bluuebunny/crossref_metadata_2025 huggingface dataset:
Supplementary Figure S2 from MYC Inhibition Potentiates CD8+ T Cells Against Multiple Myeloma and Overcomes Immunomodulatory Drug Resistance
Authors: Davis Lorraine N. , Walker Zachary J. , Reiman Lauren T. , Parzych Sarah E. , Stevens Brett M. , Jordan Craig T. , Forsberg Peter A. , Sherbenou Daniel W.
Published: July 2024

Supplemental Figure S2. Pathway analysis of gene expression changes in IMiD -refractory MM from the MMRF RNA sequencing database.
Supplementary Table S2 from Clinical and Genomic Landscape of RAS Mutations in Gynecologic Cancers
Authors: Son Ji , Zhang Yingao , Lin Heather , Mirallas Oriol , Alvarez Ballesteros Pablo , Nardo Mirella , Clark Natalie , Hillman R. Tyler , Campbell Erick , Holla Vijaykumar , Johnson Amber M. , Biter Amadeo B. , Yuan Ying , Cobb Lauren P. , Gershenson David M. , Jazaeri Amir A. , Lu Karen H. , Soliman Pamela T. , Westin Shannon N. , Euscher Elizabeth D. , Lawson Barrett C. , Yang Richard K. , Meric-Bernstam Funda , Hong David S.
Published: July 2024

Histologic distribution of gynecologic cancers by RAS mutation (expanded histologic categories, percentages by row)
Supplementary Figure S5 from Clinical and Genomic Landscape of RAS Mutations in Gynecologic Cancers
Authors: Son Ji , Zhang Yingao , Lin Heather , Mirallas Oriol , Alvarez Ballesteros Pablo , Nardo Mirella , Clark Natalie , Hillman R. Tyler , Campbell Erick , Holla Vijaykumar , Johnson Amber M. , Biter Amadeo B. , Yuan Ying , Cobb Lauren P. , Gershenson David M. , Jazaeri Amir A. , Lu Karen H. , Soliman Pamela T. , Westin Shannon N. , Euscher Elizabeth D. , Lawson Barrett C. , Yang Richard K. , Meric-Bernstam Funda , Hong David S.
Published: July 2024

Co-mutation analysis of RAS mutations in gynecologic cancers by cancer type (a) uterine, (b) ovarian, (c) cervical and vulvovaginal
Supplementary Figure S2 from Clinical and Genomic Landscape of RAS Mutations in Gynecologic Cancers
Authors: Son Ji , Zhang Yingao , Lin Heather , Mirallas Oriol , Alvarez Ballesteros Pablo , Nardo Mirella , Clark Natalie , Hillman R. Tyler , Campbell Erick , Holla Vijaykumar , Johnson Amber M. , Biter Amadeo B. , Yuan Ying , Cobb Lauren P. , Gershenson David M. , Jazaeri Amir A. , Lu Karen H. , Soliman Pamela T. , Westin Shannon N. , Euscher Elizabeth D. , Lawson Barrett C. , Yang Richard K. , Meric-Bernstam Funda , Hong David S.
Published: July 2024

Prevalence of RAS mutations in gynecologic cancers by histology for (a) NRAS and (b) HRAS. In parentheses, mut (n)/histology (n)
Supplementary Table S8 from Model-Informed Clinical Pharmacology Profile of a Novel Fixed-Dose Combination of Nivolumab and Relatlimab in Adult and Adolescent Patients with Solid Tumors
Authors: Zhao Yue , Hu Zheyi , Bathena Sai Praneeth , Keidel Sarah , Miller-Moslin Karen , Statkevich Paul , Bello Akintunde , Roy Amit , Suryawanshi Satyendra
Published: July 2024

Predicted Relatlimab Exposures at 160 mg Q4W 30-Minute Infusion and 60-Minute Infusion in Adult Patients Treated with Relatlimab Plus Nivolumab
Supplementary Table S2 from Model-Informed Clinical Pharmacology Profile of a Novel Fixed-Dose Combination of Nivolumab and Relatlimab in Adult and Adolescent Patients with Solid Tumors
Authors: Zhao Yue , Hu Zheyi , Bathena Sai Praneeth , Keidel Sarah , Miller-Moslin Karen , Statkevich Paul , Bello Akintunde , Roy Amit , Suryawanshi Satyendra
Published: July 2024

Parameter Estimates of the Full Relatlimab Population Pharmacokinetic Model
Supplementary Figure S3 from Model-Informed Clinical Pharmacology Profile of a Novel Fixed-Dose Combination of Nivolumab and Relatlimab in Adult and Adolescent Patients with Solid Tumors
Authors: Zhao Yue , Hu Zheyi , Bathena Sai Praneeth , Keidel Sarah , Miller-Moslin Karen , Statkevich Paul , Bello Akintunde , Roy Amit , Suryawanshi Satyendra
Published: July 2024

