Because data authenticity and validity are becoming more and more of a concern in the digital age file security and integrity must be guaranteed. This paper investigates the application of HMAC-SHA256 which combines the Secure Hash Algorithm 256 (SHA256) with a private key for transmission-side source file authentication and verification. The study creates a prototype application to evaluate the efficacy of HMAC-SHA256 in securing file transfers by examining previous investigations on SHA and HMAC. The findings demonstrate that SHA256 produces unique file signatures which successfully guards against unwanted changes. Through the use of cryptographic hashes and secret keys to create distinct digital signatures that guarantee file authenticity HMAC improves security. The study shows that HMAC-SHA256 protects data integrity and detects tampering effectively. It does however stress how crucial it is to comprehend cryptographic concepts and apply these strategies with caution in order to prevent vulnerabilities. Overall the study finds that when properly implemented and updated HMAC-SHA256 greatly enhances file security in the digital age.

Abstract: In order to accelerate deployment of distributed recycling by providing low-cost feed stocks of granulated post-consumer waste plastic, this study analyzes an open source waste plastic granulator system. It is designed, built and tested for its ability to convert post-consumer waste, 3-D printed products and waste into polymer feedstock for recyclebots of fused particle/granule printers. The technical specifications of the device are quantified in terms of power consumption (380 to 404W for PET and PLA, respectively) and particle size distribution. The open source device can be fabricated for less than USD$2000 in materials. The experimentally-measured power use is only a minor contribution to the overall embodied energy of distributed recycling of waste plastic. The resultant plastic particle size distributions were found to be appropriate for use in both recyclebots and direct material extrusion 3-D printers. Simple retrofits are shown to reduce sound levels during operation by 4dB-5dB for the vacuum. These results indicate that the open source waste plastic granulator is an appropriate technology for community, library, makespace, fab lab or small business-based distributed recycling.

In the present work report, the MgAl₂O₄and the Ag/MgAl₂O₄ samples were successfully synthesized by the modified hydrothermal and the isovolumetric impregnation methods, respectively. The structural properties of the prepared samples were systematically characterized by XRD, SEM, TEM, DRS, XPS and et al techniques. The photocatalytic degradation of methylene blue by the Ag/MgAl₂O₄ and MgAl₂O₄ samples was comparatively studied under UV lamp irradiation. The results revealed that the prepared Ag/MgAl₂O₄ (pH=6) samples were the most active among the samples in photocatalytic of methylene blue. Under UV lamp irradiation, the Ag/MgAl₂O₄ (pH=6) photodegradation of methylene blue reached to 89.6% within 120 min. And the Ag/MgAl₂O₄ (pH=6) complex photocatalysts displayed a high photochemical stability under repeated irradiation. Repeated irradiate the Ag/MgAl₂O₄ (pH=6) compound, which indicated it had a high photochemical stability.

River monitoring has the potential to grow substantially with present-day available affordable and locally sourced hardware. Yet river monitoring networks are still under pressure due to lack of resources, difficulties with maintenance, and rapidly changing conditions which in part may be due to climate change. We advocate that to turn around this trend, monitoring stations must rely on local people, work with locally available devices, work without contact with water and operate through openly available knowledge. River observations with camera videos have this potential. IP cameras, drones or smartphones are widely available as observation platforms. The scientific methods are well established in literature. Yet current attempts to establish scalable open-source software solutions that can be operated anywhere are lacking. In fact, currently available software is either research-oriented, more aimed at incidental observations, is restricted to single-use licenses, entirely proprietary, or restricted to operations through a third-party Software as a Service. To overcome this obstacle, we present OpenRiverCam, a free and open-source software ecosystem for river observations that can fulfill a wide variety of use cases and business cases through a well-documented and simple to use Application Programming Interface, service workflows, cloud scalability and interoperability, and options to extend to several applications within the hydrological, hydrodynamic, environmental and geospatial domains. We demonstrate its current technical abilities through three different case studies that all originate from a user perspective. We discuss the future developments to meet further requirements, which include documentation, widely available training materials and embedding in curricula, and further hardware and software developments.

Transportation plays an important role in urban development. Population growth and environmental burden have turned the efforts of cities globally towards smarter and greener mobility. Cooperative and Connected Automated Mobility (CCAM) serves as a concept with the power and potential to help achieve these goals building upon technological fields like Internet of Things, computer vision and distributed computing. However, its implementation is hindered by various challenges covering technical parameters such as performance and reliability in tandem with other issues, such as safety, accountability and trust. To overcome these issues, new distributed and decentralized approaches like blockchain and smart contracts are needed. This paper aims at identifying a comprehensive inventory of CCAM challenges and use it as a framework to describe methodologies using blockchain and smart contracts to address them. It provides a comparative analysis of the findings to draw useful conclusions and discuss future directions in CCAM and relevant blockchain applications. The paper contributes to intelligent transportation systems’ research by offering an integrated view of the difficulties in substantiating CCAM and providing insights on the most prominent blockchain and smart contract technologies that tackle them.

The Software-Defined Networking concept plays an important role in network management. The central controller, which is the main element of SDN, allows to provide traffic engineering and security solutions in single and multiple-layer networks based on optical transmission. In this work, we compare selected open-source implementations of SDN controllers. Throughput and latency measurements were analyzed using the CBench program. The simulation of a link failure and a controller failure were conducted using the API provided by the Mininet network simulator. For detecting security vulnerabilities, a dedicated program, called sdnpwn, was used. The work provides an overview of the selected controllers, indicating their strengths and weaknesses. Moreover, some implemention suggestions and recommendations are presented.

