bluuebunny/crossref_metadata_2025 huggingface dataset:
Accelerated Extraction of Parasitic Capacitance in Metal Interconnects using Floating Random Walk Method
Authors: Zhao Dongyan , Chen Yanning , Liu Fang , Zhao Yang , Shao Yali , Zhang Dong , Pan Yucheng , Meng Xiangyu
Published: February 2025

This paper presents a novel and efficient approach for the rapid extraction of parasitic capacitance in metal interconnects of large-scale integrated circuit (IC) layouts. By conducting detailed electromagnetic field simulations, we propose a streamlined method that significantly reduces both computational complexity and runtime, making the extraction process more efficient. At the heart of this approach is the use of the floating random walk (FRW) algorithm, which precisely estimates both self-capacitance and mutual capacitance of conductors. A distinguishing feature of this method is the incorporation of error thresholds, which provide a dynamic mechanism to adjust the trade-off between extraction speed and accuracy. This flexibility allows the method to adapt to varying layout complexities while maintaining a high level of precision. Experimental results reveal that, compared to traditional electromagnetic simulation tools such as ANSYS Maxwell, the proposed method achieves up to 120 times faster capacitance extraction, with accuracy deviations containedwithin 20%.
Butler Matrix Components Based on Substrate Integrated Waveguide Fed by Microstrip Separation Feedline for 5G Application
Authors: Hussein Yaqdhan Mahmood , Murad Noor Asniza , Rahim Mohamad Kamal A. , Hanoosh Hatem Oday
Published: February 2025

This paper presents a beamforming component based on vias variation substrate integrated waveguide (SIW) method at Ka-band. At Ka-band, the losses are high when planar structures are implemented due to the small wavelength, beside the expected losses from the component’s losses. Therefore, SIW technology with vias manipulation is introduced. This work aims to present a low loss coupler, crossover, and phase shifter for beamforming based on SIW at 26 GHz. Coupler and crossover are designed with vias variation based on the metallic fill inside the vias microstrip separation feedline, used for input and output ports to achieve enough distance between each adjacent port, and compact design with loss phase error. The proposed designs are simulated using CST software and fabricated using Rogers 5880 substrate with thickness of 0.508 mm and permittivity of 2.2. The measured performance agreed well with the simulated results. A return loss of less than −20 dB is achieved over a bandwidth of 5 GHz. A perfect −3 dB and 0 dB are obtained at coupler and crossover outputs. The measured phase difference −88.8∘ is observed at the outputs. Overall, the coupler and crossover show great potential performance for Ka-band applications.
An All-metal Antipodal Vivaldi Antenna Design for High-power Microwave Application
Authors: Chen Zichong , Yin Rui , Jiang Yun , Mao Xiaojun , Lv Pengjie , Jiang Shangyi , Liu Yang
Published: February 2025

In this paper, the evolutionary process, fabrication and measurement of an all-metal antipodal Vivaldi antenna (AMAVA) design are presented for the high-power microwave (HPM) application. Derived from the substrate-loaded antipodal Vivaldi antenna, the proposed antenna is made all metallic to enhance its power handling capacity (PHC). Considering the further improvement of the radiation performance and antenna fixing, rectangular slots and tuning stubs with exponential corner cuts are employed in antenna design. In the air condition, the PHC values of the final proposed antenna are over 8000 W in its operating band. The proposed AMAVA is fabricated and measured in a microwave anechoic chamber. According to the measured results, the −10 dB impedance bandwidth covers 8.3-10.66 GHz, and its deepest resonance reaches −29.7 dB at 9.75 GHz. The measured radiation pattern values are in agreement with simulation values, and its peak gain values at 9.3 GHz, 9.8 GHz and 10.3 GHz are 4.54 dBi, 5.68 dBi and 5.71 dBi, respectively. A PHC experiment is conducted, which verifies the AMAVA is qualified for 8000 W-level PHC.
Investigating Role of Artificial Intelligence for Preparing Question Paper Till Evaluation Process in Open Book Examination System
Authors: Dimari Amit , Tyagi Nidhi , Srinivasan S. , Davanageri Mahesh , Lama Prabha , Dimari Hema
Published: February 2025

In the rapidly evolving landscape of higher education, the integration of AI in various assessment techniques presents before us a revolutionary potential for grading systems. This research study aimed to investigate the role of Artificial Intelligence (AI) in open-book examinations, with a focus on question paper preparation and evaluation processes. The research employed a Quantitative approach, including surveys and data analysis techniques. The sample size of 165 participants was taken as a sample in the study which includes students, educators and administrators from various academic institutions who have implemented open book examination systems. Participants were chosen on the basis of purposive sampling technique that have vast experience in AI technologies and open book system as well. The findings revealed significant differences and associations between AI integration and traditional methods in open-book examinations. Challenges identified in traditional methods included time constraints and subjectivity in evaluation. The t-test analysis showed significant differences in the feasibility and effectiveness of open-book examinations between AI-integrated and traditional methods. There was a significant association between traditional question paper preparation and evaluation methods and the identified challenges. Additionally, a significant difference was found in the benefits and advantages of using AI technologies in question paper preparation for open book exams. The authors arrived at the resolution that further examination and educator preparation are expected to completely get a handle on the capability of artificial intelligence in instructive assessment, especially schooling level lower than advanced education.
Transforming Pakistan’s Blue Economy
Authors: Akhtar Muhammad Jawad
Published: February 2025