Prediction-Corrected Visual Predictive Check of a) Relatlimab Concentrations versus Actual Time after Previous Dose and b) Relatlimab trough concentrations versus actual time after first dose in 1L MEL and Prior-IO MEL Patients Who Received 80 mg Q2W and 160 mg Q4W Dosing Regimen (Full Population Pharmacokinetic Model)
Supplementary Data 1 from Spatially Preserved Multi-Region Transcriptomic Subtyping and Biomarkers of Chemoimmunotherapy Outcome in Extensive-Stage Small Cell Lung Cancer
Authors: Peressini Melina , Garcia-Campelo Rosario , Massuti Bartomeu , Martí Cristina , Cobo Manuel , Gutiérrez Vanesa , Dómine Manuel , Fuentes José , Majem Margarita , de Castro Javier , Córdoba Juan F. , Diz María P. , Isla Dolores , Esteban Emilio , Carcereny Enric , Vila Laia , Moreno-Vega Alberto , Ros Silverio , Moreno Amaia , García Francisco J. , Huidobro Gerardo , Aguado Carlos , Cebey-López Victor , Valdivia Javier , Palmero Ramón , Lianes Pilar , López-Brea Marta , Vidal Oscar J. , Provencio Mariano , Arriola Edurne , Baena Javier , Herrera Mercedes , Bote Helena , Molero Magdalena , Adradas Vera , Ponce-Aix Santiago , Nuñez-Buiza Angel , Ucero Álvaro , Hernandez Susana , Lopez-Rios Fernando , Conde Esther , Paz-Ares Luis , Zugazagoitia Jon
Published: July 2024

Supplementary Figures
Supplementary Table S7 from Antibody–Drug Conjugate Sacituzumab Govitecan Enables a Sequential TOP1/PARP Inhibitor Therapy Strategy in Patients with Breast Cancer
Authors: Bardia Aditya , Sun Sheng , Thimmiah Nayana , Coates James T. , Wu Bogang , Abelman Rachel O. , Spring Laura , Moy Beverly , Ryan Phoebe , Melkonyan Mark N. , Partridge Ann , Juric Dejan , Peppercorn Jeffrey , Parsons Heather , Wander Seth A. , Attaya Victoria , Lormil Brenda , Shellock Maria , Nagayama Aiko , Bossuyt Veerle , Isakoff Steven J. , Tolaney Sara M. , Ellisen Leif W.
Published: July 2024

Table S7. Representativeness of Study Participants
Data from Phase II Clinical Trial of Intravenous Levothyroxine to Mitigate Pharyngocutaneous Fistula in Euthyroid Patients Undergoing Salvage Laryngectomy
Authors: Heft Neal Molly E. , Haring Catherine T. , Bellile Emily , Jaffe Craig C. , Shuman Andrew G. , Chinn Steven B. , Stucken Chaz L. , Malloy Kelly M. , Casper Keith A. , Prince Mark E.P. , Chepeha Douglas B. , Rosko Andrew J. , Spector Matthew E.
Published: July 2024

AbstractPurpose:
Patients undergoing head and neck cancer surgery after prior radiation or chemoradiation are at high risk for wound complications. Hypothyroidism is a known risk factor for wound complications, especially fistulae after salvage total laryngectomy. The purpose of this phase II clinical trial is to investigate the effect of perioperative intravenous levothyroxine supplementation on wound complications in patients undergoing salvage total laryngectomy.
Patients and Methods:
Euthyroid patients previously treated with radiation/chemoradiation undergoing total laryngectomy were prospectively recruited (n = 72). Postoperatively, intravenous levothyroxine was administered at a weight-based dose (1.3 mcg/kg/d) and transitioned to enteral dosing on day 7. Free T3, T4, and thyroid-stimulating hormones were collected, and dosing was adjusted accordingly. The primary endpoints were rates of fistula formation and fistula requiring reoperation, compared with matched historic controls. All patients were monitored for adverse effects.
Results:
The rate of postoperative hypothyroidism was 21% compared with 49% in a matched historic cohort. The rate of fistula formation was 18.1%, whereas the rate of fistula requiring reoperation was 4.2%, significantly lower than rates in our historic cohort (34.6% and 14.8%, respectively; P = 0.02 and 0.01). Postoperative hypothyroidism and recurrent clinical stage predicted fistula requiring reoperation in multivariate analysis; other acute phase reactants were not predictive. There were no observed adverse events related to levothyroxine supplementation.
Conclusions:
Postoperative intravenous levothyroxine supplementation reduced rates of acute hypothyroidism, fistula formation, and fistula requiring reoperation in patients undergoing salvage total laryngectomy without adverse effects. Intravenous levothyroxine is a viable strategy to reduce wound complications in this high-risk patient population.
Data from Model-Informed Clinical Pharmacology Profile of a Novel Fixed-Dose Combination of Nivolumab and Relatlimab in Adult and Adolescent Patients with Solid Tumors
Authors: Zhao Yue , Hu Zheyi , Bathena Sai Praneeth , Keidel Sarah , Miller-Moslin Karen , Statkevich Paul , Bello Akintunde , Roy Amit , Suryawanshi Satyendra
Published: July 2024