A pivotal strategy in decarbonizing the transport sector is by transitioning from internal combustion engine vehicles (ICEVs) to electric vehicles (EVs), especially if they are charged with renewable energy. To provide an incentive to the common populace to switch to EVs, cities should set up - or enable or even encourage the private sector to do so - electric vehicle charging stations (EVCS) at multiple and suitably accessible locations. This paper aims to present a digitaltwin-enabled methodology study for selecting the most suitable possible locations to establish EVCS with consideration of the low voltage (LV) network operation in terms of power losses, active and reactive power in EV charging demand and the effect of the EVCS on the transformers, based on examples in Newcastle upon Tyne (England, UK). It also evaluates the most suitable type of charger that could be installed at these locations by studying the estimated traffic, cost and impact of the EVCS on the power grid, both at peak and off hours. This paper demonstrates how digitaltwin technologies, such as the web-based tool AutoDesign by Northern Powergrid and EA Technology and open source Pandapower can be used for identifying the most viable and cost-effective locations to connect EVCSs to a Distribution Network Operators (DNO)’s LV network. The results of the analysis indicate that with the installation of the most suitable type of EVCS in a particular location, the local power grid would not be significantly affected at any hour of the day.

Teledermatology, the dermatological consultation and diagnosis via digital communication technologies, has become increasingly important in modern healthcare. The integration of teledermatology into clinical practice has gained significant interest, especially during the COVID-19 pandemic. Numerous studies have shown the effectiveness and reliability of teledermatology, with high levels of patient satisfaction and diagnostic accuracy. Pathpoint® eDerma is a cloud-based dermatology platform that aims to streamline the documentation and management of dermatological conditions. It offers several clinical benefits, including faster diagnosis, reduced unnecessary procedures, improved access to care, and cost savings. The platform follows a comprehensive risk management plan and complies with safety regulations. It undergoes regular recertification and reviews to ensure its safety and effectiveness. The clinical evaluation of eDerma confirms its ability to deliver significant clinical benefits while effectively mitigating risks. The benefit-risk ratio of eDerma is highly acceptable, supporting its use in clinical settings to enhance dermatological care.

Primary Ciliary Dyskinesia (PCD) is a rare genetic disorder characterized by alterations in motile cilia func-tion. The diagnosis of PCD is challenging due to the lack of standardized methods in clinical practice. High-speed video microscopy analysis (HSVA) directly evaluates ciliary beat frequency (CBF) in PCD. Recently, open-source ciliary analysis software applications have shown promise in measuring CBF accurately. How-ever, there is limited knowledge about the performance of different software applications, creating a gap in understanding their comparative effectiveness in measuring CBF in PCD. We compared two open-source software applications, CiliarMove and Cilialyzer, against the manual count method. We used videos rec-orded at high-speed of nasal ciliary brush samples from PCD patients and healthy controls. All three meth-ods showed lower median CBF values in PCD patients than healthy controls. CiliarMove and Cilialyzer identified lower CBF in PCD patients, similar to the manual count. Cilialyzer, CiliarMove and manual count demonstrated statistical significance (p-value < 0.0001) in the difference of median CBF values be-tween PCD and healthy controls. These findings support the utility of open-source software-based analysis tools. Further studies are needed to validate these findings with other genetic variants and identify the op-timal software for accurate CBF measurement in PCD.

Preoperative assessment is crucial in surgical care, traditionally relying on physical examinations and paper-based questionnaires. The emergence of digital tools like Pathpoint® ePOA represents a significant advancement, aiming to enhance the efficiency, accuracy, and standardisation of preoperative evaluations. Pathpoint® ePOA is a cloud-based platform designed to integrate seamlessly with Electronic Health Records (EHRs), providing a comprehensive, data-driven approach to preoperative assessments. It supports improved risk stratification, optimised resource allocation, and enhanced patient engagement through features such as customisable templates and real-time data integration.Current research highlights that digital preoperative tools like ePOA offer notable advantages, including increased clinical capacity, better complexity stratification, and improved patient follow-up. Despite these benefits, gaps remain in comparative studies, detailed clinical outcomes, and patient engagement strategies, indicating areas for further exploration. Pathpoint® ePOA adheres to rigorous safety standards and risk management protocols, ensuring reliability and data security while contributing to improved surgical outcomes. The benefit-risk ratio for ePOA is favourable, underscoring its potential to advance preoperative care by optimising clinical workflows and enhancing patient safety.

Abstract: Development of the fast neutron radiography with higher penetration capability in Non-Destructive Testing (NDT) techniques is rapidly. The detection efficiency and the imaging spatial resolution are the main problem of the radiography detector for many fast neutron imaging systems. In this paper, a detector composed of pixelated EJ200 scintillator array，an 16 × 16 silicon-photomultipliers (SiPM) array, and a capacitive multiplexing network readout electronics is designed. Using Monte-Carlo simulations，the main parameters of the detector was optimization. Then the detector prototype was fabricated and tested at a 14 MeV D-T neutron source. The preliminary test results showed that the prototype has spatial resolution of 1.26 mm. Using pixelated scintillator structure，the conflict between spatial resolution and detect efficiency could improved. Moreover, SiPMs offer a flexibility for the expansion of application field of the imaging system due to their excellent photon detection performance, relatively low price and joint possibility for large area.

The Digital electronics collaborative enhanced learning (DECEL) project has recently developed an international collaborative education course. Its main objective is to enhance the digital electronics skills of international students by working on a complex, multidisciplinary applied problem using a mixed digital architecture. We have developed a logic level synthesis and dedicated software layers on the Red Pitaya FPGA platform. The diversity of digital concepts to be implemented, from hardware description language (HDL) to high-level languages such as Python or Matlab, forced the students to work together and rapidly improve their skills. Their motivation was fueled by the curiosity of controlling an ultrasound probe to obtain ultrasound signatures. This particular physics, little known to the students, was an additional source of curiosity. The goal of forming an image in a liquid medium was an additional motivating factor for them. The students reported that they learned a lot from the experiment. Thus, the technical parts and pedagogical results are documented in this work for reproducibility.