Pakistan’s maritime sector has long been neglected despite holding immense potential for economic development and regional connectivity. However, operational, governance, and environmental challenges hindered exploiting its untapped potential. Recognizing the need to overhaul the sector, in light of the 2025 National Maritime Policy (NMP) policy draft, the Prime Minister of Pakistan approved certain directives. These reforms seek to align the maritime sector with the principles of the blue economy. This paper evaluates the proposed directives and the implementation challenges of governance, operational efficiency, and sustainability concerns. By analyzing these structural and operational reforms, the paper proposes actionable recommendations and a strategic approach to unlock Pakistan’s maritime potential and elevate its position as a competitive player in the regional and global maritime landscape.
‘The feeling that I’m unimportant’: epistemic injustice lens on formal support for women with disabilities survivors of intimate partner violence
Authors: Anyango Cartrine , Goicolea Isabel , Lövgren Veronica , Namatovu Fredinah
Published: February 2025

Intimate partner violence is a pervasive injustice that affects one in three women globally. Women experiencing intimate partner violence require immediate, compassionate and non-judgemental support, not only to prevent negative outcomes and aid in recovery but also to encourage functionality and resilience. However, maintaining equitable relationships during the support-seeking process poses challenges. Formal support can either validate or contribute to re-victimisation, thereby influencing the rectification or reinforcement of injustices. This article explores the experiences of women with disabilities seeking formal support relating to intimate partner violence, utilising an epistemic injustice lens. The focus is on formal support in Sweden, delivered by professionals in healthcare, social services, the police, women’s shelters, and the Centre against Violence (centrum mot våld). Employing reflexive thematic analysis guided by epistemic injustice as a theoretical framework, the results reveal instances of epistemic injustice. Participants expressed feelings of marginalisation, unheard voices, mistrust and misunderstanding within a formal support system they described as unintelligible and fragmented. Continuous scrutiny of the support-seeking process, coupled with improvements in the capacity of support providers and a re-evaluation of guidelines and procedures, becomes essential to promote inclusivity for women with disabilities, thereby contributing to the achieving of epistemic justice.
Queer Taiwan and the construction of a Taiwanese queer identity
Authors: Zheng Yayu
Published: February 2025

This article examines Queer Taiwan, a docu-series focusing on LGBTQ topics in Taiwan. Among the very first original content commissioned by GagaOOLala, Asia’s first LGBTQ streaming platform, Queer Taiwan is imbued with messages of social import while tracing the history and recording the current fight for LGBTQ rights. By adopting a participatory approach, Queer Taiwan sparked conversation on hotly debated topics among different social groups with the goal of enhancing mutual understanding and shedding light on common misconceptions. This article explores how these conversations reflect the changing social outlook and public attitudes during Taiwan’s journey towards marriage equality. It includes a discussion of the socialization and politicization of sexual identity by situating it within the history of Taiwan’s national identity politics, a pervasive theme of the island’s queer literature and cinema. The analysis encompasses queer cinema, documentaries in particular, illustrating how non-fiction film envisions the parallels between campaigns to assert queer pride and Taiwanese distinctiveness. This study illuminates the relationship between queer cinema and the wider sociopolitical landscape in the run-up to Taiwan’s legalization of same-sex marriage.
Molecular Docking, Computational DFT, Biological Activity, Phytochemical Analysis and Spectrum Analysis Investigations of Neoandrographolide
Authors: Kamalarajan P. , Ahamed J. Irshad , Ramesh S. , Valan M.F.
Published: February 2025

In this work, neoandrographolide (C26H40O8) was isolated first time from the ethanolic extract of Nilavembu Kudineer Chooranam (NKC), traditional Siddha medicine powder. Thin-layer chromatographic (TLC), GC-MS and mass spectrometry techniques were employed to extract after the preliminary phytochemical screening. Neoandrographolide has a significant level of α-amylase inhibition activity. The ab initio DFT theory of DFT-B3LYP/6-311++ G(d,p) basis set technique was used for theoretical studies and comparison with the three experimental spectral studies such as 1H, 13C NMR, FTIR and UV-visible methods. When compared to the theoretical computational density functional theory (DFT) using Gaussian 9.0, the results have shown that the investigated compounds are potential therapeutic leads for in vitro biological and in silico molecular docking utilizing auto dock vina 4.2. Based on the results, it is confirmed that compound neoandrographolide would be most effective against α-amylase inhibitor activities.
Design, Synthesis, Molecular Docking and Antimicrobial Activity of New Thiazole-Fused Pyrimidine Derivatives
Authors: Azamat K.M. , Chauhan Bhupendra , Naseer MD Arif , Kumar Naveen , Ali Zulphikar
Published: February 2025