AbstractPurpose:
Progression-free survival (PFS) was significantly improved with nivolumab 480 mg plus relatlimab 160 mg fixed-dose combination (FDC) every 4 weeks (Q4W) versus nivolumab alone in patients with previously untreated advanced melanoma in RELATIVITY-047. In addition, RELATIVITY-020 (Part D) demonstrated a manageable safety profile and potential for durable response with nivolumab plus relatlimab in previously treated patients. Here, we evaluate the clinical pharmacology profile (CPP) of nivolumab plus relatlimab to support the approved regimen for adult and adolescent patients with advanced melanoma and its continued clinical development in solid tumors.
Experimental Design:
The pharmacokinetics (PK) and immunogenicity of relatlimab and nivolumab were assessed using data from RELATIVITY-047 and RELATIVITY-020. Patients with advanced solid tumors received relatlimab alone or nivolumab plus relatlimab as single-agent vials (SAV) or FDC. PK was characterized using a population PK (popPK) model.
Results:
Relatlimab demonstrated nonlinear and time-varying PK. Nonlinearity in relatlimab PK represented approximately 31% of total CL of relatlimab 160 mg Q4W. Relatlimab PK was dose proportional at doses ≥160 mg Q4W. Geometric mean exposures were similar for SAV and FDC cohorts receiving equivalent dosing regimens. No dose adjustment was required for covariates. Incidence of relatlimab antidrug antibodies was <6% for nivolumab plus relatlimab and had no clinically meaningful impact. There was no PK-related drug interaction of nivolumab plus relatlimab.
Conclusions:
The CPP of relatlimab alone or in combination with nivolumab supports the approved dosing in advanced melanoma and the continued evaluation of nivolumab and relatlimab across other solid tumors.

See related commentary by Gopalakrishnan and Amaria, p. 2862
Spatial Heterogeneity of Immune Regulators Drives Dynamic Changes in Local Immune Responses, Affecting Disease Outcomes in Pancreatic Cancer
Authors: Karamitopoulou Eva , Wenning Anna S. , Acharjee Animesh , Aeschbacher Pauline , Marinoni Ilaria , Zlobec Inti , Gloor Beat , Perren Aurel
Published: July 2024

Purpose:

Pancreatic ductal adenocarcinoma (PDAC) is considered a low-immunogenic (LI) tumor with a “cold” tumor microenvironment and is mostly unresponsive to immune checkpoint blockade therapies. In this study, we decipher the impact of intratumoral heterogeneity of immune determinants on antitumor responses.

Experimental Design:

We performed spatial proteomic and transcriptomic analyses and multiplex immunofluorescence on multiple tumor regions, including tumor center (TC) and invasive front (IF), from 220 patients with PDAC, classified according to their transcriptomic immune signaling into high-immunogenic PDAC (HI-PDAC, n = 54) and LI PDAC (LI-PDAC, n = 166). Spatial compartments (tumor: pancytokeratin+/CD45− and leukocytes: pancytokeratin−/CD45+) were defined by fluorescence imaging.

Results:

HI-PDAC exhibited higher densities of cytotoxic T lymphocytes with upregulation of T-cell priming–associated immune determinants, including CD40, ITGAM, glucocorticoid-induced TNF–related receptor, CXCL10, granzyme B, IFNG, and HLA-DR, which were significantly more prominent at the IF than at the TC. In contrast, LI-PDAC exhibited immune-evasive tumor microenvironments with downregulation of immune determinants and a negative gradient from TC to IF. Patients with HI-PDAC had significantly better outcomes but showed more frequently exhausted immune phenotypes.

Conclusions:

Our results indicate strategic differences in the regulation of immune determinants, leading to different levels of effectiveness of antitumor responses between HI and LI tumors and dynamic spatial changes, which affect the evolution of immune evasion and patient outcomes. This finding supports the coevolution of tumor and immune cells and may help define therapeutic vulnerabilities to improve antitumor immunity and harness the responsiveness to immune checkpoint inhibitors in patients with PDAC.
Figure S1 from Tumor-Immune Signatures of Treatment Resistance to Brentuximab Vedotin with Ipilimumab and/or Nivolumab in Hodgkin Lymphoma
Authors: Gonzalez-Kozlova Edgar , Huang Hsin-Hui , Jagede Opeyemi A. , Tuballes Kevin , Del Valle Diane M. , Kelly Geoffrey , Patel Manishkumar , Xie Hui , Harris Jocelyn , Argueta Kimberly , Nie Kai , Barcessat Vanessa , Moravec Radim , Altreuter Jennifer , Duose Dzifa Y. , Kahl Brad S. , Ansell Stephen M. , Yu Joyce , Cerami Ethan , Lindsay James R. , Wistuba Ignacio I. , Kim-Schulze Seunghee , Diefenbach Catherine S. , Gnjatic Sacha
Published: July 2024

Supplemental Figure 1. A. Volcano plots showing differentially expressed proteins with P<0.05 between treatments.
Figure 3 from Tumor-Immune Signatures of Treatment Resistance to Brentuximab Vedotin with Ipilimumab and/or Nivolumab in Hodgkin Lymphoma
Authors: Gonzalez-Kozlova Edgar , Huang Hsin-Hui , Jagede Opeyemi A. , Tuballes Kevin , Del Valle Diane M. , Kelly Geoffrey , Patel Manishkumar , Xie Hui , Harris Jocelyn , Argueta Kimberly , Nie Kai , Barcessat Vanessa , Moravec Radim , Altreuter Jennifer , Duose Dzifa Y. , Kahl Brad S. , Ansell Stephen M. , Yu Joyce , Cerami Ethan , Lindsay James R. , Wistuba Ignacio I. , Kim-Schulze Seunghee , Diefenbach Catherine S. , Gnjatic Sacha
Published: July 2024