This work introduces a novel facial image capture system that utilizes computer vision technology and artificial intelligence for real-time detecting, tracking, and capturing of human faces. The objective of this study is to address the challenges posed by poor-quality facial images in biometric authentication, especially in passport photo acquisition and recognition. By combining face-aware capture technology with AES encryption for secure image storage, we present a completely open-source hardware solution that consists of a Jetson processor, a 16MP autofocus RGB camera, a custom enclosure, and a touch sensor LCD for user interaction. Pilot data collection demonstrates the system's ability to capture high-quality images, achieving a 98.98% accuracy in storing images of acceptable quality. The integration of AES encryption ensures data security, making the proposed system suitable for real-time applications in other domains beyond identity verification in passport applications, such as security systems, video conferencing, etc

Alternative food sources are essential in both low-resource settings or during emergencies like abrupt sunlight reduction scenarios. Seaweed presents a promising option but requires investigation into the viability of unconventionally sourced ropes for harvesting. As such, a low-cost reliable method to test the tensile strength of rope is needed to validate alternative materials for use in harvesting seaweed. Unfortunately, commercial rope testing jigs alone range in price from several thousand to tens of thousands of dollars. To fill this need, this article reports on an open-source design for tensile strength rope testing hardware. The hardware design focuses on using readily available parts that can be both sourced from a hardware store and manufactured with simple tools to provide for the greatest geographic accessibility. The jig design, which can be fabricated for CAD$20 is two to three orders of magnitude less expensive than commercially available solutions. The jig was built and tested using a case study example investigating denim materials (of 1 5/8”, 3 1/4", 4 7/8”, 6 1/2", and 8 1/8” widths) as a potential alternative rope material for seaweed farming. Denim demonstrated strength up to 1.65kN for the widest sample and the jig demonstrated sufficient strength and stiffness for operating at forces below 4kN. The results are discussed and areas for future improvements are outlined to adapt the device to other circumstances and increase the strength of materials that can be tested.

Solar powering the increasing fleet of electrical vehicles (EV) demands more surface area than may be available for photovoltaic (PV) powered buildings. Parking lot solar canopies can provide the needed area to charge EVs, but are substantially costlier than roof- or ground-mounted PV systems. To provide a lower-cost PV parking lot canopy to supply EV charging beneath them, this study provides a full mechanical and economic analysis on three novel PV canopy systems: (1) exclusively wood, single parking spot spanning system, (2) wood and aluminum double parking spot spanning system, and (3) wood and aluminum cantilevered system for curbside parking. All systems can be scalable to any amount of EV parking spots. The complete designs and bill of materials (BOM) of the canopies are provided along with basic instructions and are released with an open source license that will enable anyone to fabricate them. The results found single-span systems have cost savings of 82%-85%, double-span systems save 43%-50%, and cantilevered systems save 31%-40%. In the first operation year, the PV canopies can provide 157% of energy needed to charge the least efficient EV currently on the market if it is driven the average driving distance in London ON, Canada.

There is an intense need to optimize agrivoltaic systems. This article describes the invention of a new testing system: the parametric open source cold-frame agrivoltaic system (POSCAS). POSCAS is an adapted gardening cold-frame used in cold climates as it acts as a small greenhouse for agricultural production. POSCAS is designed to test partially transparent solar photovoltaic (PV) modules targeting the agrivoltaic market. It can both function as a traditional cold frame, but it can also be automated to function as a full-service greenhouse. The integrated PV module roof can be used to power the controls or it can be attached to a microinverter to produce power. POSCAS can be placed in an experimental array for testing, agricultural and power production. It can be easily adapted for any type of partially transparent PV module. An array of POSCAS systems al-lows for testing agrivoltaic impacts from the percent transparency of the modules by varying the thickness of a thin film PV material or the density of silicon-based cells, and various forms of optical enhancement, anti-reflection coatings and solar light spectral shifting materials in the back sheet. All agrivoltaic variables can be customized to identify ideal PV designs for a given agricultural crop.

This study provides designs for a low-cost, easily replicable open source lab-grade digital scale that can be used as a precision balance. The design is such that it can be manufactured for use in most labs throughout the world with open source RepRap-class material extrusion-based 3-D printers for the mechanical components and readily available open source electronics including the Arduino Nano. Several versions of the design were fabricated and tested for precision and accuracy for a range of load cells. The results showed the open source scale was found to be repeatable within 0.1g with multiple load cells, with even better precision (0.01g) depending on load cell range and style. The scale tracks linearly with proprietary lab-grade scales, meeting the performance specified in the load cell data sheets, indicating that it is accurate across the range of the load cell installed. The smallest loadcell tested(100g) offers precision on the order of a commercial digital mass balance. The scale can be produced at significant cost savings compared to scales of comparable range and precision when serial capability is present. The cost savings increase significantly as the range of the scale increases and are particularly well-suited for resource-constrained medical and scientific facilities.

