bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimisation-Enabled Transfer Learning Framework for Stock Market Prediction
Authors: Patil Pankaj Rambhau , Parasar Deepa , Charhate Shrikant
Published: January 2024

Stock market prediction is a vital task with high attention for gaining attractive profits with proper decisions to invest. Predicting the stock market is becoming a major challenge nowadays due to chaotic data, non-stationary data, and blaring data. Hence, it’s challenging for investors to invest money to make profits. Many techniques are developed to predict stock market trends, but each differs based on time and year. In this paper, hybridised optimisation algorithm, namely the proposed Gannet Ladybug Beetle Optimisation (GLBO), is used for training Transfer Learning (TL), which considers Convolutional Neural Network-enabled Long Short-Term Memory (CNN-enabled LSTM). This TL is responsible for predicting the stock market from augmented data. Here, the stock market dataset of two companies is used as input time series data. Moreover, many features are extracted from those input data and then from those features, necessary features are selected based on Motyka similarity. The bootstrap method is used in this paper for data augmentation. Also, GLBO is hybridised with Gannet Optimisation Algorithm (GOA) along Ladybug Beetle Optimisation (LBO) algorithm. Furthermore, the proposed model is verified for its performance capability based on three metrics, Mean Squared Error (MSE), Root Mean Squared Error (RMSE), as well as Mean Absolute Percentage Error (MAPE) with values of 5.8%, 24.1%, and 78.8%.
CASE REPORT: POSSIBLE EMERGING OF SALMONELLA ENTERICA SUBSP. ENTERICA SEROVAR HAVANA INFECTION IN NEWBORN KID GOATS
Authors: Chen Kuei-Miao , Wu Ming-Pin , Chiu Ting-Wei , Hung Chien-Ning , Lai Jyhmirn
Published: January 2024

Although salmonellosis has been considered an important problem in the ruminant farm from 10 weeks to 14 months old, there is no information about the disease in goats, especially in 2 to 3-day-old kids, in recent years. The goat farmers complained that the 2 to 3-day-old kids showed clinical signs of depression, weakness, lameness, and diarrhea. The kids might die within one week after the symptoms appeared. The mortality reached 60% (48/80). After many antimicrobial agents were dosed, no better outcome was expected. The farmer sent one kid to the official deputy for further investigation. By helping with bacterial and molecular biological techniques, autopsy, serotyping, and histopathological diagnosis, the kids were infected by Salmonella enterica subsp. enterica serovar Havana strain. After a farm visit, a moldy floor contaminated by 2 to 3[Formula: see text]cm thick feces was identified on the floor. After removing the mold and implementing disinfection, the outbreak was stopped. In conclusion, this report proves that salmonellosis has recently been identified in goat farms, especially in kids, within one week. Moreover, good hygiene and keeping feces out of barns are essential to preventing salmonellosis.
Constraining the exhumation history of the northwestern margin of Tibet with a comparison to the adjacent Pamir
Authors: Zhang Shijie , Najman Yani , Hu Xiumian , Carter Andrew , Mark Chris , Xue Weiwei
Published: January 2024

Regional variations in the evolution of the Tibetan Plateau have important implications for our understanding of crustal deformation processes. There have been few studies of the evolution of the NW margin of the plateau and its transition to the Pamir Mountains to the west. We focus on this region with a multi-technique detrital study of two sedimentary sections in the Tarim Basin. Our provenance data show that an appreciable component of the detrital material in the sedimentary sections was derived from the Songpan-Ganzi–Tianshuihai composite terrane, with some contribution from the Karakoram and/or West Qiangtang. Given the proximity of the West Kunlun terrane to the sedimentary sections under study, and its long history of exhumation, this terrane in all likelihood also contributed to the studied successions. Our thermochronological data record phases of exhumation in the hinterland in the Triassic, Early Cretaceous and Oligo-Miocene. Similar to the Pamir Mountains, the Triassic and Oligo-Miocene periods of exhumation are attributed to the Cimmerian and Himalayan orogenies, respectively. The Early Cretaceous signal may reflect the distal effects of the Lhasa–Qiangtang collision. Coevality with deformation in the Pamir Mountains suggests a coupled geodynamic system, with retro-arc deformation associated with Neotethyan subduction in the west and terrane accretion in the east.

Supplementary material:
Detailed analytical method, sample information, petrographic, geochronological and low-temperature thermochronological data are available at
https://doi.org/10.6084/m9.figshare.c.7040686
The Falls of the Ohio River: America's First Fossil Bed
Authors: Goldstein M. Alan , Bulinski Katherine V.
Published: January 2024

The Falls of the Ohio is a world-renowned geoheritage site of palaeontological and geological importance that also played key roles in the cultural and historical development of America. Studied by geologists for over two centuries, over 600 species of fossils are known from the site, hundreds of which were first described here. Beyond geology, the Falls of the Ohio can also be considered the origin and ending of the Lewis and Clark expedition, as well as an important location for naturalists and educators. A treasure of natural and human history and a National Natural Landmark, this spectacular 220 acre (89 ha) expanse of fossiliferous bedrock is worthy of ongoing study and protection.
Customized FPGA Implementation of Authenticated Lightweight Cipher Fountain for IoT Systems
Authors: Shi Zhengyuan , Chen Cheng , Yang Gangqiang , Zhou Hongchao , Xiong Hailiang , Wan Zhiguo
Published: January 2024