A new class of compounds formed by the linkage of –N=C– (Schiff base) with pyrimidine fused thiazole moieties was designed and synthesized. All the synthesized novel 15 compounds were characterized by spectral analysis and screened for their antimicrobial activity. To gain a prior evidence for obtaining a good antimicrobial property a molecular docking study was carried out on the 3D structure of enzyme using Maestro 16.0 program (Schrödinger Inc., USA). Molecular docking studies demonstrated a better docking score and interacted well with the target protein. Antimicrobial results revealed that compounds 4d, 4i and 4k showed the overall good result against tested microbes. Physico-chemical parameters of the designed compounds were predicted in silico using the QikProp module of Schrödinger. Compound 4i exhibited the best ADME features and highest binding affinity. The in silico molecular docking study revealed their FabH inhibitory action. According to the in silico findings, all the 15 newly framed derivatives would be regarded as leads for the discovery of novel antimicrobial agent. Compound 4d emerged as a significant bioactive molecule among all the docked analogues.
Design, Synthesis and Anticancer Activity of Benzothiazole Hybrids: Insights from Molecular Docking Studies
Authors: Kotte Raju , Vedula Girija Sastry
Published: February 2025

A series of benzothiazole hybrids 5a-n bearing acetamide and benzamide functionalities were synthesized and evaluated for their anticancer activity and binding affinity with epidermal growth factor receptor (EGFR) targets, 4WKQ and 6LUD. The synthesis involved the synthesis of 6-hydroxy-2-aminobenzothiazole, followed by methylation and coupling with carboxylic acids to yield benzothiazole hybrid compounds. The structures of the synthesized compounds were confirmed using analytical techniques such as 1H NMR, 13C NMR and HRMS techniques. Molecular docking studies indicated that the hydroxyl (-OH) and amino (-NH2) groups significantly enhanced binding to both EGFR targets, with compounds 5j (3-OH) and 5i (4-OH) showing the highest binding affinities. The anticancer activity of these hybrids was tested against MCF-7 breast cancer, HCT-116 colon cancer and HEK-293 normal cells using MTT assays. The compounds exhibited promising cytotoxicity, with meta-substituted derivatives showing superior activity. Among them, compounds 5f, 5h, 5i, 5j and 5m demonstrated a significant potency, suggesting their potential as candidates for further development in cancer research.
Luminescent Red Emitting Magnetic Fe3O4@GdVO4:Eu3+ Nanocomposite: Heat Ability in AC Magnetic Field and Cell Viability in HCT116 Cell Lines
Authors: Khundrakpam Nehru S. , Khundongbam Biken S. , Oinam Ibopishak S. , Asem Bimola D. , Devi Soibam Thoithoisana
Published: February 2025

Red-emitting magnetic Fe3O4@GdVO4:Eu3+ nanocomposite was synthesized to study its heat generation ability under the influence of alternating magnetic fields. The crystalline structure of the Fe3O4 and Fe3O4@GdVO4:Eu3+ nanocomposite were confirmed and determined by X-ray diffraction (XRD) measurement. Fourier transformation infrared (FTIR) spectroscopy confirmed the presence of polyethylene glycol, from the solvent, adhered to the surface of the nanoparticles. From the TEM images, it is suggested that Fe3O4@GdVO4:Eu3+ sample contains spherical (< 10 nm) and cubic (~100 nm) shaped particles. Vibrating sample magnetometry (VSM) analysis revealed the superparamagnetic nature of the sample with sufficient saturation magnetization (Ms) values and low coercivity (Hc) values. The samples were subjected to an alternating magnetic field showing efficient heat generation by the nanoparticles and the nanocomposites viz. 3.05 × 106 and 4.58 × 106 kAm–1 s–1. The Fe3O4@GdVO4:Eu3+ nanocomposite also showed strong red emission under excitation at 300 nm. The prepared nanocomposite was found to have high viability in HCT116 colon cancer cell lines. Therefore, Fe3O4@GdVO4:Eu3+ magnetic luminescent nanocomposite may be useful for optical imaging and hyperthermia applications.
Synthesis and Biological Evaluation of New Chalcone based Thiazole Derivatives: Antimicrobial, Antifungal Activity, ADME and Molecular Docking Studies
Authors: Geetha D. , Basavaraju Y.B. , Roopa K.
Published: February 2025

The Claisen-Schmidt condensation reaction of 2-acetyl thiophene with heterocyclic carboxaldehyde or substituted benzaldehyde in the presence of alkaline medium was used to synthesize novel thiophene chalcones. Several chalcone heterocycle hybrids appear to have more activity than the standards. These chalcones can be hydroaminated to provide good yields of amino thiazole derivatives. The newly synthesized compounds were characterized with spectroscopic techniques including FT-IR, 1H NMR, 13C NMR and HRMS. In addition to a seed germination inhibition test and an evaluation of the synthesized compounds in vitro antibacterial activity against a variety of bacteria and fungi, the synthesized aminothiazole derivatives underwent molecular docking and in silico ADMET studies.
Synthesis, Moleculoar Docking and Antidiabetic Studies of Some 3,5-Disubstituted Thiazolidinediones
Authors: Madhuri P. Laxmi , Rajitha G.
Published: February 2025