Centrifuges are commonly required devices in medical diagnostics facilities as well as scientific laboratories. Although there are commercial and open source centrifuges, costs of the former and required electricity to operate the latter, limit accessibility in resource-constrained settings. There is a need for low-cost, human-powered, verified and reliable lab-scale centrifuge. This study provides the designs for a low-cost 100% 3-D printed centrifuge, which can be fabricated on any low-cost RepRap-class fused filament fabrication (FFF) or fused particle fabrication (FPF)-based 3-D printer. In addition, validation procedures are provided using a web camera and free and open source software. This paper provides the complete open source plans including instructions for fabrication and operation for a hand-powered centrifuge. This study successfully tested and validated the instrument, which can be operated anywhere in the world with no electricity inputs obtaining a radial velocity of over 1750rpm and over 50N of relative centrifugal force. Using commercial filament the instrument costs about US$25, which is less than half of all commercially available systems; however, the costs can be dropped further using recycled plastics on open source systems for over 99% savings. The results are discussed in the contexts of resource-constrained medical and scientific facilities.

The advantage of FPGAs lies in the ability to implement a fully hardware solution for interfacing with various input/output (I/O) devices. Each block can work in parallel with all the others, simplifying the satisfaction of timing constraints. However, this hardware utilization consumes FPGA resources that could otherwise be allocated to the primary project. An alternative involves employing a small "soft-core" processor implementing I/O in software. With the goal to design and evaluate a new tiny soft-core processor optimized for FPGA resources in I/O , a novel processor named Baby8 is developed. It is an 8-bit CISC soft-core processor optimized for reduced FPGA resources including program size for 8-bit applications. The number of instructions is not large but any instruction can access arbitrary memory locations. The performance and resource utilization of the newly designed processor are evaluated and compared with a variety of other soft-core processors. The results demonstrate its competitive performance, achieving an average maximum clock frequency of approximately 57 MHz and a power consumption of around 2mW. Furthermore, it conserves nearly half of the FPGA resources in implementation.

This study aimed to identify the most beneficial attitudes adopted by enterprise participants during their engagement in open-source software (OSS) activities. For this purpose, we selected repositories from GitHub, featuring the top 10 with the highest stars and forks, classified the participants according to their sentiment states, and compared their productivity. The results indicated that participants with positive sentiments were more productive than those with negative sentiments. Consequently, it can be inferred that encouraging organizations to express positive sentiments towards their developers publicly may stimulate OSS community activities and enhance productivity, thereby potentially leading to increased open innovation and sustainability.

Historically, the military and non-religious, sub-continent’s intellectual elite Muslim men crafted state ideologies before partition, by actively contributing to sociocultural constructs prevalent to this day, in service of colonial patriarchal concepts. The purpose of this ideological collaboration has been to mould a Pakistani cis-gendered female child primarily into the ideal “Pakistan-Muslim” bride for marriage, carried out through her family and society. This has shaped the lives of cis-gendered female children in Pakistan through coerced, gendered control, implemented as prescriptive societal norms. These norms are rooted in colonial, patriarchal ideologies and are functions of capital and coercion intentionally perpetuated to erase her pluralistic identity, reducing her to a central resource within a family unit. To the military concept of nationalism, her mind and her body symbolize the unification and centralization of a statist ideology. Thus, the military state plays an essential role in shaping her purpose around the concept of nationalism. The intellectual elite, via the state, uphold colonial, patriarchal ideologies, where the primary identity of a cis-gendered female child is actualized through her marriage. The cis-gendered female child’s life is a vehicle to unify the state’s two-fold “Pakistani-Muslim” agenda, by implementing a ‘singular statist narrative’. A narrative that attempts to resolve two major tensions: First, it seeks to wipe out the possibility of a nation connecting with and exploring its own immense, internal ethnocultural diversity. It does this by imposing an imagined “homogenous Muslim” identity — which doesn’t exist — and is instead imported from multiple countries to reinforce a ‘singular statist narrative’, Second, it aims to control the mixing of local, sociocultural narratives by bridging any disjuncture between them by labelling colonial institutional patriarchy concepts as inherently “Pakistani”; in service of its preferred ‘singular statist narrative’.

In the process of sewage coagulation treatment, quartz sand is often used as a heavy medium to accelerate the settling rate of flocs, but it will adversely affect the removal efficiency of pollutants. The factors that affect the coagulation effect and can be controlled manually include the quartz sand dosage, coagulant dosage, sewage pH, stirring time, settling time, etc, their reasonable setting is critical to. This paper was to study the optimal conditions of quartz sand enhanced coagulation(QSEC), first, single-factor tests were conducted to preliminarily explore the optimal range of influencing factors, and then response surface methodology（RSM）tests were performed to accurately determine the optimums of significant factors. The results showed that the addition of quartz sand can’t improve the water quality of coagulation treatment, but it can significantly accelerate the coagulation settlement process, the quartz sand dosage, the coagulant dosage and sewage pH all impacted significantly on its coagulation effect, and existed inflection points. A model that could guide QSEC was obtained by RSM tests. The model optimization and experimental validation showed that the optimal QSEC conditions for treating domestic sewage were as follows: the polyaluminum chloride(PAC) dosage, cationic polyacrylamide(CPAM) dosage, the sewage pH, quartz sand dosage, stirring time and settling time were 0.97 g·L-1, 2.25 mg·L-1, 7.22, 2 g·L-1, 5 minutes and 30 minutes, respectively, and the turbidity of treated sewage was reduced to 1.15 NTU.