Cellular dynamics in HL during checkpoint blockade treatment. A, Cell type composition of major cell groups (myeloid and lymphoid) for all available samples at baseline. This bar plot shows the composition and variation of cellular components, including unassigned cells, across all patients. The cell types were identified using a semi-automated approach with the software Astrolabe. B, Heatmap map showing differentially abundant cell type changes over time. The rows are shown as relative abundance or scaled (z-score) allowing comparison across samples for each cell type simultaneously. C–F, Boxplots and line plots colored based on treatment showing the dynamics for the differentially abundant cell types. G, Boxplots showing the differentially abundant cells between treatments at baseline. H, Comparison of cell abundances for different treatments after the start of treatment.
Data from Tumor-Immune Signatures of Treatment Resistance to Brentuximab Vedotin with Ipilimumab and/or Nivolumab in Hodgkin Lymphoma
Authors: Gonzalez-Kozlova Edgar , Huang Hsin-Hui , Jagede Opeyemi A. , Tuballes Kevin , Del Valle Diane M. , Kelly Geoffrey , Patel Manishkumar , Xie Hui , Harris Jocelyn , Argueta Kimberly , Nie Kai , Barcessat Vanessa , Moravec Radim , Altreuter Jennifer , Duose Dzifa Y. , Kahl Brad S. , Ansell Stephen M. , Yu Joyce , Cerami Ethan , Lindsay James R. , Wistuba Ignacio I. , Kim-Schulze Seunghee , Diefenbach Catherine S. , Gnjatic Sacha
Published: July 2024

Abstract
To investigate the cellular and molecular mechanisms associated with targeting CD30-expressing Hodgkin lymphoma (HL) and immune checkpoint modulation induced by combination therapies of CTLA4 and PD1, we leveraged Phase 1/2 multicenter open-label trial NCT01896999 that enrolled patients with refractory or relapsed HL (R/R HL). Using peripheral blood, we assessed soluble proteins, cell composition, T-cell clonality, and tumor antigen-specific antibodies in 54 patients enrolled in the phase 1 component of the trial. NCT01896999 reported high (>75%) overall objective response rates with brentuximab vedotin (BV) in combination with ipilimumab (I) and/or nivolumab (N) in patients with R/R HL. We observed a durable increase in soluble PD1 and plasmacytoid dendritic cells as well as decreases in plasma CCL17, ANGPT2, MMP12, IL13, and CXCL13 in N-containing regimens (BV + N and BV + I + N) compared with BV + I (P < 0.05). Nonresponders and patients with short progression-free survival showed elevated CXCL9, CXCL13, CD5, CCL17, adenosine–deaminase, and MUC16 at baseline or after one treatment cycle and a higher prevalence of NY-ESO-1-specific autoantibodies (P < 0.05). The results suggest a circulating tumor-immune-derived signature of BV ± I ± N treatment resistance that may be useful for patient stratification in combination checkpoint therapy.
Significance:
Identification of multi-omic immune markers from peripheral blood may help elucidate resistance mechanisms to checkpoint inhibitor and antibody–drug conjugate combinations with potential implications for treatment decisions in relapsed HL.
Comparative study of password storing using hash function with MD5, SHA1, SHA2, and SHA3 algorithm
Authors: Natho Parinya , Somsuphaprungyos Suwit , Boonmee Salinun , Boonying Sangtong
Published: July 2024

The main purpose of passwords is to prevent unauthorized people from accessing the system. The rise in internet users has led to an increase in password hacking, which has resulted in a variety of problems. These issues include opponents stealing a company's or nation's private information and harming the economy or the organization's security. Password hacking is a common tool used by hackers for illegal purposes. Password security against hackers is essential. There are several ways to hack passwords, including traffic interception, social engineering, credential stuffing, and password spraying. In an attempt to prevent hacking, hashing algorithms are therefore mostly employed to hash passwords, making password cracking more difficult. In the suggested work, several hashing techniques, including message digest (MD5), secure hash algorithms (SHA1, SHA2, and SHA3) have been used. They have become vulnerable as a result of being used to store passwords. A rainbow table attack is conceivable. Passwords produced with different hash algorithms can have their hash values attacked with the help of the Hashcat program. It is proven that the SHA3 algorithm can help with more secure password storage when compared to other algorithms.
Comparing feature usage in IMU-based gesture control for omnidirectional robot via wearable glove
Authors: Syauqy Dahnial , Setiawan Eko , Widasari Edita Rosana
Published: July 2024

To improve the intuitiveness of maneuver control on omniwheeled mobile robot, many hand gesture-based robot controls have been developed. The focus of this research is to develop a wearable system for data acquisition from inertial measurement unit (IMU) sensors and compare its features to be used as gesture recognition using the random forest algorithm. With the need of resource constrained device for wearable system based on microcontrollers, we compared the use of Euler and quaternion-based orientation data as input features. As additional comparison, dimension reduction was also carried out using the principal component analysis (PCA) method. Hand gestures are recognized using data obtained by the IMU sensor embedded in the wearable glove. This study compared the accuracy and size of library files embedded in microcontrollers in several feature usage scenarios. The test evaluation results of all scenarios show that the use of all features provides a balance between high accuracy but small file sizes, respectively 99% and 9.2 KB. However, the use of other fewer features, such as by only using 3 Euler data, 4 quaternion data, or by using PCA algorithm (PC=3) can also be used since the accuracy is still above 90%, with a relatively larger file size.
Earthquake magnitude prediction in Indonesia using a supervised method based on cloud radon data
Authors: Pratama Thomas Oka , Sunarno Sunarno , Wijatna Agus Budhie , Haryono Eko
Published: July 2024