Novel thiazolidinedione derivatives incorporating a naphthylidene moiety were synthesized through Knoevenagel condensation reaction. The structural confirmation of the synthesized compounds was achieved through IR, mass and NMR spectral analyses. These compounds were assessed for their antidiabetic effects in alloxan-induced diabetic rats and in vivo antidiabetic analysis indicated that the compounds IIg and IIh exhibited significant antidiabetic activity. Molecular docking studies on the PPARγ receptor were performed to gain insights into the binding interactions of these designed compounds. The molecular docking studies identified compounds IIg and IIh as particularly effective against the PPARγ receptor. ADME properties were predicted using the QikProp module from the Schrödinger suite and all compounds complied with Lipinski’s rule of five, suggesting good oral absorption. Thus, compounds IIg and IIh may further be considered as potential antidiabetic agents.
Design and Synthesis of Quaternized Antimicrobial Polymer against Escherichia coli
Authors: Nagaraja Akshatha , Kanth Shreya , Jalageri Manohara Dhulappa
Published: February 2025

New strategies and approaches are required due to the rising levels of antibiotic resistance, which are frequently brought on by long-term misuse or overuse of conventional antimicrobial medications. Due to their minimal potential to produce drug-resistant bacteria, effective antimicrobial polymers have been garnering more attention. The incorporation of quaternary ammonium groups into polymers is among the most beneficial methods for fabricating biomaterials with antimicrobial properties. This study presents the synthesis pathway on developing quaternized jeffamine polymer (QJP) with efficient antimicrobial property. The QJP was prepared by post polymerization modification of Jeffamine ED2003 and the structural integrity of the QJP was investigated by NMR and thermal properties. The synthesized QJP exhibited activity against E. coli and kill time assay revealed the synthesized polymer has a bacteriostatic effect.
Effective, Reusable Applications of Nanostructured Silver-MnO2 for Dye Degradation under UV Light and Dye-Sensitized Solar Cells
Authors: Chinnadhurai S. , Doss M. Arockia , Kamalakkannan J.
Published: February 2025

Silver-MnO2, a metal-doped semiconductor oxide, was synthesized using a simple precipitation technique and characterized with XRD, FESEM, HR-SEM, TEM, EDS, UV-Vis DRS and PL spectroscopy. The XRD and EDS results confirmed that MnO2 and metallic silver (Ag) are present in the catalyst, whereas FESEM images revealed a blend of nanoparticles with many cavities and hexagonal nanosheets. The HR-SEM and TEM analyses indicated that MnO2 particles have a pentagonal or hexagonal shape with silver clusters on their smooth surfaces. Interestingly, Ag-MnO2 absorbed more light in both the UV and visible areas compared to pure MnO2. The photocatalytic performance of Ag-MnO2 was evaluated by breaking down Evans blue (EB) dye under UV light, it clearly outperformed single-component MnO2 and two-component systems. The enhanced performance is attributed due to the effects of silver doping, which appear to facilitate improved charge separation and transfer within the catalyst. Additionally, Ag-MnO2 demonstrated a high degree of stability and can be reused easily. Over the course of four cycles, the catalytic capacity with a minimal reduction is sustained. Moreover, this material was more hydrophobic than MnO2, which could help with self-cleaning uses.
Evaluating Water Quality of Village Ponds using Water Quality Index and Multivariate Statistical Techniques: A Case Study of Rohtak Block, Haryana, India
Authors: Khatri Amita , Panghal Vishal , Singh Asha , Sharma Shruti , Bhateria Rachna , Kumar Rohit , Arya Sunder Singh , Kumar Sunil
Published: February 2025

Pond water pollution has become a menace caused by various anthropogenic factors such as agricultural runoff, industrial waste and domestic wastewater. This study aims to assess the water quality and pollution levels in rural village ponds of Rohtak block, Haryana state, India. To assess the water quality, a total of 34 samples from 22 villages and one from the Tilyar city lake were collected. Various physico-chemical parameters were determined using standard methods. Total dissolved solids (TDS) were varied from 105 to 4254 mg/L, maximum was recored at S5 site (Shimli village). The 30% water samples for TDS, 62% for total hardness (TH) and 56% for Mg2+ surpass the prescribed limits of the Bureau of Indian Standards (BIS). The dissolved oxygen (DO) and biological oxygen demand (BOD) were ranged from 1.0 to 4.5 mg/L and 1.6 to 34.4 mg/L respectively, maximum recorded at S1 site (Sunderpur village). The 90% of the samples have very low DO (> 4 mg/L) and have higher BOD (< 2 mg/L) indicating a high organic load in the ponds. The water quality index (WQI) shows that 82% of samples were not fit for human consumption. Multivariate statistical technique, principal component analysis (PCA) reported that the first four principal components (PCs) accounted for 77.46% of the variance in water samples. Hierarchical cluster analysis (HCA) formed up four different clusters. It can be concluded that the pond water quality of the block has deteriorated and domestic wastewater treatment needs to be done by district administration.
Potential of Novel Synthesized Neem Gum and Gelatin Biocomposites based Topical Gel in Effective Wound Healing
Authors: Arora Sonia , Kaur Malkiet , Grewal Amarjot Kaur , Chauhan Samrat , Kaur Mandheer , Nagpal Manju
Published: February 2025