In the early 2000s, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) emerged as a performant and relevant tool for identifying micro-organisms. Since then, it has become practically essential for identifying bacteria in microbiological diagnostic laboratories. In the last decade, it was successfully applied for arthropod identification allowing to distinguish vectors from non-vectors of infectious diseases. However, identification failures are not rare, hampering it widely use. Failure is generally attributed either to the absence of respective counter species MS spectra in the database, or to the insufficient quality of query MS spectra (i.e. lower intensity and diversity of MS peaks detected). To avoid matching errors due to non-compliant spectra, the development of a strategy for detecting and excluding outlier MS profiles became compulsory. To this end, we created MSProfileR, an R package leading to a bioinformatics tool through a simple installation, integrating the control quality system of MS spectra and an analysis pipeline including peak detection and MS spectra comparisons. MSProfileR can also add metadata concerning the sample that the spectra are derived from. MSProfileR has been developed in the R environment and offers a user-friendly web interface using the R Shiny framework. It is available on Microsoft Windows as a web browser application by simply navigation using the link of the package on the Github. MSProfileR is therefore accessible to non-computer specialists and is freely available to the scientific community. We evaluated MSProfileR using two datasets including exclusively MS spectra from arthropods. In addition to coherent sample classification, outlier MS spectra were detected in each dataset confirming the value of MSProfileR.

Many middle-aged and older adults (MAOA) do not engage in sufficient physical activity (PA) despite its well-documented benefits for healthy aging. Existing PA interventions often fail to reach or engage the target population effectively. This study investigates MAOA's preferences for recruitment strategies to optimize the reach and uptake of PA interventions, thereby enhancing their impact on healthy aging and public health. Qualitative interviews were conducted with 39 MAOA participants (69% female, mean age = 69.46, SD = 7.07), guided by McGuire's Theory on Persuasive Communication. Factors related to the source, message content, channel, receiver characteristics, and target behavior of recruitment strategies were analyzed. Findings suggest a preference for trustworthy sources (e.g., healthcare professionals over commercial entities) and positive, non-ageist messaging. MAOA vary in channel preferences but emphasize the importance of personalization. Despite heterogeneity, MAOA commonly perceive themselves as sufficiently active, necessitating improving knowledge on what constitutes sufficient PA, and easy enrollment or trying-out interventions. Tailoring recruitment strategies to diverse MAOA segments, based on age, seems crucial for effective engagement. Future research could explore quantitative research into how communication factors relate to various target population characteristics.

As operations in Cislunar space continue to expand, the sustainability of operations in orbital environments beyond GEO has become a critical concern. The Cislunar region is known to have a higher non-linear chaotic component in the dynamics compared to the low-Earth environment. This research is focused on producing simulations to model debris trajectories and dispersion from spacecraft mishaps across various identified key Cislunar orbits. By varying initial conditions, simulations of explosions at different locations of the orbits are carried out and the debris propagation is analyzed. This research emphasizes the creation of a robust debris propagation scheme and the development of a comprehensive database to address the computational costs associated with debris propagation. The resulting codes and databases documenting the historical evolution of debris are published as open-source resources, aiming to aid in solving the Cislunar space debris and traffic problem and in forecasting future needs and policies.

The information society has transformed human life. Technology is almost everywhere, including health and education. For example, years ago, speech and language therapy students required a long time and high-cost equipment to develop healthcare of the auditory and vestibular systems competencies. The high cost of the equipment permitted its practical use only in classes, hindering students’ autonomy in developing those competencies. That situation was a real issue, even more in times of pandemic where online education was essential. This article describes SAEF, an open-source software simulator for autonomously developing procedural audiology therapy competencies, user acceptance, and the validity of experiments and results. SAEF delivers immediate feedback and performance results. Obtained results permit validating students’ and educators’ acceptability of SAEF in audiology therapy education. Obtained results invite authors to continue developing simulator software solutions in other health education contexts. SAEF was developed using open-source technology to facilitate its accessibility, classification, and sustainability.

Vacuum drying can dehydrate materials further than dry heat methods while protecting sensitive materials from thermal degradation. Many industries have shifted to vacuum drying as cost- or time-saving measures. Small-scale vacuum drying, however, has been limited by high costs of specialty scientific tools. To make vacuum drying more accessible, this study provides design and performance information for a small-scale open source vacuum oven, which can be fabricated from off-the-shelf and 3-D printed components. The oven is tested for drying speed and effective-ness on both waste plastic polyethylene terephthalate (PET) and a consortium of bacteria developed for bioprocessing of terephthalate wastes to assist in distributed recycling of PET for both additive manufacturing as well as potential food. Both materials can be damaged when exposed to high temperatures, making vacuum drying a desirable solution. The results showed the open source vacuum oven was effective at drying both plastic and biomaterials, drying at a higher rate than a hot-air dryer for small samples or for low volumes of water. The system can be constructed for less than 20% of commercial vacuum dryer costs for several laboratory-scale applications including dehydration of bio-organisms, drying plastic for distributed recycling and additive manufacturing, and chemical processing.

Open source software such as OpenDSS has given a lot of help to distribution network researchers and educators. With high penetration of distributed renewable energy resources into distribution network, tradition distribution steady state analysis software such as OpenDSS is faced with difficulty in handling distributed generators. Three-phase distributed generators are often modeled in sequence frame while unbalanced distribution network are usually modeled in phase frame. So a load flow in sequence-phase coupled frame is proposed to handle models described in both frames. Voltage controlled DGs which are difficult to cope with in OpenDSS are handled in proposed program. The steady state analysis platform is programmed with open source Modelica language and the main aim of this paper is to introduce an open source platform for active distribution network steady analysis include load flow and short circuit analysis which can be easily adopted and improved by other educators and researchers.