Authenticated Encryption with Associated-Data (AEAD) can ensure both confidentiality and integrity of information in encrypted communication. Distinctive variants are customized from AEAD to satisfy various requirements. In this paper, we take a 128-bit lightweight AEAD stream cipher Fountain as an example. We provide a general cryptographic solution with three Fountain variants. These three variants are for encryption, message authentication code (MAC) generation, and authenticated encryption with associated data, respectively. Besides, we propose area-saved and throughput-improved strategies for the FPGA implementation of Fountain. The conventional paralleled hardware implementation leads to much resource-consuming with higher parallel width. We propose a hybrid architecture with parallel and serial update modes simultaneously. We also analyze the trade-off between area occupation and authentication latency for those two architectures. According to our discussion, hybrid architectures can perform efficiently with higher throughput than most ciphers, including Grain-128 x32. Our Fountain keystream generator occupies 46 slices on Spartan-3 FPGAs, smaller than most ciphers with the same security level, and even smaller than the 80-bit security level cipher Trivium. In summary, the customized Fountain with optimized implementations on FPGA is suitable for various applications in the field of IoT.
Designing Difference-in-Difference Studies with Staggered Treatment Adoption: Key Concepts and Practical Guidelines
Authors: Wing Coady , Yozwiak Madeline , Hollingsworth Alex , Freedman Seth , Simon Kosali
Published: January 2024

Difference-in-difference (DID) estimators are a valuable method for identifying causal effects in the public health researcher's toolkit. A growing methods literature points out potential problems with DID estimators when treatment is staggered in adoption and varies with time. Despite this, no practical guide exists for addressing these new critiques in public health research. We illustrate these new DID concepts with step-by-step examples, code, and a checklist. We draw insights by comparing the simple 2 × 2 DID design (single treatment group, single control group, two time periods) with more complex cases: additional treated groups, additional time periods of treatment, and treatment effects possibly varying over time. We outline newly uncovered threats to causal interpretation of DID estimates and the solutions the literature has proposed, relying on a decomposition that shows how the more complex DIDs are an average of simpler 2 × 2 DID subexperiments.
A guide to establishing, implementing, and optimizing diversity, equity, inclusion, and accessibility (DEIA) committees
Authors: Bethea Maigen , Silvers Sophielle , Franklin Latisha , Robinson Renã A. S. , Brady Lillian J. , Vue Neng , Beasley Heather K. , Kirabo Annet , Wanjalla Celestine N. , Shuler Haysetta D. , Hinton Antentor , McReynolds Melanie R.
Published: January 2024

Diversity, equity, inclusion, and accessibility (DEIA) efforts are increasingly recognized as critical for the success of academic institutions. These efforts are facilitated mainly through the formation of dedicated DEIA committees. DEIA committees enhance professional development and create a more inclusive environment, which benefits all members of the institution. Although leadership and faculty membership have recognized the importance and necessity of DEIA, the roles of DEIA committees may be more ambiguous. Although leadership and faculty may seek to support DEIA at their institutions, they may not always fully understand the necessity of these committees or how to successfully create a committee, foster and promote its success, and sustain its impact. Thus, here, we offer a background rationale and guide for strategically setting up DEIA committees for success and impact within an academic institution with applicability to scientific societies.
High-throughput methods for cardiac cellular electrophysiology studies: the road to personalized medicine
Authors: Seibertz Fitzwilliam , Voigt Niels
Published: January 2024

Personalized medicine refers to the tailored application of medical treatment at an individual level, considering the specific genotype or phenotype of each patient for targeted therapy. In the context of cardiovascular diseases, implementing personalized medicine is challenging due to the high costs involved and the slow pace of identifying the pathogenicity of genetic variants, deciphering molecular mechanisms of disease, and testing treatment approaches. Scalable cellular models such as human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) serve as useful in vitro tools that reflect individual patient genetics and retain clinical phenotypes. High-throughput functional assessment of these constructs is necessary to rapidly assess cardiac pathogenicity and test new therapeutics if personalized medicine is to become a reality. High-throughput photometry recordings of single cells coupled with potentiometric probes offer cost-effective alternatives to traditional patch-clamp assessments of cardiomyocyte action potential characteristics. Importantly, automated patch-clamp (APC) is rapidly emerging in the pharmaceutical industry and academia as a powerful method to assess individual membrane-bound ionic currents and ion channel biophysics over multiple cells in parallel. Now amenable to primary cell and hiPSC-CM measurement, APC represents an exciting leap forward in the characterization of a multitude of molecular mechanisms that underlie clinical cardiac phenotypes. This review provides a summary of state-of-the-art high-throughput electrophysiological techniques to assess cardiac electrophysiology and an overview of recent works that successfully integrate these methods into basic science research that could potentially facilitate future implementation of personalized medicine at a clinical level.
An antisense oligonucleotide efficiently suppresses splicing of an alternative exon in vascular smooth muscle in vivo
Authors: Damacena de Angelis Celio , Meddeb Mariam , Chen Nelson , Fisher Steven A.
Published: January 2024