Wound healing and tissue repair is a complex cascade evolving due to anthropogenic and lifestyle factors. For this purpose, a well-orchestrated wound dressing can help to cover the wound or injury, which protect from surrounding environment and also provide moisture for tissue regeneration. Antimicrobial resistance is one of the major factors in increasing mortality due to wounds. Wound infection is the cause of more than 75% death in post operative infections. The biocomposites of neem gum and gelatin were prepared using crosslinking via pH change method and characterized with Fourier transmission infrared (FTIR), scanning electron microscopy (SEM) and X-ray diffraction (XRD) techniques. The optimized biocomposite formulation was used to formulate solid dispersions of pure drug clindamycin phosphate. The characterization studies confirmed the absence of drug-biocomposite interactions. The in vitro dissolution studies were carried out to evaluate the effect of amount on biocomposites polymer on the release of clindamycin from the dispersions. The optimized dispersion was incorporated into topical gel and the gel formulation exhibited sustained relese of drug for 24 h. The formulated biocomposites functioned as sustained release polymers and were employed to prolong medication release in wound healing applications.
Synthesis, in silico ADME, Molecular Docking and in vitro Cytotoxicity Evaluation of Indolin-2-one linked Stilbene Derivatives
Authors: Pirgal Dimple , Karki Subhas S. , Kumar Sujeet , Metikurki Basavraj
Published: February 2025

Considering the potential of stilbene derivatives as biologically active frameworks in cancer research, the synthesis of several indole-2-one linked stilbenes was proposed as evaluate their cytotoxic effects on cancer cells. To develop some indole-2-one linked stilbene analogs as lead molecule against cancer, novel indole-2-one linked derivatives (BK 1-11) were synthesized by reacting 4-formyl-trans-stilbene with 2-oxindole in methanol. The structural characterizations were performed by FTIR, NMR and mass techniques. Molecular docking was performed on the Janus kinase 2 (JAK2) receptor (Pdb ID: 4Z32), with binding energies expressed in kcal/mol. All the synthesized compounds were screened for their cytotoxicity against MCF, HCT116 and HeLa cells taking 5-fluorouracil (5-FU) and resveratrol as reference. Among tested derivatives, compound BK-6 was found to be most potent against all the three cell lines with IC50 of 48-64 µM and 49.92% cell viability after 72 h of treatment. A low to moderate aqueous solubility was predicted by Swiss-ADME web-tool. The docking score and cytotoxicity data suggest compound BK-6 as a potential molecule against MCF cancer cells. However, further biological studies require to support the cytotoxicity and in silico results.
Retraction Notices Issued Over 20 Years Against India-Affiliated Ophthalmology Research Papers
Authors: Das Natasha , Das Saurendra
Published: February 2025

Objectives: This analysis of retraction notices against ophthalmology research articles by India-affiliated authors examined the frequency, reasons, initiators of retractions and its impact on scholarly integrity.

Methods: In May 2024, we searched Retraction Watch Database (RWD) for “Retraction Notices” issued between January 1, 2004 and December 31, 2023. Searches targeted health science research articles, narrowed by [Country: “India”] and [Subject: “(HSC) Medicine – Ophthalmology”]. Citation data was obtained from Google Scholar. Reasons for retraction were broadly categorized as error, misconduct, or unclear. Retraction notices were checked to identify who initiated the retraction.

Results:For the 20-year period, RWD recorded 8 540 retraction notices against health science research articles; 192/8540 (2.25%) were against ophthalmology research articles. Twenty entries were against ophthalmology research articles with at least one India-affiliated author. Two entries were erroneous and 18 were analysed. One article was retracted over 142 months after and another on the day of publication. The median time from publication to retraction for the other 16 articles was about 22.9 months. Only three articles had >five authors. Retractions were rarely author-driven (2/18). No retraction notice was recorded until 2010; most (six) were issued in 2022. Misconduct, especially, fake peer reviews and rogue editors, accounted for 15 retractions. Mean citation count was similar before and after retraction (5.61 versus 5.39).

Conclusion: Retractions of India-affiliated ophthalmology research articles were rare but primarily due to misconduct. The surge in 2022 emphasizes the need to strengthen editorial and peer review processes.
Peningkatan Pengetahuan Petugas Tracing (Tracer) dan Kinerja Program COVID-19 Kota Depok Mengenai Pelacakan Kontak (Contact Tracing) Tahun 2020
Authors: Syaputri Nadhiratul , Wahyono Tri Yunis Miko , Wahyuningsih Tri
Published: February 2025

Background: COVID-19 cases in Depok City continued to increase until November 2020, so case tracking and close contact (tracing) are needed to suppress COVID-19 cases. However, tracing officers still face obstacles in conducting case tracking and close contact (tracing). The purpose of this study is to improve the knowledge of tracing officers and see the performance of the Depok City COVID-19 program in terms of contact tracing.Methods: The design of this study was One Group Pretest-Posttest, consisting of 121 participants using virtual lecture methods and online assignments through Zoom Meeting and Google Form. The collected data were analyzed with STATA.12 (paired t test) to see the difference in the mean scores of participants between pretest and posttest. In addition, SPSS.24 (paired t test and Wilcoxon) was also used to see the achievement of the COVID-19 search program.Results: The statistical test results showed that this training increased the knowledge of COVID-19 trackers in Depok City with a p-value <0.05. The average score before the training was 69.89 and after the training increased to 84.89.Conclusion: The successful implementation of case and contact finding is strongly influenced by the community and the number of officers needed to trace COVID-19 cases, and is supported by the availability of COVID-19 test kits at the examining laboratory.
Studi Tinjauan Pustaka: Faktor Risiko Kejadian Amputasi pada Pasien Kaki Diabetes Mellitus
Authors: Amalina Nida , Djuwita Ratna , Yunir Em
Published: February 2025