In the challenging realm of earthquake prediction, the reliability of forecasting systems has remained a persistent obstacle. This study focuses on earthquake magnitude prediction in Indonesia, leveraging supervised machine learning techniques and cloud radon data. We present an analysis of the tele-monitoring system, data collection methods, and the application of regression-based machine learning algorithms. Utilizing a comprehensive dataset spanning 30 training instances and 105 test instances, the study evaluates multiple metrics to ascertain the efficacy of the prediction models. Our findings reveal that the linear regression approach yields the best earthquake magnitude prediction method, with the lowest values across multiple evaluation metrics: standard deviation 0.40, mean absolute error (MAE) 0.30, mean absolute percentage error (MAPE) 6%, root mean square error (RMSE) 0.52, mean squared error (MSE) 0.28, symmetric mean absolute percentage error (SMAPE) 0.06, and conformal normalized mean absolute percentage error (cnSMAPE) 0.97. Additionally, we discuss the implications of the research results and the potential applications in enhancing existing earthquake prediction methodologies.
Robust embedded access control system based on face and encrypted QR with RPi4
Authors: Hammami Samir Marwan , Alhammami Muhammad
Published: July 2024

Facial-based recognition systems are commonly used for building access control, with the accuracy and computing requirements still being improved. On the other hand, QR codes are gaining rising attention as an input interface to many embedded applications. This paper proposes an embedded access control system that customises both previous techniques to be implemented on the CPU of a low-cost Raspberry Pi 4 computer. The achieved system works smoothly with a frame rate of 8.27 FPS, increasing the accessing control's robustness compared to a system based on face recognition only. It also offers the ability to control the access of unknown faces. In tandem with integration, this strengthens security measures, improves user experience, and outperforms conventional access control approaches, creating an attractive offer for many businesses.
Moving objects detection based on histogram of oriented gradient algorithm chip for hazy environment
Authors: Sharma Monika , Kaswan Kuldeep Singh , Yadav Dileep Kumar
Published: July 2024

The most important aspects of computer vision are moving object detection (MOD) and tracking. Many signal-processing applications use regional image statistics. Compute-intensive video and image processing with low latency and high throughput is done with field programmable gate array (FPGA) image processing. Local image statistics are used for edge identification and filtering. The histogram of oriented gradients (HoG) algorithm extracts local shape characteristics by equalizing histograms. The objective of the work is to design the hardware chip of the algorithm and perform the simulation in the Xilinx ISE 14.7 simulation environment. The performance of the chip is evaluated in Modelsim 10.0 simulation software to check its feasibility. The performance of the chip design is estimated on Viretx-5 FPGA and compared with the MATLAB-2020 image processing tool-based response time. This form of tracking typically deals with identifying, anchoring, and tracking images and videos. A mask made from a cut-out of the object can then determine the plane's coordinates depending on its position. This type of object tracking is frequently utilized in the field of augmented reality (AR). The algorithm is most suited for object detection using hardware controllers in haze and foggy environments.
An active two-stage class-J power amplifier design for smart grid’s 5G wireless networks
Authors: Sridhar Nagisetty , Senthilpari Chinnaiyan , Roslee Mardeni , Yong Wong Hin
Published: July 2024

The wireless communication networks in the smart grid’s advanced metering infrastructure (AMI) applications need 5G technology to support large data transmission efficiently. As the 5G wireless communication network’s overall bandwidth (BW) and efficiency depend on its power amplifier (PA), in this work, a two-stage class-J power amplifier’s design methodology that operates at 3.5 GHz centre frequency by utilizing the CGH40010F model gallium nitride (GaN) transistor is presented. The proposed design methodology involves proper designing of input, output, and interstage matching networks to achieve class-J operation with improved power gain over desired BW using the advanced design system (ADS) electronic design automation (EDA) tool and estimating its integration feasibility through active element-based design approach using the Mentor Graphics EDA tool. The proposed PA provides 54% drain efficiency (D.E), 53% power added efficiency (PAE) with a small signal gain of 27 dB at 3.5 GHz and 41 dBm power output with 21 dB of improved power gain across a BW of around 400 MHz using 28 V power supply into 50 Ω load. By replacing the two-stage PA's passive elements with active elements, its layout size is estimated to be (15.5×29.2) μm2 . The results of the proposed PA exhibit its integration feasibility and suitability for the smart grid’s 5G wireless networks.
Approximate single precision floating point adder for low power applications
Authors: Narayanappa Manjula , Yellampalli Siva Sankar
Published: July 2024

With an increasing demand for power-hungry data-intensive computing, design methodologies with low power consumption are increasingly gaining prominence in the industry. Most of the systems operate on critical and noncritical data both. An attempt to generate a precision result results in excessive power consumption and results in a slower system. For noncritical data, approximate computing circuits significantly reduce the circuit complexity and hence power consumption. In this paper, a novel approximate single precision floating point adder is proposed with an approximate mantissa adder. The mantissa adder is designed with three 8-bit full adder blocks. In this paper, a detailed mathematical background, and proposed design approach in terms of the circuit configuration and truth tables are discussed. Additionally, a concept of switching between exact computing and approximate computing is analysed considering an approximate carry look-ahead adder. The delay and power consumption for the exact operating mode and approximate operation mode considering varied window sizes is observed. Performance of the approximate computation is compared against exact computation and varied approximate computing approaches.
Arowana cultivation water quality monitoring and prediction using autoregressive integrated moving average
Authors: Daru April Firman , Susanto Susanto , Adhiwibowo Whisnumurti
Published: July 2024