Alternative exon usage is a major driver of phenotypic diversity in all cell types including smooth muscle. However, the functional significance of most of the hundreds of thousands of alternative exons has not been defined, nor in most cases even tested. If their importance to vascular function were known these alternative exons could represent novel therapeutic targets. Here, we present injection of Vivo-morpholino splice-blocking antisense oligonucleotides as a simple, efficient, and cost-effective method for suppression of alternative exon usage in vascular smooth muscle in vivo.
Cotargeting CDK4/6 and BRD4 Promotes Senescence and Ferroptosis Sensitivity in Cancer
Authors: Zhu Xianbing , Fu Zheng , Dutchak Kendall , Arabzadeh Azadeh , Milette Simon , Steinberger Jutta , Morin Geneviève , Monast Anie , Pilon Virginie , Kong Tim , Adams Bianca N. , Prando Munhoz Erika , Hosein Hannah J.B. , Fang Tianxu , Su Jing , Xue Yibo , Rayes Roni , Sangwan Veena , Walsh Logan A. , Chen Guojun , Quail Daniela F. , Spicer Jonathan D. , Park Morag , Dankort David , Huang Sidong
Published: January 2024

Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors are approved for breast cancer treatment and show activity against other malignancies, including KRAS-mutant non–small cell lung cancer (NSCLC). However, the clinical efficacy of CDK4/6 inhibitors is limited due to frequent drug resistance and their largely cytostatic effects. Through a genome-wide cDNA screen, we identified that bromodomain-containing protein 4 (BRD4) overexpression conferred resistance to the CDK4/6 inhibitor palbociclib in KRAS-mutant NSCLC cells. Inhibition of BRD4, either by RNA interference or small-molecule inhibitors, synergized with palbociclib to induce senescence in NSCLC cells and tumors, and the combination prolonged survival in a KRAS-mutant NSCLC mouse model. Mechanistically, BRD4-inhibition enhanced cell-cycle arrest and reactive oxygen species (ROS) accumulation, both of which are necessary for senescence induction; this in turn elevated GPX4, a peroxidase that suppresses ROS-triggered ferroptosis. Consequently, GPX4 inhibitor treatment selectively induced ferroptotic cell death in the senescent cancer cells, resulting in tumor regression. Cotargeting CDK4/6 and BRD4 also promoted senescence and ferroptosis vulnerability in pancreatic and breast cancer cells. Together, these findings reveal therapeutic vulnerabilities and effective combinations to enhance the clinical utility of CDK4/6 inhibitors.

Significance:

The combination of cytostatic CDK4/6 and BRD4 inhibitors induces senescent cancer cells that are primed for activation of ferroptotic cell death by targeting GPX4, providing an effective strategy for treating cancer.
Multi-omics Analysis Reveals Immune Features Associated with Immunotherapy Benefit in Patients with Squamous Cell Lung Cancer from Phase III Lung-MAP S1400I Trial
Authors: Parra Edwin Roger , Zhang Jiexin , Duose Dzifa Yawa , Gonzalez-Kozlova Edgar , Redman Mary W. , Chen Hong , Manyam Ganiraju C. , Kumar Gayatri , Zhang Jianhua , Song Xingzhi , Lazcano Rossana , Marques-Piubelli Mario L. , Laberiano-Fernandez Caddie , Rojas Frank , Zhang Baili , Taing Len , Jhaveri Aashna , Geisberg Jacob , Altreuter Jennifer , Michor Franziska , Provencher James , Yu Joyce , Cerami Ethan , Moravec Radim , Kannan Kasthuri , Luthra Rajyalakshmi , Alatrash Gheath , Huang Hsin-Hui , Xie Hui , Patel Manishkumar , Nie Kai , Harris Jocelyn , Argueta Kimberly , Lindsay James , Biswas Roshni , Van Nostrand Stephen , Kim-Schulze Seunghee , Gray Jhanelle E. , Herbst Roy S. , Wistuba Ignacio I. , Gettinger Scott , Kelly Karen , Bazhenova Lyudmila , Gnjatic Sacha , Lee J. Jack , Zhang Jianjun , Haymaker Cara
Published: January 2024

Purpose:

Identifying molecular and immune features to guide immune checkpoint inhibitor (ICI)-based regimens remains an unmet clinical need.

Experimental Design:

Tissue and longitudinal blood specimens from phase III trial S1400I in patients with metastatic squamous non–small cell carcinoma (SqNSCLC) treated with nivolumab monotherapy (nivo) or nivolumab plus ipilimumab (nivo+ipi) were subjected to multi-omics analyses including multiplex immunofluorescence (mIF), nCounter PanCancer Immune Profiling Panel, whole-exome sequencing, and Olink.