Sleep and stress significantly affect emotions, productivity, and overall well-being, crucial for optimal health and performance. However, limited research examines how Nepalese nurses' quality of life relates to their sleep quality and stress levels. This study aims to assess this relationship among nurses in private hospitals in Kathmandu. Three private hospitals were selected for this cross-sectional analytical study. Eligible nurses were chosen through purposive sampling, and data were analysed using IBM SPSS v25, employing Chi-square tests and logistic regression analysis. Research revealed a high rate of poor sleep quality (83.9%) among individuals with a mean age of 24.33 ± 3.08 years. Initially, significant associations were found with the factors like bachelor's degree, no tobacco use, absence of insomnia, good sleep quality, and low stress with good quality of life. After adjustment, the association with bachelor's degree [AOR:2.025, CI at 95%: 1.021-4.016, p

The complexity of software is increasing day by day due to the increase in the size of the projects being developed. For better planning and management of large software projects, estimation of software quality is important. During the development processes, complexity metrics are used for the indication of the attributes/characteristics of the quality software. There are many studies about the effect of the complexity of the software on the cost and quality. In this study, we discussed the effects of software complexity on the quality attributes of the software for open source and closed source software. Though, the quality metrics for open and closed source software are not distinct from each other. In this paper, we comparatively analyzed the impact of complexity metrics on open source and private software. We also presented various models for the management of the project complexity such as William’s Model, Stacey’s Agreement and Certainty matrix, Kahane’s Approach and UCP Model. Quality metrics here refer to the standards for the measurement of the quality of software which contains certain attributes or characteristics of the software that are related to the quality of the software. Certain quality attributes addressed in this study are Usability, Reliability, Security, Portability, Maintainability, Efficiency, Cost, Standards and Availability, etc. Both Open source and Closed source software are evaluated on the basis of these quality attributes. This study also recommended future approaches to manage the quality of project Open source and Closed source software and specify which one of them is mostly used in the industry.

Industrial pilot projects often rely on proprietary and expensive electronic hardware to control and monitor experiments. This raises costs and retards innovation. Open-source hardware tools exist for implementing these processes individually, however, they are not easily integrated with other designs. The Broadly Reconfigurable and Expandable Automation Device (BREAD) framework provides many open-source devices which can be connected to create more complex data acquisition and control systems. This article explores the feasibility of using BREAD plug-and-play open hardware to quickly design and test monitoring and control electronics for an industrial materials processing prototype pyrolysis reactor. Generally, pilot-scale pyrolysis plants are expensive custom designed systems. The plug-and-play prototype approach is first tested by connecting it to the pyrolysis reactor and ensuring it can measure temperature and actuate heaters and a stirring motor. Next, a single circuit board system was created and tested using the designs from the BREAD prototype to reduce the number of microcontrollers required. Both open-source control systems were capable of reliably running the pyrolysis reactor continuously and the overall cost of control was reduced by more than 10X. Open-source, plug-and-play hardware provides a reliable avenue for researchers to quickly develop data acquisition and control electronics for industrial-scale experiments.

A crucial component for developing an automated speaker or speech recognition system is voice preprocessing, which filters unwanted noise and detects the speech part. This study aimed to develop a computerized model to remove background noise and improve signal quality for future applications. This model was developed on a large longitudinal dataset containing varying real-world noise and validated on both a public dataset and a locally collected test dataset in different environments. An overall voice pre-processing pipeline is presented in this study, including denoising, segmentation, feature extraction, and ease of storage. The backbone of the denoising model is a Kalman filter, where the parameters were obtained from a grid search method; the signal-to-noise ratio (SNR) was used as the performance metric. Also, the segmentation was done to remove the pauses from the audio signal before the feature extraction. Finally, the data was stored as a template with the most common features. The SNR result suggested that the Kalman filter-based proposed method performed successfully across diverse datasets. Thus, this model provides a robust and adaptable solution for real-world scenarios and also ensures the data storing quality for future applications.

This study describes the development of an automated bag valve mask (BVM) compression system, which, during acute shortages and supply chain disruptions can serve as a temporary emergency ventilator. The resuscitation system is based on the Arduino controller with a real-time operating system installed on a largely RepRap 3-D printable parametric component-based structure. The cost of the system is under $170, which makes it affordable for replication by makers around the world. The device provides a controlled breathing mode with tidal volumes from 100 to 800 milliliters, breathing rates from 5 to 40 breaths/minute, and inspiratory-to-expiratory ratio from 1:1 to 1:4. The system is designed for reliability and scalability of measurement circuits through the use of the serial peripheral interface and has the ability to connect additional hardware due to the object-oriented algorithmic approach. Experimental results demonstrate repeatability and accuracy exceeding human capabilities in BVM-based manual ventilation. Future work is necessary to further develop and test the system to make it acceptable for deployment outside of emergencies in clinical environments, however, the nature of the design is such that desired features are relatively easy to add with the test using protocols and parametric design files provided.

Distributed digital manufacturing offers a solution to medical supply and technology shortages during pandemics. To prepare for the next pandemic, this study reviews the state-of-the-art for open hardware designs needed in a COVID-19-like pandemic. It evaluates the readiness of the top twenty technologies requested by the Government of India. The results show that the majority of the actual medical products have had some open source development, however, only 15% of the supporting technologies that make the open source device possible are freely available. The results show there is still considerable work needed to provide open source paths for the development of all the medical hardware needed during pandemics. Five core areas of future work are discussed that include: i) technical development of a wide-range of open source solutions for all medical supplies and devices, ii) policies that protect the productivity of laboratories, makerspaces and fabrication facilities during a pandemic, as well as iii) streamlining the regulatory process, iv) developing Good-Samaritan laws to protect makers and designers of open medical hardware, as well as to compel those with knowledge that will save lives to share it, and v) requiring all citizen-funded research to be released with free and open source licenses.