Decorative fish is a fish that humans keep for amusement. There are many decorative fish that exist in this world, one of them is known as the Arowana fish (Scleropages Formosus). This fish is known around Asia including in Indonesia. However, to ensure the Arowana is living well is not easy. The water quality inside a farm must follow a strict balance. The pH of the water must not exceed or below 7 pH. Meanwhile, the total dissolved solid (TDS) salt must not exceed 1000 parts per million. If the balance collapsed, the Arowana fish will not grow. Thus, the owner must monitor the water to make sure that the water is ideal. There were many approaches including internet of things (IoT) solutions. However, they have weaknesses with prediction. Because of this reason, this study designed pH and TDS monitoring with autoregressive integrated moving average (ARIMA) as the algorithm. To achieve the solution, this study used experiment methodology as the research fundamental from top to bottom. According to the evaluation, this study found that the accuracy of ARIMA model is 98.12% for pH and 98.86% for TDS. On the contrary, the seasonal autoregressive integrated moving average (SARIMA) model has an accuracy of 98.52% for pH and 99.89% for TDS.
Internet of things and long range-based bridge slope early detection systems
Authors: Umar Nuraeni , Syarif Syafruddin , Dewiani Dewiani , Baharuddin Merna
Published: July 2024

This research proposes an internet of things and long range (LoRa)-based bridge slope status monitoring and warning system that is wireless, low-cost, and user-friendly, with continuous data sent. Bridge inspection officers can easily obtain bridge slope data via a web browser on a cell phone. The design uses Arduino integrated development environment software and an ITGMPU accelerometer sensors, TTGO ESP32, cellphones, successfully identified tilt angle variations from 0.11° to 15.2° were the research's outputs, and and they were continuously transmitted to the bridge inspection officer's mobile phone. Measurements of throughput, quality of service (QoS), and latency characteristics have been made to assess the internet network's performance. The network system performance statistics show an average measured network delay of 1.2 seconds, a throughput of 85 bps, and a QoS of 0%. Consequently, the system performs well and the internet network performance falls into the very good range.
Internet based highly secure data transmission system in health care monitoring system
Authors: Ram Gubbala Bhaskar Phani , Thirunarayanan Shankar
Published: July 2024

The health care systems in our contemporary countries are advancing rapidly in terms of maturity and professionalism. In an effort to alleviate the current burden on the public health system and boost the popularity of regular health self-checks, this method has been developed for producing prediagnoses that are easier to use, quicker, and more accurate. To ascertain how well the heart is circulating oxygen throughout the body, a pulse test, a painless examination that measures an individual's degree of oxygen saturation, is used. It can be used to evaluate the state of any patient with a disease, particularly those with pulmonary problems. Diseases in these patients could need ongoing observation and care. Our system comes to the rescue in order to resolve this problem. This portable system is simple to use and may be taken anywhere by the subject. The internet of things (IoT) will update the pertinent parameters. This health monitoring system's controller is made up of an adaptor, a saturation of peripheral oxygen (SPO2 ) sensor (a blood oxygen meter), a temperature sensor, a heart rate sensor, a WiFi module, and a liquid crystal display (LCD).
Design of IoT-based monitoring system for temperature and dissolved oxygen levels in catfish aquaculture pond water
Authors: Sari Nurma , Savitri Yuniar , Wahyono Sri Cahyo , Santoso Joko , Nasrulloh Amar Vijai
Published: July 2024

One of the fish in Indonesian waters that has been successfully bred and cultivated is the catfish (Pangasius sp.). In catfish farming, there are several water quality factors that need to be considered, such as temperature and dissolved oxygen levels. Based on the existing description, it is very important to pay attention to the water quality of aquaculture ponds, especially temperature and dissolved oxygen levels for fish survival. This study aims to create an internet of things (IoT) based monitoring system for temperature and dissolved oxygen levels in catfish aquaculture pond water based on NodeMCU ESP8266. Monitoring system is using SEN0237 gravity analog dissolved oxygen sensor, DS18B20 sensor module, NodeMCU ESP8266, 20×4-character liquid-crystal display (LCD), micro secure digital (SD) card module, internet modem. Data from measurements of temperature and dissolved oxygen levels are stored online in the Adafruit.io database in the .csv format and on a micro secure digital (SD) card in the device in the .txt format. The lowest value of dissolved oxygen levels and temperature are 3.4 mg/L or 3.4 ppm and a temperature of 27.9 °C, respectively. Meanwhile, the highest value of dissolved oxygen levels and temperature are 4.6 mg/L or 4.6 ppm and temperature of 30.9 °C, respectively.
IoT-enabled smart cities towards green energy systems: a review
Authors: Ajra Husnul , Majid Mazlina Abdul , Islam Md. Shohidul
Published: July 2024

Integration of internet of things (IoT) in smart city management to improve various functions and living standards due to increasing population growth has dramatically evolved ubiquitous and essential services at various stages of urbanization. Hence, smart cities need to be eco-friendly by improving various sectors like education, health, and transport to provide an urban and sustainable quality of life through solving complicated green energy networks, controlling toxic pollution risks, and public safety. Linking optimized green energy systems with the production and automation of advanced applications is crucial to compose implementation strategies for smart city services. This paper aims to conduct a review on eco-friendly plans and infrastructure of IoT-enabled smart cities by exploiting green energy approaches. This study performs critical observations, ideas, and analyses of recent research in the context of our mentioned research theme. This paper points out the technical and functional challenges of an optimal performance-based green IoT-enabled smart city infrastructure. In this sense, this study organizes observations of relevant initiatives, technologies, and experiences in IoT-enabled smart cities, as well as how to embed it with green energy. Moreover, it can provide significant directions to intellectuals and authorities to develop IoT-enabled smart city applications for prospective research.
Improving the performance of IoT devices that use Wi-Fi
Authors: Razzaq Ali Ahmed , Rao Kunjam Nageswara
Published: July 2024