Results:

Higher immune scores from immune gene expression profiling or immune cell infiltration by mIF were associated with response to ICIs and improved survival, except regulatory T cells, which were associated with worse overall survival (OS) for patients receiving nivo+ipi. Immune cell density and closer proximity of CD8+GZB+ T cells to malignant cells were associated with superior progression-free survival and OS. The cold immune landscape of NSCLC was associated with a higher level of chromosomal copy-number variation (CNV) burden. Patients with LRP1B-mutant tumors had a shorter survival than patients with LRP1B-wild-type tumors. Olink assays revealed soluble proteins such as LAMP3 increased in responders while IL6 and CXCL13 increased in nonresponders. Upregulation of serum CXCL13, MMP12, CSF-1, and IL8 were associated with worse survival before radiologic progression.

Conclusions:

The frequency, distribution, and clustering of immune cells relative to malignant ones can impact ICI efficacy in patients with SqNSCLC. High CNV burden may contribute to the cold immune microenvironment. Soluble inflammation/immune-related proteins in the blood have the potential to monitor therapeutic benefit from ICI treatment in patients with SqNSCLC.
FIGURE 4 from Exploring Co-occurring POLE Exonuclease and Non-exonuclease Domain Mutations and Their Impact on Tumor Mutagenicity
Authors: Shah Shreya M. , Demidova Elena V. , Ringenbach Salena , Faezov Bulat , Andrake Mark , Gandhi Arjun , Mur Pilar , Viana-Errasti Julen , Xiu Joanne , Swensen Jeffrey , Valle Laura , Dunbrack Roland L. , Hall Michael J. , Arora Sanjeevani
Published: January 2024

Comparison of mTMB and ΔΔG values in Group 2 and 3 tumors in the CLS dataset. With AF2 DNA unbound model and Rosetta ddG_monomer, we generated 25 repacked decoys for each mutation and compared the average energy score for these decoys with an average for 25 decoys of the WT protein. For mutations in the NTL, we performed calculations on both models (with and without DN). For those in the CTL, we performed calculations only on the DNA unbound model. We used a cutoff of ±1.45 kcal/mol for significant ΔΔG, corresponding to approximately 3 SDs of the differences of the mean Rosetta scores for WT and mutant structures. A, Comparison of mTMB and ΔΔG values in Group 2 and Group 3 tumors by the number of POLE variants. Data for colorectal cancer, endometrial cancer, and ovarian cancer genomic profiles were combined, and ΔΔG values were plotted against the mTMB. For Group 2 or 3 data with + 1 POLE variant plots, each filled round circle represents a single tumor genomic profile. B, Comparison of mTMB and ΔΔG values in Group 2 and Group 3 tumors by POLE ExoD driver. Data for colorectal cancer, endometrial cancer, and ovarian cancer genomic profiles were combined, and ΔΔG values were plotted against the mTMB. A and B, Group 3 tumors with multiple variants, a circle next to another circle (without any space) represents a single tumor. For clarity, ΔΔG values for ExoD drivers in Group 3 tumors are not shown (they are same as in Group 2). Color in each filled circle—green and shades of green, structure-destabilizing variants (positive ΔΔG); white, variants that are within the SDs of ±1.45 kcal/mol and are structure neutral; red and shades of red, structure-stabilizing variants (negative ΔΔG). Yellow, nonsense, or frameshift variants.
A novel approach to evaluate dynamic performance for photovoltaic system using software platform
Authors: Yu Byunggyu , Jung Youngseok
Published: January 2024

With the growing demand for renewable energy, solar photovoltaic (PV) systems have gained popularity as a reliable source of clean electricity. However, the performance of these systems can be limited by factors such as suboptimal maximum power point tracking (MPPT) algorithms. In order to improve the power generation efficiency of PV systems, it is important to evaluate the performance of dynamic MPPT algorithms that can adapt to varying operating conditions. Traditionally, such evaluations have been time consuming and expensive, often requiring extensive testing and measurement equipment. In this paper, we propose a novel approach to evaluate dynamic MPPT performance very quickly and simply using PSIM software. This approach enables accurate and efficient evaluation of MPPT performance under a wide range of operating conditions, while minimizing the cost and time involved in traditional testing methods. When applying the proposed method to a 3.7 kW inverter using the traditional perturbation and observation (P and O) method, we found that the highest average efficiency was 98.92% at an MPPT control period of 0.1s and a voltage perturbation of 1 V. This evaluation technique provides valuable insights into the design and optimization of more efficient MPPT control algorithms, leading to improved power generation efficiency and increased adoption of solar PV systems.
Experimental and simulation analysis for insulation deterioration and partial discharge currents in nanocomposites of power cables
Authors: Thabet Ahmed , Fouad Mohamed
Published: January 2024

Partial discharge (PD) has a well-established relationship with the lifespan of power cables. This paper has been treated the polyvinyl chloride (PVC) with specified nanoparticles for enhancing dielectric degradation and reducing partial discharge current to extending lifespan of power cables. It has been succeeded to creation new polyvinyl chloride nanocomposites that have been synthesized experimentally via using solution-gel (SOL-GEL) technique and have high featured electric and dielectric properties. The validation of nanoparticles penetration inside polyvinyl chloride during synthesis process have been constructed and tested via scanning electron microscope (SEM) images. The partial discharge current mechanisms in polyvinyl chloride nanocomposites have also been simulated in this work by using MATLAB® software. This paper has explored the characterization of partial discharge current for variant void patterns (air, water, rubber impurity) in polyvinyl chloride nanocomposites insulations of power cables to clarify the benefit of filling different nanoparticles (Clay, MgO, ZnO, and BaTiO3) with varied patterns inside power cables dielectrics. A comparative study has been done for different partial discharges patterns to propose characterization of partial discharges using nanoparticles of appropriate types and concentrations.
A deep dive into enhancing frequency stability in integrated photovoltaic power grids
Authors: Abderrazak Tadjeddine Ali , Arbaoui Iliace , Hichem Hamiani , Nour Mohamed , Alami Mohamed
Published: January 2024