Open Inertia Modelling (OpInMod) is a modelling framework designed to create unit commitment and economic inertia dispatch optimisation problems. Present energy system modelling generators do not consider power system inertia in unit commitment and economic dispatch modelling to assess future energy system pathways. However, maintaining sufficient power system inertia in power systems is the foundation for power frequency controllability. The work at hand describes the functionality and approaches of open source tool OpInMod. The softwares universal design approach increases reuse potential. OpInMod is distributed with a set of examples to test and understand OpInMod

We introduce PyNTA, a modular instrumentation software for live particle tracking. By using the multiprocessing library of Python and the distributed messaging library pyZMQ, PyNTA allows users to acquire images from a camera at close to maximum readout bandwidth while simultaneously performing computations on each image on a separate processing unit. This publisher/subscriber pattern generates a small overhead and leverages the multi-core capabilities of modern computers. We demonstrate capabilities of the PyNTA package on the featured application of nanoparticle tracking analysis. Real-time particle tracking on megapixel images at a rate of 50 Hz is presented. Reliable live tracking reduces the required storage capacity for particle tracking measurements by a factor of approximately 10³, as compared with raw data storage, allowing for a virtually unlimited duration of measurements

One of the most important pieces of equipment used in labs in culturing populations of fruit flies (Drosophila sp.) is that of the “CO₂ gas plate”, which is used to anesthesize individuals during “fly-pushing”. This piece of equipment consists of a box with a porous top into which carbon-dioxide is pumped. Flies placed on its surface are left immobilized, permitting the sorting, categorizing and/or counting of flies during population culturing and experimental assays. Unfortunately, commercially available gas plates are typically expensive. Here, we describe a new design for a gas plate that can be easily produced using a 3D printer and a laser cutter, which we are making freely available to the fly community.

This paper describes the proposal and development of a proof of concept (PoC) for a data logger system designed for operation and fault detection in bench testing of combustion engines. The main objective was to develop a data logger system that collects data on vibration, sound, temperature, and CO2 levels to identify ignition and combustion faults, thereby contributing to reducing greenhouse gas emissions (GHG). The paper presents (i) the proposal and development and (ii) the open-source code: proof of concept for a data logger system focused on detecting faults and monitoring the operational condition of benchtop combustion engines. The results indicate the feasibility of the PoC for data acquisition and dataset creation for Research and Development purposes.

Distance Learning has become the new standard, especially after the pandemic and due to the technological advances, that are incorporated into the teaching procedure. At the same time, the augmented use of the internet has blurred the borders between distance and conventional learning. Students interact mainly through LMSs, leaving their digital traces that can be leveraged to improve the educational process. This work aims to propose a model that can capture the students' behaviors based on the clickstream data associated with the discussion forum and additionally to suggest interpretable patterns that will support education administrators and tutors in the decision-making process. To achieve our goal, we use Social Network Analysis (SNA) as networks represent complex interactions in a meaningful and easily interpretable way. Moreover, simple or complex network metrics are becoming available to provide valuable insights into the students’ social interaction. This study concludes that by leveraging the imprint of these actions in an LMS and using metrics of SNA, differences can be spotted in the communicational patterns that go beyond simple participation recording. Although HITS and PageRank algorithms were created with completely different targeting, it is shown that they can also reveal methodological features in students’ communicational approach.

To improve accessibility, this article describes a static, four-legged, walker that can be constructed from materials and fasteners commonly available from hardware stores coupled by open-source 3-D printed joints. The designs are described in detail, shared under an open-source license, and fabricated with a low-cost open-source desktop 3-D printer and hand tools. The resulting device is loaded to failure to determine the maximum load that the design can safely support in both vertical and horizontal failure modes. The experimental results showed the average vertical failure load capacity was 3680±694.3N, equivalent to 375.3±70.8kg of applied weight with the fractured location at the wood dowel handlebars. The average horizontal load capacity was 315.6±49.4N, equivalent to 32.2±5.1kg. The maximum weight capacity of a user of 187.1±29.3kg was obtained, which indicates the open-source walker design can withstand the weight requirements of all genders with a 95% confidence interval that includes a safety factor of 1.8 when considering the lowest deviation weight capacity. The design has a cost at the bottom of the range of commercial walkers and reduces the mass compared to a commercial walker by 0.5kg (19% reduction). It can be concluded that this open-source walker design can aid accessibility in low-resource settings.

Large datasets that enable researchers to perform investigations with unprecedented rigor are growing increasingly common in neuroimaging. Due to the simultaneous increasing popularity of open science, these state-of-the-art datasets are more accessible than ever to researchers around the world. While analysis of these samples has pushed the field forward, they pose a new set of challenges that might cause difficulties for novice users. Here, we offer practical tips for working with large datasets from the end-user’s perspective. We cover all aspects of the data life cycle: from what to consider when downloading and storing the data, to tips on how to become acquainted with a dataset one did not collect, to what to share when communicating results. This manuscript serves as a practical guide one can use when working with large neuroimaging datasets, thus dissolving barriers to scientific discovery.

The proliferation of physiological sensors opens new opportunities to explore interactions, conduct experiments and evaluate the user experience with continuous monitoring of bodily functions. Commercial devices, however, can be costly or limit access to raw waveform data, while low-cost sensors are efforts-intensive to setup. To address these challenges, we introduce PhysioKit, an open-source, low-cost physiological computing toolkit. PhysioKit consists of (i) a sensor and hardware layer that can be configured in a modular manner per research needs, (ii) a software application layer that enables data acquisition, real-time visualization and machine learning (ML)-enabled signal quality assessment. This also supports basic visual biofeedback configurations and synchronized acquisition for co-located or remote multi-user settings. In a validation study for photo-plethysmography (PPG) sensor with 15 participants, PhysioKit shows strong agreement with research-grade PPG sensors. Furthermore, we report usability survey results from 10 micro-project teams (44 individual members in total) who use PhysioKit for 4-6 weeks, providing insights into its use cases and research benefits. We conclude by discussing extensibility and potential impact of the toolkit on the research community.