Background: Diabetes mellitus increased from 6.9% in 2013 to 8.5% in 2018. This figure shows that only about 25% of people with diabetes know that they have diabetes. According to the International Working Group on the Diabetic Foot (IWGDF), 1 in 4 people with DM will develop an ulcer on their foot during their lifetime with a proportion of 19-34% of the total DM patients. Wound healing of DM ulcers often requires longer time and considerable resources and has a 40% risk of re-formation at 1 year and increases to 60% after 3 years.Methods: Articles selected based on the inclusion criteria were journals that examined the relationship between diabetic foot and amputation, either using a longitudinal design, cohort study (retrospective or prospective) or case control. The exclusion criteria were journals that were systematic literature reviews, screening, diagnosis.Results: Obesity in 2 articles mentioned that OR=1.20-3.20 had a significant association with amputation while blood glucose factor in 2 articles mentioned that OR=2.92-9.43 had a statistically significant association with amputation. It was found in these 3 articles with OR range=6.9-13.97, poorly controlled HbA1c had a statistically significant association with amputation.Conclusion: This literature review study concluded that amputation risk factors are influenced by BMI and blood sugar levels.  Patients should be educated on the importance of maintaining good blood sugar control, in addition to wearing proper footwear, avoiding repetitive mechanical trauma to the foot, and performing regular foot examinations.
An in silico molecular strategy to uncover medication against SARS CoV-2 from coastal grass Spinifex littoreus (Burm f.) Merr.
Authors: Vedhamani J , Ajithkumar I P
Published: February 2025

The coronavirus (COVID-19) caused a global public health disaster and every outbreak is believed to have a natural cure. Hence, this investigation aims to identify a suitable target to inhibit viral multiplication using Spinifex littoreus and to control the binding of human ACE2 receptors with the viral protein through molecular docking. This investigation aids in finding a SARS-CoV-2 antagonist in the coastal grass S. littoreus. Through GC-MS analysis, 22 different phytochemical compounds were screened from the methanolic and chloroform extracts of S. littoreus. Using Swiss ADME software, the drug-likeness properties of the screened compounds were examined. Of the 22 screened compounds, only seven adhere to Lipinski's rule of five. The compound 1-methylene-2b-hydroxymethyl-3,3-dimethyl-4b -(3-methylbut-2-enyl)-cyclohexane was docked against 3CLPRO and the spike (S) glycoprotein of SARS-CoV-2. The free binding energies of the target proteins are -6.12 kcal/mol and -6.0 kcal/mol, respectively. A stronger ligand -protein interaction results in lower binding energy. These findings could contribute to the development of a new medication for the treatment of SARS-CoV-2.
Efficient and Effective Algorithms for A Family of Influence Maximization Problems with A Matroid Constraint
Authors: Huang Yiqian , Zhang Shiqi , Lakshmanan Laks V. S. , Lin Wenqing , Xiao Xiaokui , Tang Bo
Published: February 2025

Influence maximization (IM) is a classic problem that aims to identify a small group of critical individuals, known as seeds, who can influence the largest number of users in a social network through word-of-mouth. This problem finds important applications including viral marketing, infection detection, and misinformation containment. The conventional IM problem is typically studied with the oversimplified goal of selecting a
single
seed set. Many real-world scenarios call for
multiple
sets of seeds, particularly on social media platforms where various viral marketing campaigns need different sets of seeds to propagate effectively. To this end, previous works have formulated various IM variants, central to which is the requirement of multiple seed sets, naturally modeled as a matroid constraint. However, the current best-known solutions for these variants either offer a weak (1/2 -
ε
)-approximation, or offer a (1 - 1/
e - ε
)-approximation algorithm that is very expensive. We propose an efficient seed selection method called AMP, an algorithm with a (1 - 1/
e
-
ε
)-approximation guarantee for this family of IM variants. To further improve efficiency, we also devise a fast implementation, called RAMP. We extensively evaluate the performance of our proposal against 6 competitors across 4 IM variants and on 7 real-world networks, demonstrating that our proposal outperforms all competitors in terms of result quality, running time, and memory usage. We have also deployed RAMP in a real industry strength application involving online gaming, where we show that our deployed solution significantly improves upon the baselines.
Color: A Framework for Applying Graph Coloring to Subgraph Cardinality Estimation
Authors: Deeds Kyle , Sabale Diandre , Kayali Moe , Suciu Dan
Published: February 2025

Graph workloads pose a particularly challenging problem for query optimizers. They typically feature large queries made up of entirely many-to-many joins with complex correlations. This puts significant stress on traditional cardinality estimation methods which generally see catastrophic errors when estimating the size of queries with only a handful of joins. To overcome this, we propose COLOR, a framework for subgraph cardinality estimation which applies insights from graph compression theory to produce a compact summary that captures the global topology of the data graph. Further, we identify several key optimizations that enable tractable estimation over this summary even for large query graphs. We then evaluate several designs within this framework and find that they improve accuracy by up to 10
3
× over all competing methods while maintaining fast inference, a small memory footprint, efficient construction, and graceful degradation under updates.
NeutronTP: Load-Balanced Distributed Full-Graph GNN Training with Tensor Parallelism
Authors: Ai Xin , Yuan Hao , Ling Zeyu , Wang Qiange , Zhang Yanfeng , Fu Zhenbo , Chen Chaoyi , Gu Yu , Yu Ge
Published: February 2025