Voltage control strategies (VCS) and frequency stability analysis (FSA) are essential for power system reliability, particularly during high-load periods. Stable voltage and frequency levels prevent malfunction, power quality deterioration, and supply interruptions. Grid operators must skillfully manage VCS and FSA control to ensure system stability. Nonlinear loads, especially under transient conditions, significantly affect voltage stability (VS), introducing harmonics, waveform distortion, and stability complexities. Accurate modeling of these nonlinear loads is vital when traditional static load models fall short. Frequency fluctuations from power generation-demand imbalances require vigilant monitoring and regulation. Effective frequency control mechanisms are indispensable for preserving desired frequencies. Using a Western Algeria case study, this paper underscores FSA's significance in integrating photovoltaic (PV) systems into power grids. It addresses challenges from frequency fluctuations due to dynamic ZIP load profiles, emphasizing the importance of FSA for reliable grid operation. The study offers insights and practical approaches to enhance VS, FSA control, and energy management (EM), improving grid reliability and ensuring uninterrupted power supply. We must look into FSA's benefits in integrating PV systems to improve performance and lower grid interruptions. This includes looking into its control mechanisms and feedback systems.
Dynamic voltage restorer performance analysis using fuzzy logic controller and battery energy storage system for voltage sagging
Authors: Siregar Yulianta , Azhari Nasution Azrial Aziz , Suan Tial Mai Kai , Mubarakah Naemah , Soeharwinto Soeharwinto
Published: January 2024

Power quality is a major issue in the power transfer process. This is caused by disturbances such as voltage sags, voltage spikes, and harmonics. Voltage sag is the most common disturbance in the electric power system. However, the dynamic voltage restorer (DVR) is the most effective device for voltage sags. This research uses the DVR to overcome voltage sags using fuzzy logic controller (FLC) and battery energy storage system (BESS) to improve the performance of the DVR. The results showed that DVR using FLC improved the quality of voltage recovery compared to BESS because FLC injected a greater voltage of 0.0991 pu than BESS.
Transient response mitigation using type-2 fuzzy controller optimized by grey wolf optimizer in converter high voltage direct current
Authors: Ginarsa I Made , Nrartha I Made Ari , Muljono Agung Budi , Zebua Osea
Published: January 2024

Long high voltage direct current (HVDC) transmission link is commonly used to transmit electrical energy via land or under-sea cable. The long HVDC avoids reactive power losses (RPL) and power stability problems (PSP). On the contrary, the RPL and PSP phenomena occur in long high voltage alternative current-link (HVAC) caused by the high reactive component in the HVAC-link. However, the HVDC produces a high and slow transient current response (TCR) on the high value of the up-ramp rate. Interval type-2 fuzzy (IT2F) control on converter-side HVDC is proposed to mitigate this TCR problem. The IT2F is optimized by grey wolf optimizer (GWO) to adjust input-output IT2F parameters optimally. The performance of IT2F-GWO is assessed by the minimum value of integral time squared error (ITSE), peak overshoot, and settling time of the TCR. The IT2FC-GWO performance is validated by the performance of IT2F control that is optimized by genetic algorithm (IT2F-GA) and proportional integral (PI) controller. Simulation results show that the IT2F-GWO performs better with small ITSE, low peak overshoot, and shorter settling times than competing controllers.
Efficient wireless power transfer for a moving electric vehicle by digital control of frequency
Authors: Yamaguchi Kazuya , Okamura Ryusei , Yian Kiat Adrian Wee , Iida Kenichi
Published: January 2024

Recently, demand for electric vehicles has been increasing as a countermeasure against global warming, but they currently face many problems compared to gasoline-powered vehicles. For example, charging takes time, and there are few places where electric vehicles can be charged. If AC power supplies that can transfer energy to electric vehicles wirelessly exist under the lanes where electric vehicles drive, the cruising range will be increased. In this study, assuming wireless power transfer to a moving electric vehicle, an experiment was conducted to light up a light-emitting diode (LED) on a moving electric model car. To improve the efficiency of transfer, the optimal frequency for the position of the electric model car was calculated, and the value was fed back to the power supply to adjust the frequency in real time.
Bibliometric analysis and survey on electronic nose used in agriculture
Authors: Farel Kiki Manhougbé Probus Aymard , Martial Ahouandjinou Sèmèvo Arnaud Roland , Assogba Kokou Marc , Sutikno Tole
Published: January 2024

