impact of earth quake that maybe led to resonance and collapse the structures. The results  for the  displacement in isolated buildings was bigger  than that of fixed ones, so  flexibility and higher ability to reduce seismic impact. The displacement for symmetric buildings was about 50 mm in the isolated case, compared to 30 mm in the fixed case. As for drift, it increased to 0.015 in isolated buildings compared to 0.01 in fixed buildings, led to a good distribution for stresses in different storey. For Shear forces reduce  by  50% in isolated buildings, reaching about 1500 kN compared to 3000 kN in fixed buildings, and   overturning moment also decreased  to about 20,000 kNm in isolated buildings, compared to 40,000 kNm in fixed buildings, which improve  the stability of structures  and decrease  the possibility of damages. the above results proves that base isolation technics offer a good reduction in the seismic impact of structures, which increase the safety and stability of these structures under earthquake loads. The research recommends to using base isolation systems in seismic zones and provide a new design standards based on use of base isolation to have a good improve the ability of structures to resist seismic loads. In general, this study gives a strong confirmation of the fund of using base isolation systems to provide    a good resistance for the impact of seismic of multi-storey buildings, making a better in contribution for protecting lives and structures.
Mathematical Modeling and Statistical Analysis of Deep Learning Techniques for Brain Tumor Segmentation using MRI Scans
Authors: Mukesh Chand
Published: January 2025

This study presents a mathematical and statistical framework for analyzing the performance of deep learning models applied to brain tumor segmentation using MRI scans. Models such as 3D U-Net, PSPNet, DeepLabV3, and ResNet50 are evaluated using quantitative metrics, including the Dice coefficient, Hausdorff distance, sensitivity, specificity, and false positive/negative rates. The segmentation process is modeled mathematically to assess the accuracy and precision of tumor boundary delineation. Among the models, 3D U-Net demonstrates superior performance in boundary demarcation and overall segmentation accuracy, achieving the lowest Hausdorff distance and a high Dice coefficient.Computational analysis includes model parameters, training time, and GPU memory usage, emphasizing the feasibility of deploying these models in clinical settings with resource constraints. Statistical measures such as sensitivity, specificity, and false positive rates further validate the diagnostic capabilities of the models. The results reveal that the 3D U-Net model provides the best trade-off between computational efficiency and segmentation accuracy, making it a viable choice for neuro-oncology applications. The findings underscore the importance of leveraging mathematical models and statistical analyses to enhance early tumor detection, optimize treatment planning, and improve patient outcomes. This study concludes that integrating these models into clinical workflows offers significant potential to transform brain tumor diagnostics, particularly in resource-limited settings.
Mathematics Learning Evaluation Use Mobile Application: A Systematic Review
Authors: Leni Agustina Daulay
Published: January 2025

This study aims to provide a comprehensive overview of the use of mobile applications for the evaluation of mathematical learning in various educational contexts. It will also answer important questions about effective evaluation methods, effectiveness, benefits, and issues related to the use of mobile applications for mathematical learning evaluation. The study was designed as a systematic literature review. The results show that the use of mobile applications in mathematics learning evaluation has great potential to improve student engagement, improve their academic performance, and provide an interactive learning experience. Pre- and post-testing, use of usage data, opinion polls, and a combination of interviews and questionnaires are the most common methods of evaluation. The educational context and in-depth understanding of student needs greatly influence the performance of mobile applications in the evaluation of mathematical learning. Despite having significant benefits, the implementation of mobile applications also faces challenges, such as ethical issues, good application design, and the selection of applications that fit the curriculum. These findings suggest that to improve the quality and effectiveness of the use of mobile applications by students, it is necessary to develop ethical guidelines, better application design, and thorough evaluation of the compatibility of applications with curricula.
A Comparative Analysis of Machine Learning Imputation Techniques for MAR Missingness
Authors: Shweta Tiwaskar
Published: January 2025