Providing quality service to users of the internet of things (IoT) entails addressing two crucial aspects: one related to security and the other concerning the limited resources of IoT devices. We will face a challenge while using timesensitive applications within a network that utilizes a high-performance Wi-Fi technology with exceeding energy consumption. Due to this research challenge, we propose a new algorithm, IoT-quality of service (QoS), designed to achieve a true balance between enhancing the security aspects of IoT devices and improving network-hardware performance. Thus, the algorithm efficiently manages the limited energy resources by monitoring energy levels, communication quality, and queuing delay at access points. This is accomplished by utilizing a streamlined identity management system capable of achieving authentication and access authorization with reduced loading for IoT devices. The research hypothesis underwent validation through a comparative analysis of its performance against the conventional model of a Wi-Fi-based IoT device. This evaluation was conducted utilizing the NS3 simulator and was based on a predetermined set of parameters influencing the examined performance metrics, including power consumption, throughput, delay, and response time. The findings exposed the superiority of the proposed algorithm.
A novel smart irrigation framework with timing allocation using solenoid valves and Arduino microcontroller
Authors: Ramakrishnaiah Vijaya Kumar Hemapura , Lakshmappa Harish , Gururaj Bharathi , Muniyappa Ramesha , Siddaramaiah Pavan Godekere , Bylamurthy Nagesh Hunnigere
Published: July 2024

Irrigation in agriculture is the most common way of providing water to agricultural land or fields at normal stretches through channels and embedded platforms with the internet of things (IoT), to upgrade rural development. In this paper, the arrangement of the various types of irrigation systems and embedded platforms for agriculture was studied. The embedded platform can be designed in a suitable framework that can assist the irrigation system in growing more water-required crops. In this work, three relay switches, two solenoid valves, and one water pump source were connected to Arduino ESP32. The free version of Sinric Google Cloud was utilized significantly to control three devices namely, two solenoid valves using two relay switches and a water pump source using one relay switch. The experiment was executed in a prototype manner with timing allocation by considering two agricultural fields where water was supplied either in one field at a time and showed more prominent results to save time, replacement of manual valves, man intervention, power, and suitable quantity of water for more water-required crops namely, arecanut and coconut.
Leveraging the learning focal point algorithm for emotional intelligence
Authors: Mansour Salah Eddine , Sakhi Abdelhak , Kzaz Larbi , Sekkaki Abderrahim
Published: July 2024

One of the secrets of the success of the education process is taking into account the learner’s feelings. That is, the teacher must be characterized by high emotional intelligence (EI) to understand the student’s feelings in order to facilitate the indoctrination process for him. Within the framework of the project to create a robot teacher, we had to add this feature because of its importance. In this article, we create a computer application that classifies students' emotions based on deep learning and learning focal point (LFP) algorithm by analyzing facial expressions. That is, the robot will be able to know whether the student is happy, excited, or sad in order to deal with him appropriately.
Energy-efficient clustering and routing using fuzzy k-medoids and adaptive ranking-based wireless sensor network
Authors: Sivaraman Haritha K. , Leburu Rangaiah
Published: July 2024

The wireless sensor network (WSN) is a vital component of infrastructure that is seeing tremendous demand and quick expansion in a variety of industries, including forestry, airports, healthcare, and the military. Increasing network lifetime and reducing power consumption (PC) are now major goals in WSN research. This research proposes a unique energy-efficient cross-layer WSN design that aims to maximize network lifetime while maintaining quality of service (QoS) criteria to address these challenges. The research initially utilizes the fuzzy k-medoids (FKMeds) clustering technique to group sensor nodes (SN) to improve resilience, scalability, and minimize network traffic. Following that, the hybrid improved grey wolf and ant colony (HIGWAC) optimization approach is applied to choose cluster heads (CH), minimizing distances, reducing latency, and optimizing energy stability. Finally, data is transmitted through the shortest pathways using the adaptive ranking-based energy-efficient opportunistic routing (ARanEOR) protocol, which ensures effective and energy-conserving routing in WSN while dynamically lowering network overhead. Compared to existing approaches, the proposed method in this study outperforms them in terms of energy efficiency, latency, and network longevity.
Channel reconstruction through improvised deep learning architecture for high-speed networks
Authors: Jayashanka Parinitha , Shobha Byrappa Nanjundaiah
Published: July 2024