Work carried out at the beginning of this century on improvements in semiconductor materials, transducers, sensors and artificial intelligence algorithms led to the rapid expansion of research topics related to the electronic nose, with diverse applications. Agriculture is a recent application field that needs a review of the usage of electronic noses in this field and the future challenges. The paper provided a bibliometric analysis and review of electronic noses used in agriculture. A search of published works on the e-nose and its applications in agriculture was carried out in the Web of Science and Scopus databases, which provide comprehensive citation data for academic disciplines worldwide. In the end, 2,953 documents were identified, and the data collected was analyzed mainly using the bibliometric toolbox, and then a deep study was carried out. The study results show that in the agricultural field, some works were achieved on different varieties of plants to detect disease or plant damage with very good results using electronic noses. However, less research was carried out to directly identify animals in crops like pests or environmental monitoring using electronic noses in agriculture. Some recommendations for future research efforts are finally provided.
Design and analysis of 7-stage MOS current mode logic power gated MOSFETs in current starved voltage-controlled oscillator for the phase locked loop application
Authors: Madheswaran Sivasakthi , Panneerselvam Radhika
Published: January 2024

This paper presents a new process, voltage and temperature (PVT) tolerant 7-stage ring type current starved voltage-controlled oscillator (CS-VCO). In this, a 7-stage ring VCO is proposed using power gated technique for phase locked loop (PLL) application. PLL plays a major role in clock and data recovery, Global Positioning System (GPS) system and satellite communications. For the high-speed application of PLL it is designed using 7-stage inverter delay cell with MOS current mode logic (MCML) technique. The circuit undergoes process, voltage and temperature variations with different parameters such as average power, oscillation frequency, phase noise, tuning range and output noise. The Monte-Carlo analysis justifies the proposed design provides better results. The circuit is simulated under 45 nm CMOS technology using cadence virtuoso. The average power consumption of the proposed circuit is 29.368 µW with the oscillation frequency of 3.06 GHz. The output noise and the phase noise of the proposed VCO are -161.55 dB and -125.92 dBc/Hz respectively. It achieves the frequency tuning range (FTR) of 95.09%. The obtained simulation results are highly robust with PVT making the circuit suitable for PLL application.
Maximum power point tracking and space vector modulation control of quasi-z-source inverter for grid-connected photovoltaic systems
Authors: Jaoide Essaid , El Aamri Faicel , Outazkrit Mbarek , Radouane Abdelhadi , Mouhsen Azeddine
Published: January 2024

The quasi-Z-source inverter (qZSI) become one of the most promising power electronic converters for photovoltaic (PV) applications, due to its capability to perform a buck-boost conversion of the input voltage in a single stage. The control strategy based maximum power point tracking (MPPT) and proportional integral (PI) controller are well known in grid-connected with traditional configuration but not in qZSI. This paper presents a control strategy for qZSI grid-connected based on the MPPT algorithm and the linear control by PI controllers. This is complemented by the capability to efficiently transfer the harvested power to the grid, ensuring a unity power factor. The proposed control strategy effectively separates the control mechanisms for the direct current (DC) and alternating current (AC) sides by utilizing the two control variables, the shoot-through duty ratio and the modulation index. An adapted space vector modulation technique is then utilized to generate the switching pulse width modulation (PWM) signals, using these two control variables as inputs. The proposed approach was tested and validated under MATLAB/Simulink and PLECS software.
Effective driver distraction warning system incorporating fast image recognition methods
Authors: Nguyen Van Binh , Trinh Phu Duy
Published: January 2024

Modern cars are equipped with advanced automatic technology featuring various safety measures for car occupants. However, the growing density of vehicles, especially in areas where infrastructure development lags, poses potential dangers, particularly accidents caused by driver subjectivity. These incidents may occur due to driver distraction or the presence of high-risk obstacles on the road. This article presents a comprehensive solution to assist drivers in mitigating these risks. Firstly, the study introduces a novel method to enhance the recognition of a driver's facial features by analyzing benchmarks and the whites of the eyes to assess the distraction level. Secondly, a domain division method is proposed to identify obstacles and lanes in front of the vehicle, enabling the assessment of the danger level. This information is promptly relayed to the driver and relevant individuals, such as the driver's manager or supervisor. An experimental device has also been developed to evaluate the effectiveness of the algorithms, solutions, and processing capabilities of the system.
A simple feed orthogonal excitation X-band dual circular polarized microstrip patch array antenna
Authors: Das Debprosad , Hossain Md. Farhad , Hossain Md. Azad
Published: January 2024

This work represents a microstrip patch array antenna which is designed and analyzed for the application of circular polarization in X band frequency range. The proposed antenna array has a very simple microstrip line feeding mechanism and each patch is energized orthogonally to acquire circular polarization without the need for any phase shifters. The array antenna has a slot line in the ground to electrically couple the signals from the microstrip feed line to feed each patch. The outcome demonstrates that the antenna is capable of radiating both left-hand circular polarization (LHCP) and right-hand circular polarization (RHCP). The designed work has a return loss of -41.88 dB, that is the antenna is perfectly matched. The outcome also demonstrates the antenna’s strong gain and directivity capabilities, which are 12.87 dBi and 13.30 dBi, respectively. The antenna resonates circularly at a frequency of 10 GHz.
On performance analysis of non-orthogonal multiple access downlink for cellular-connected unmanned aerial vehicle relaying assisted vehicle-to-everything system
Authors: Nguyen Hong-Nhu , Nguyen Nhat-Tien , Vo Gia-Thinh
Published: January 2024