Electronic health records (EHR) are essential for making informed patient care decisions., but missing data can hinder decision-making. This study addresses the issue of missing data, specifically under the Missing at Random (MAR) mechanism, which is common in real-world datasets. While statistical methods are traditionally used for data imputation, machine learning (ML) approaches offer greater flexibility and can capture complex relationships within the data. The paper evaluates three prominent ML-based imputation techniques—K Nearest Neighbor Imputation (KNNI), Multivariate Imputation by Chained Equations (MICE), and MissForest—focusing on their performance in handling MAR missingness in multivariate configurations. The study simulates MAR missingness (5%-30% of the dataset) across multiple variables and imputes the missing values using these methods. The imputed datasets are evaluated against a complete subset of the original data using several performance metrics e.g. (accuracy, F1 score, MAE, RMSE, R-squared, Pearson correlation, and BIC etc.). particularly examining correlations between missing and observed values. To calculate these performance metrics, eighteen imputed datasets are compared with one complete subset of original dataset. As compared to KNNI and MICE, MissForest imputation method demonstrated reduced SD, MAE, and RMSE in 83.33% of MR cases, and higher R-squared values in all (100%) MR cases. MissForest performs better in 100% of MR cases in all the five performance metrics of model performance. This suggests that MissForest is a superior imputation method for handling MAR missingness in multivariate settings.
A Note on Linear Operator Defined by Lambda Function for Certain Subclass of Uniformly Convex Functions
Authors: G. Swapna
Published: January 2025

In this manuscript, we initiate a novel  Categories of consistently curved functions with unconstructive coefficients defined by lambda operator. We obtain the coefficient limits, tremendous points and  radii of Celestial resemblance as well as roundness for functions belonging to the class. Moreover, incomplete sums  of functions in the class are careful with pointed lower bounds for the ratios of real part of to  and  are determined and also discussed neighbourhood results for this group.
An Analytical Exploration of Mathematical Stress and Anxiety Among Engineering Students: Challenges and Insights
Authors: Sankari Kodukula
Published: January 2025

This paper aims to investigate the effects of maths stress and anxiety on engineering students, with special regard to their results and psychological state. Due to the competitive academic environment of engineering and the critical role mathematics has, this study is to explore the correlation of mathematical stress and anxiety, and a variety of demographic variables such as gender, place of living, birth order, intermediate group, and residential status. The research design adopted in the study incorporated both quantitative and qualitative research methods in order to collect a myriad of information. The target population was engineering students; 300 participants were included in the sample, and data were collected from a self-administered questionnaire on the mathematical stress and anxiety of students. To analyze the data collected the following statistical analysis techniques were employed: descriptive statistics, correlation analysis and regression analysis. The results presented also suggest that there is no straightforward association between mathematical stress and anxiety and: demographic variables, although some of these relationships bear a mild relationship. In the regression analysis it was established that both mathematical stress and anxiety affect the academic performance, but this relationship is complex and depends on various factors. The authors note that mathematical anxiety does not have a one-size-fits-all solution; the study’s results indicate that it should be treated individually. This calls for several techniques to be formulated and implemented in colleges to address the problems and various student’s background are considered. Therefore, this study seeks to support the existing initiatives by examining the complex antecedents of students and hence boost academic performance and well-being. Future studies should build on these relations and identify more variables to enhance support initiatives and methods.
Active Filter Based Harmonics Mitigation in Grid-Connected PV Systems
Authors: Vijaykumar S. Kamble
Published: January 2025

One essential component of human advancement is energy. Fossil fuels have been the primary energy source for many centuries, but as businesses and society grow, so does the demand for energy resources. However, fossil fuels produce emissions of greenhouse gases that cause climate change in addition to being depletable. Therefore, humanity must hasten the shift to a low-carbon economy due to the predictable rise in energy consumption and the depletion of fossil fuels, which necessitates the search for clean and renewable alternative energies. These consist of solar, geothermal, biomass, wind, and hydropower. Our planet's cleanest and most plentiful energy source is solar energy, which is also limitless.
Solar energy, with its immense potential, is now a major subject of intense research and swift advancement, particularly in recent years. Rooftop photovoltaic (PV) systems are arising as a popular replacement for electricity generation. Installing and connecting PV systems to the electrical grid is now simpler thanks to advancements in power electronic devices.  Nonetheless, ensuring power quality is essential when integrating PV systems with the power grid. Among power quality issues, harmonics pose a substantial difficulty because of the reliance on various power electronic components in PV systems.
This paper focuses on designing and evaluating the performance of a rooftop solar system connected to power grid in a solar-rich location, using simulation tools to address harmonic mitigation. By successfully reducing harmonics in the grid-connected PV system, it seeks to improve power quality.