Efficient acquisition of channel state information (CSI) is quite complicated process but immensely essential to exploit probable benefits of massive multiple input multiple output (MIMO) systems. Therefore, a deep learningbased model is utilized to estimate channel feedback in a massive MIMO system. The proposed improvised deep learning-based channel estimation (IDLCE) model enhances channel reconstruction efficiency by using multiple convolutional layers and residual blocks. The proposed IDLCE model utilizes encoder network to compress CSI matrices where decoder network is used to downlink reconstruct CSI matrices. Here, an additional quantization block is incorporated to improve feedback reconstruction accuracy by reducing channel errors. A COST 2,100 model is adopted to analyse performance efficiency for both indoor and outdoor scenarios. Further, deep learning-based model is used to train thousands of parameter and correlation coefficients much faster and to minimize computational complexity. The proposed IDLCE model evaluate performance in terms of normalized mean square error (NMSE), correlation efficiency and reconstruction accuracy and compared against varied state-of-art-channel estimation techniques. Excellent performance results are obtained with large improvement in channel reconstruction accuracy
Whole-head high-density diffuse optical tomography to map infant audio-visual responses to social and non-social stimuli
Authors: Collins-Jones Liam H. , Gossé Louisa K. , Blanco Borja , Bulgarelli Chiara , Siddiqui Maheen , Vidal-Rosas Ernesto E. , Duobaitė Nida , Nixon-Hill Reuben W. , Smith Greg , Skipper James , Sargent Tim , Powell Samuel , Everdell Nicholas L. , Jones Emily J.H. , Cooper Robert J.
Published: July 2024

Infancy is a time of rapid brain development. High-density diffuse optical tomography (HD-DOT) is an optical neuroimaging method that maps changes in cortical haemoglobin concentration, a marker of functional brain activation. Recent years have seen a huge advance in wearable hardware for HD-DOT, however previous headgear has only been capable of sampling specific areas of the cortex. In this work, we aimed to develop headgear capable of sampling across the whole infant scalp surface and to conduct a proof-of-concept demonstration of whole-head HD-DOT in infants aged 5 to 7 months. We developed a whole-head infant implementation of the high-density LUMO design developed by Gowerlabs Ltd. (UK). HD-DOT data were collected from a cohort of infants (N = 16) during the presentation of a screen-based paradigm assessing social processing. Using whole-head HD-DOT, we mapped activity across the entirety of the optically-accessible cortex which far exceeds coverage achieved by previous infant optical neuroimaging methods. We found activity in temporal regions which corroborates previous research. Further, we mapped activity in regions outside those typically sampled in infant research using social processing paradigms, finding activation in regions across the occipital, parietal, and frontal cortices as well as an apparent inverted response in sensorimotor regions. Following this proof-of-concept, we envisage that whole-head HD-DOT will be applied to map the interaction between different regions of the brain, opening new avenues to map activity in the awake infant brain to better understand the trajectory of typical and atypical neurodevelopment.
The effects of musicality on brain network topology in the context of Alzheimer’s disease and memory decline
Authors: Matziorinis Anna Maria , Leemans Alexander , Skouras Stavros , Flo Birthe Kristin , Bashevkin Tobias , Koelsch Stefan
Published: July 2024

Music’s role in modulating brain structure, particularly in neurodegenerative contexts such as Alzheimer’s Disease (AD), has been increasingly recognized. While previous studies have hinted at the potential neuroplastic benefits of musical engagement and training, the mechanisms through which music impacts structural connectivity in neurodegenerative pathways remain underexplored. We aimed to examine the impact of music perception skills, active musical engagement, and musical training on structural connectivity in areas relating to memory, emotion, and learning in individuals with worsening memory impairment, investigating the potential neuroplastic effects of music. Employing diffusion tensor imaging (DTI) based structural connectivity and graph theoretical analysis, we investigated brain topological features in 78 participants aged 42 to 85 with a range of memory impairments. Participants were assessed for musical training, engagement, and perception skills. The study analyzed regional and local network topological metrics to examine the influence of musical activities on graph metrics, while controlling for stages of objective memory impairment (SOMI) and diagnosis, separately. This study aimed to elucidate the effects of musical perception skills, active musical engagement, and musical training on structural connectivity within memory, emotion, and learning-related brain areas in individuals with varying degrees of memory impairment. We found enhanced structural connectivity of the right hippocampus and the right posterior cingulate cortex was associated with stronger local network metrics, such as clustering coefficient and betweenness centrality, with increased music perception skills like melody and beat perception. Musical training specifically impacted the clustering coefficient of the right hippocampus and the node degree of the right mid cingulate gyrus. Active musical engagement influenced the eigenvector centrality of the right hippocampus. Furthermore, musical training was associated with enhanced global metrics, such as global efficiency and characteristic path length. Our study integrates diffusion magnetic resonance imaging (MRI) and graph theoretical analysis to reveal significant effects of musical activities on structural connectivity in key brain regions. The results highlight the potential of musical activities to serve as a non-invasive modulatory tool for cognitive resilience, especially in memory impairment and neurodegeneration contexts. These insights contribute to the understanding of delaying AD onset and aiding early-stage patients through music-based interventions, emphasizing the importance of musical engagement in maintaining cognitive and brain health.
The Development of a Dialogical Pedagogical Agency in Initial Teacher Formation Programs: A Critical Inquiry
Authors: Echeverria Priscilla
Published: July 2024

Initial teacher formation is a permanent focus of attention on the part of research, as the value of education for the progress of society is well known. However, given the naturalization of instrumental criteria as common sense acquired in today’s society, on occasion, initial teacher formation reproduces a technocratic perspective of education, not assisting a transformation into a fairer, ethically healthier, and politically more democratic society. This article is the result of doctoral research that addresses this concern, proposing that initial teacher formation could play a transformative role in society. Considering the Bourdieusian dialectical perspective of agency, as well as elements from critical approach literature, this article particularly focuses on showing some results obtained regarding about the capacity for ethical/political/epistemic pedagogical agency that novice teachers show in their first professional experiences as teachers, discussing how important the development of this capacity is in initial teacher formation programs to prepare teachers to be able to transform education.