Graph neural networks (GNNs) have emerged as a promising direction. Training large-scale graphs that relies on distributed computing power poses new challenges. Existing distributed GNN systems leverage data parallelism by partitioning the input graph and distributing it to multiple workers. However, due to the irregular nature of the graph structure, existing distributed approaches suffer from unbalanced workloads and high overhead in managing cross-worker vertex dependencies.

In this paper, we leverage tensor parallelism for distributed GNN training. GNN tensor parallelism eliminates cross-worker vertex dependencies by partitioning features instead of graph structures. Different workers are assigned training tasks on different feature slices with the same dimensional size, leading to a complete load balance. We achieve efficient GNN tensor parallelism through two critical functions. Firstly, we employ a generalized decoupled training framework to decouple NN operations from graph aggregation operations, significantly reducing the communication overhead caused by NN operations which must be computed using complete features. Secondly, we employ a memory-efficient task scheduling strategy to support the training of large graphs exceeding single GPU memory, while further improving performance by overlapping communication and computation. By integrating the above techniques, we propose a distributed GNN training system NeutronTP. Our experimental results on a 16-node Aliyun cluster demonstrate that NeutronTP achieves 1.29×-8.72× speedup over state-of-the-art GNN systems including DistDGL, NeutronStar, and Sancus.
Less is More: Efficient Time Series Dataset Condensation via Two-Fold Modal Matching
Authors: Miao Hao , Liu Ziqiao , Zhao Yan , Guo Chenjuan , Yang Bin , Zheng Kai , Jensen Christian S.
Published: February 2025

The expanding instrumentation of processes throughout society with sensors yields a proliferation of time series data that may in turn enable important applications, e.g., related to transportation infrastructures or power grids. Machine-learning based methods are increasingly being used to extract value from such data. We provide means of reducing the resulting considerable computational and data storage costs. We achieve this by providing means of condensing large time series datasets such that models trained on the condensed data achieve performance comparable to those trained on the original, large data. Specifically, we propose a time series dataset condensation framework, TimeDC, that employs two-fold modal matching, encompassing frequency matching and training trajectory matching. Thus, TimeDC performs time series feature extraction and decomposition-driven frequency matching to preserve complex temporal dependencies in the reduced time series. Further, TimeDC employs curriculum training trajectory matching to ensure effective and generalized time series dataset condensation. To avoid memory overflow and to reduce the cost of dataset condensation, the framework includes an expert buffer storing pre-computed expert trajectories. Extensive experiments on real data offer insight into the effectiveness and efficiency of the proposed solutions.
LEAP: LLM-Powered End-to-End Automatic Library for Processing Social Science Queries on Unstructured Data
Authors: Hu Chuxuan , Peters Austin , Kang Daniel
Published: February 2025

Social scientists are increasingly interested in analyzing the semantic information (e.g., emotion) of unstructured data (e.g., Tweets), where the semantic information is not natively present. Performing this analysis in a cost-efficient manner requires using machine learning (ML) models to extract the semantic information and subsequently analyze the now structured data. However, this process remains challenging for domain experts.

To demonstrate the challenges in social science analytics, we collect a dataset, QUIET-ML, of 120 real-world social science queries in natural language and their ground truth answers. Existing systems struggle with these queries since (1) they require selecting and applying ML models, and (2) more than a quarter of these queries are vague, making standard tools like natural language to SQL systems unsuited. To address these issues, we develop LEAP, an end-to-end library that answers social science queries in natural language with ML. LEAP filters vague queries to ensure that the answers are deterministic and selects from internally supported and user-defined ML functions to extend the unstructured data to structured tables with necessary annotations. LEAP further generates and executes code to respond to these natural language queries. LEAP achieves a 100% pass @ 3 and 92% pass @ 1 on QUIET-ML, with a $1.06 average end-to-end cost, of which code generation costs $0.02.
Discovering Leitmotifs in Multidimensional Time Series
Authors: Schäfer Patrick , Leser Ulf
Published: February 2025

A leitmotif is a recurring theme in literature, movies or music that carries symbolic significance for the piece it is contained in. When this piece can be represented as a multi-dimensional time series (MDTS), such as acoustic or visual observations, finding a leitmotif is equivalent to the pattern discovery problem, which is an unsupervised and complex problem in time series analytics. Compared to the univariate case, it carries additional complexity because patterns typically do not occur in all dimensions but only in a few - which are, however, unknown and must be detected by the method itself. In this paper, we present the novel, efficient and highly effective leitmotif discovery algorithm LAMA for MDTS. LAMA rests on two core principals: (a) a leitmotif manifests solely given a yet unknown number of sub-dimensions - neither too few, nor too many, and (b) the set of sub-dimensions are not independent from the best pattern found therein, necessitating both problems to be approached in a joint manner. In contrast to most previous methods, LAMA tackles both problems jointly - instead of independently selecting dimensions (or leitmotifs) and finding the best leitmotifs (or dimensions). Our experimental evaluation on a novel ground-truth annotated benchmark of 14 distinct real-life data sets shows that LAMA, when compared to four state-of-the-art baselines, shows superior performance in detecting meaningful patterns without increased computational complexity.
MILLION: A General Multi-Objective Framework with Controllable Risk for Portfolio Management
Authors: Deng Liwei , Wang Tianfu , Zhao Yan , Zheng Kai
Published: February 2025