This paper presents the unmanned aerial vehicle (UAV) relays’ assisted vehicle-to-everything (V2X) network to implement the internet of things (IoT) systems with improvement in the coverage area. Such a network benefits from many advantages of the non-orthogonal multiple access (NOMA) scheme. We have implemented a decode-and-forward (DF) scheme for these UAVs. Then, we characterize the channels as Nakagami-m fading to evaluate the performance of the system. We derive closed-form expressions of outage probability (OP), ergodic capacity (EC), and throughput. The results show that the performance of the system depends on the transmitted signal-to-noise ratio (SNR) at the base station and the heights of the UAV relays. Target rate and power allocation factors are two main parameters that can be adjusted to achieve better performance. The results also compare to the system without UAV and OMA technique that shows the advantages of deploying UAV-assisted NOMA. Therefore, the design of NOMA for UAV relay-assisted V2X systems provides sufficient demand. The simulation results verified the effectiveness of the proposed UAV network and the precision of the theoretical analysis.
A systematic review of in-memory database over multi-tenancy
Authors: Shah Arpita , Bhatt Nikita
Published: January 2024

The significant cost and time are essential to obtain a comprehensive response, the response time to a query across a peer-to-peer database is one of the most challenging issues. This is particularly exact when dealing with large-scale data processing, where the traditional approach of processing data on a single machine may not be sufficient. The need for a scalable, reliable, and secure data processing system is becoming increasingly important. Managing a single in-memory database instance for multiple tenants is often easier than managing separate databases for each tenant. The research work is focused on scalability with multi-tenancy and more efficiency with a faster querying performance using in-memory database approach. We compare the performance of a row-oriented approach and column-oriented approach on our benchmark human resources (HR) schema using Oracle TimesTen in-memory database. Also, we captured some of the key advantages on optimization dimension(s) are the traditional approach, late-materialization, compression and invisible join on column-store (c-store) and row-base. When compression and late materialization are enabled in a query set; it improves the overall performance of query sets. In particular, the paper aims to elucidate the motivations behind multi-tenant application requirements concerning the database engine and highlight major designs over in-memory database for the tenancy approach on cloud.
Prediction of the risk of developing heart disease using logistic regression
Authors: Salau Ayodeji Olalekan , Assegie Tsehay Admassu , Markus Elisha Didam , Eneh Joy Nnenna , Ozue ThankGod Izuchukwu
Published: January 2024

Heart disease (HD) accounts for more deaths every year than other illnesses. World Health Organization (WHO) assessed 17.9 million life losses caused by heart disease in 2016, demonstrating 31% of all international life losses. Three-quarters of these life losses occur in low and middle-income nations. Machine learning (ML), due to advanced precision in pattern recognition and classification, demonstrates to be in effect in complementing decision-making and threat prediction from the huge number of HD data created by the healthcare sector. Thus, this study aims to develop a logistic regression model (LRM) for predicting the risk of getting HD in ten years. The study explores the different methodologies for improving the performance of base LRM for predicting whether a person gets HD after ten years or not. The result demonstrates the capability of LRM in predicting the risks of getting HD after ten years. The LRM achieves 97.35% accuracy with the recursive feature elimination and random under-sampling. This implies that the LRM can play an important role in precautionary methods to avoid the risk of HD.
Predictive modeling for breast cancer based on machine learning algorithms and features selection methods
Authors: Al Tawil Arar , Almazaydeh Laiali , Alqudah Bilal , Zaid Abualkishik Abedallah , A. Alwan Ali
Published: January 2024

Breast cancer is one of the leading causes of death among women worldwide. However, early prediction of breast cancer plays a crucial role. Therefore, strong needs exist for automatic accurate early prediction of breast cancer. In this paper, machine learning (ML) classifiers combined with features selection methods are used to build an intelligent tool for breast cancer prediction. The Wisconsin diagnostic breast cancer (WDBC) dataset is used to train and test the model. Classification algorithms, including support vector machine (SVM), light gradient boosting machine (LightGBM), random forest (RF), logistic regression (LR), k-nearest neighbors (k-NN), and naïve Bayes, were employed. Performance measures for each of them were obtained, namely: accuracy, precision, recall, F-score, Kappa, Matthews correlation coefficient (MCC), and time. The results indicate that without feature selection, LightGBM achieves the highest accuracy at 95%. With minimum redundancy maximum relevance (mRMR) feature selection (15 features), LightGBM outperforms other classifiers, achieving an accuracy of 98%. For Pearson correlation coefficient feature selection (15 features), LightGBM also excels with a 95% accuracy rate. Lasso feature selection (5 features) produces varied results across classifiers, with logistic regression achieving the highest accuracy at 96%. These findings underscore the importance of feature selection in refining model performance and in improving detection for breast cancer.
An efficient convolutional neural network-extreme gradient boosting hybrid deep learning model for disease detection applications
Authors: Bhaskar Navaneeth , Ajithkumar Aswathy Maruthompilli , Tupe-Waghmare Priyanka
Published: January 2024

In this paper, we present an efficient deep-learning hybrid model comprising an extreme gradient boosting (XGBoost) supervised learning algorithm and convolutional neural networks (CNN) for the automated detection of diseases. The proposed model is implemented and tested to detect type-2 diabetes by measuring the acetone concentration in the exhaled breath. Acetone will be present in much higher concentrations in type-2 diabetic patients compared to non-diabetic people. A novel sensing module is designed and implemented in our study to measure the acetone concentration in exhaled breath. The proposed approach delivered good results, with a classification accuracy of 97.14%. The findings of this study show how effectively the proposed detection module functions in disease diagnosis applications. As the detection process is simple and non-invasive, people can undergo routine checks for diabetes with the proposed detection module.
An overlapping conscious relief-based feature subset selection method
Authors: Mim Nishat Tasnim , Kadir Md. Eusha , Akhter Suravi , Khan Muhammad Asif Hossain
Published: January 2024

Feature selection is considered as a fundamental prepossessing step in various data mining and machine learning based works. The quality of features is essential to achieve good classification performance and to have better data analysis experience. Among several feature selection methods, distance-based methods are gaining popularity because of their eligibility in capturing feature interdependency and relevancy with the endpoints. However, most of the distance-based methods only rank the features and ignore the class overlapping issues. Features with class overlapping data work as an obstacle during classification. Therefore, the objective of this research work is to propose a method named overlapping conscious MultiSURF (OMsurf) to handle data overlapping and select a subset of informative features discarding the noisy ones. Experimental results over 20 benchmark dataset demonstrates the superiority of OMsurf over six existing state-of-the-art methods
Agarwood oil quality identification using artificial neural network modelling for five grades
Authors: Mohd Huzir Siti Mariatul Hazwa , Tajuddin Saiful Nizam , Mohd Yusoff Zakiah , Ismail Nurlaila , Almisreb Ali Abd , Taib Mohd Nasir
Published: January 2024

Agarwood (Aquilaria Malaccensis) oil stands out as one of the most valuable and highly sought-after oils with a hefty price tag due to its widespread use of fragrances, incense, perfumes, ceremonial practices, medicinal applications and as a symbol of luxury. However, nowadays the conventional method that rely on color alone has its limitations as it yields varying results depending on individual panelists' experiences. Hence, the quality identification system of Agarwood oil using its chemical compounds had been proposed in this study to enhance the precision of the Agarwood oil grades thus addressing the shortcomings of traditional methods. This study indicates that the primary chemical compounds of Agarwood oil encompass ɤ-Eudesmol, ar-curcumene, β-dihydroagarofuran, ϒ-cadinene, α-agarofuran, allo-aromadendrene epoxide, valerianol, α-guaiene, 10-epi-ɤ-eudesmol, β-agarofuran and dihydrocollumellarin. This study employed artificial neural network analysis with the implementation of Levenberg-Marquardt algorithm to identify the Agarwood oil grades. The study's findings revealed that this modeling system of five grades got 100% accuracies with mean square error of 0.14338×10-08. Notably, this lowest mean square error (MSE) value falls within the best hidden neuron 3. These study outcomes play a pivotal role in highlighting the Levenberg Marquardt- artificial neural network (LM-ANN) modeling that contribute to the successful of Agarwood oil quality identification using its chemical compounds.
Smart monitoring technique for solar cell systems using internet of things based on NodeMCU ESP8266 microcontroller
Authors: Ali Ahmed H. , El-Kammar Raafat A. , Hamed Hesham F. Ali , Elbaset Adel A. , Hossam Aya
Published: January 2024

Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
O Suicídio de Jean Améry (1968-1978)
Authors: Gonçalves Marcos
Published: January 2024

Enfoca-se a história da reflexão de Jean Améry (1912-1978) sobre o envelhecimento e a morte voluntária. Prisioneiro e sobrevivente de campos de concentração e extermínio da segunda guerra, Améry teve uma relação cotidiana com a violência e a morte. Na década de 1960, produziu de modo mais organizado uma série de ensaios que se tornaram referência na literatura de teor testemunhal. A hipótese é que as reflexões de Améry sobre o suicídio, e a decisão por ser o algoz de si mesmo em 1978, passam a tomar parte mais enfática do seu trabalho intelectual em 1968, com a publicação do ensaio Über das Altern. Revolte und Resignation. O artigo procura não perder de vista a dialética sujeito/coletivo, indivíduo/sociedade, e considera a dimensão histórica das experiências de Améry, constituintes da contemporaneidade de suas ideias.
Fishes of Cocibolca, the great Central American lake
Authors: Contreras-MacBeath Topiltzin , Rodríguez Pérez Byron Josue , Mejia-Mojica Humberto , Rivas-González Juan Manuel
Published: January 2024

The diversity of freshwater fish species from Lake Cocibolca (Nicaragua) is presented, describing the history of biological explorations in the lake from the first record in 1519, to the 52 species that are listed today. Information on current and future threats is also included.