Portfolio management is an important yet challenging task in AI for FinTech, which aims to allocate investors' budgets among different assets to balance the risk and return of an investment. In this study, we propose a general
M
ulti-object
I
ve framework with contro
LL
able r
I
sk for p
O
rtfolio ma
N
agement (
MILLION
), which consists of two main phases, i.e., return-related maximization and risk control. Specifically, in the return-related maximization phase, we introduce two auxiliary objectives, i.e., return rate prediction, and return rate ranking, combined with portfolio optimization to remit the overfitting problem and improve the generalization of the trained model to future markets. Subsequently, in the risk control phase, we propose two methods, i.e., portfolio interpolation and portfolio improvement, to achieve fine-grained risk control and fast risk adaption to a user-specified risk level. For the portfolio interpolation method, we theoretically prove that the risk can be perfectly controlled if the to-be-set risk level is in a proper interval. In addition, we also show that the return rate of the adjusted portfolio after portfolio interpolation is no less than that of the min-variance optimization, as long as the model in the reward maximization phase is effective. Furthermore, the portfolio improvement method can achieve greater return rates while keeping the same risk level compared to portfolio interpolation. Extensive experiments are conducted on three real-world datasets. The results demonstrate the effectiveness and efficiency of the proposed framework.
cedar
: Optimized and Unified Machine Learning Input Data Pipelines
Authors: Zhao Mark , Adamiak Emanuel , Kozyrakis Christos
Published: February 2025

The input data pipeline is an essential component of each machine learning (ML) training job. It is responsible for reading massive amounts of training data, processing batches of samples using complex transformations, and loading them onto training nodes at low latency and high throughput. Performant input data systems are becoming increasingly critical due to skyrocketing data volumes and training throughput demands. Unfortunately, current input data systems cannot fully leverage key performance optimizations, resulting in hugely inefficient infrastructures that require significant resources - or worse - underutilize expensive accelerators.

To address these demands, we present
cedar
, an optimized and unified programming framework for ML input data pipelines.
cedar
allows users to define a training job's data pipeline using composable operators that support arbitrary ML frameworks and libraries.
cedar
's extensible optimizer systematically combines and applies performance optimizations to the pipeline.
cedar
then orchestrates pipeline processing across configurable local and distributed compute resources to efficiently meet the training job's data throughput demands. Across eight pipelines,
cedar
improves performance by up to 1.87× to 10.65× compared to state-of-the-art input data systems.
The Development of Law and Economics Scholarship in Hong Kong
Authors: Lin Lauren Yu-Hsin , Liu Shu-Kai
Published: February 2025

Law and Economics (L&E), as an interdisciplinary approach, is prominent in Europe and the US but remains preliminary in Hong Kong (HK), with limited progress despite expanding research scope and quantity. This study examines HK law schools’ academic output, analyzing L&E scholars’ composition, research areas, methodologies, and development barriers. Most scholars employ L&E concepts as supplementary tools, while only a few core scholars systematically adopt it as a primary analytical framework. Research focuses on market-related areas such as competition law, financial law, and corporate law, with less focus on fields like private law and criminal law. Empirical methods, cost-benefit analysis, and institutional economics are commonly applied, but diversity and theoretical depth remain inadequate. Structural constraints – legal traditions, educational systems, and limited academic platforms – further impede L&E’s growth in HK. This study advocates interdisciplinary collaboration, research centers, academic support, and broader L&E application in policymaking and judicial processes in HK.
Insights into the physicochemical stability of ammonium glycyrrhizate and curcumin nanocomplexes
Authors: Wang Yonghui , Wu Jingwen , Guo Weiyun , Gao Xueli , Li Guanghui , He Shenghua , Huang Jihong , Du Zirui , Wen Sa
Published: February 2025

In this study, ammonium glycyrrhizate (AG) based curcumin (Cur) nanocomplexes (AG/Cur NCs) were prepared. Water solubility of Cur and the physical stability of AG/Cur NCs under varying conditions were investigated, and the stability and bioaccessibility of Cur during in vitro digestion were also studied. The results showed that Cur solubility and physical stability of the NCs increased significantly (p < 0.05) with the increase of AG concentration. The solubility of encapsulated Cur and the physical stability of AG/Cur NCs were affected by the changes in pH, salt concentration, and temperature, but the NCs showed good stability against various environmental conditions. After in vitro simulated digestion, the stability and bioaccessibility of the embedded Cur in the NCs were 6.54 % and 21.70 % respectively, higher than that of free Cur. The formulation of AG/Cur NCs significantly enhanced the solubility and stability of Cur, indicating substantial promising for Cur-based functional foods.