Understanding the detailed timing of crop phenology and their variability enhances grain yield and quality by providing precise scheduling of irrigation, fertilization, and crop protection mechanisms. Advances in information and communication technology (ICT) provide a unique opportunity to develop agriculture-related tools that enhance wall-to-wall upscaling of data outputs from point-location data to wide-area spatial scales. Because of the heterogeneity of the worldwide agro-ecological zones where crops are cultivated, it is unproductive to perform plant phenology research without providing means to upscale results to landscape-level while safeguarding field-scale relevance. This paper presents an advanced, reproducible, and open-source software for plant phenology prediction and mapping (PPMaP) that inputs data obtained from multi-location field experiments to derive models for any crop variety. This information can then be applied consecutively at a localized grid within a spatial framework to produce plant phenology predictions at the landscape level. This software supports the development of process-oriented and temperature-driven plant phenology models by intuitively and interactively leading the user through a step-by-step progression to the production of spatial maps for any region of interest. Maize (Zea mays L.) was used to demonstrate the robustness, versatility, and high computing efficiency of the resulting modeling outputs of the PPMaP. The framework is implemented in R, providing a flexible and easy‐to‐use GUI interface. Since this allows appropriate scaling to the larger spatial domain, the software can effectively be used to determine the spatially explicit length of growing period (LGP) of any variety.

In this article, many experimental similarities between electromagnetic fields (which are applied in systems of electrons, atoms, and liquids) and strong interaction fields (which are applied in systems of quarks, nucleons, and nuclei) are reviewed. The currently accepted theories describing electromagnetic fields differ fundamentally from those describing strong fields. Therefore, the many similarities are quite surprising, and some are not adequately explained even today. Several such unexplained similarities are listed among the top open problems in particle physics, such as the “EMC effect,” the “proton spin crisis,” and the “strong CP problem.” This paper highlights, for the first time, the underlying common characteristics of these problems, potentially offering valuable contribution to future explanations.

The rapidly evolving field of artificial intelligence (AI) continues to witness the introduction of innovative open-source pre-trained models, fostering advancements in various applications. One such model is Llama 2, an open-source pre-trained model released by Meta, which has garnered significant attention among early adopters. In addition to exploring the foundational elements of the Llama v2 model, this paper investigates how these early adopters leverage the capabilities of Llama 2 in their AI projects. Through a qualitative study, we delve into the perspectives, experiences, and strategies employed by early adopters to leverage Llama 2's capabilities. For the purpose of data analysis, the capabilities inherent in the Llama 2 model were employed to conduct keyword extraction from the context of the early adopters' case studies. The findings shed light on the model's strengths, weaknesses, and areas of improvement, offering valuable insights for the AI community and Meta to enhance future model iterations. Additionally, we discuss the implications of Llama 2's adoption on the broader open-source AI landscape, addressing challenges and opportunities for developers and researchers in the pursuit of cutting-edge AI solutions. The present study constitutes an early exploration of the Llama 2 pre-trained model, holding promise as a foundational basis for forthcoming research investigations.

This paper describes the use of an open source instrument called LANcube v2 to build a lighting device inventory. The LANcube v2 is and instrument having 5 color sensitive sensors, each on a face of a cube. The instrument can be mounted on a car roof in order to create a map of the artificial light at night while roaming the streets and roads. Based on the temporal variations of the detected signal on various cube’s faces, we developed a method of finding the position in 3D of each lighting device. The lamp spectral types can be determined thanks to the color balance of the raw Red (R) Green (G) Blue (B) and Clear (C) color bands. If one assumes a typical angular photometry of a lighting device with respect to its location, it is possible to estimate its luminous flux. Such information allows us to build a lighting devices inventory of a territory. One advantage of that new method is that it can provide information about the private lighting devices that are always excluded from public lighting inventories. We will compare the inventory extracted with that new methodology with an in situ lamp inventory made for two villages in Canada. This will allow us to emphasize the strengths and limitations of the method by comparing to the ground truth.

Three-dimensional (3D) bioprinting promises to be essential in tissue engineering for solving the rising demand for organs and tissues. Some bioprinters are commercially available, but their impact on the field of TE is still limited due to their cost or difficulty to tune. Herein, we present a low-cost easy-to-build printhead for microextrusion-based bioprinting (MEBB) that can be installed in many desktop 3D printers to transform them into 3D bioprinters. We can extrude bioinks with precise control of print temperature between 2 - 60 ºC. We validated the versatility of the printhead, by assembling it in three low-cost open-source desktop 3D printers. Multiple units of the printhead can also be easily put together in a single printer carriage for building a multi-material 3D bioprinter. Print resolution was evaluated by creating representative calibration models at different temperatures using natural hydrogels such as gelatin and alginate, and synthetic ones like poloxamer. Using one of the three modified low-cost 3D printers, we successfully printed cell-laden lattice constructs with cell viabilities higher than 90% after 24h post printing. Controlling temperature and pressure according to the rheological properties of the bioinks was essential in achieving optimal printability and great cell viability. The cost per unit of our device, which can be used with syringes of different volume, is less expensive than any other commercially available product. These data demonstrate an affordable open-source printhead with the potential to become a reliable alternative to commercial bioprinters for any laboratory.

Nineteen million Americans have significant vision loss. Over 70% of these are not employed full-time, and more than a quarter live below the poverty line. Globally, there are 36 million blind people, but less than half use white canes or more costly commercial sensory substitutions. The quality of life for visually impaired people is hampered by the resultant lack of independence. To help alleviate these challenges this study reports on the development of a low-cost (<$24), open-source navigational support system to allow people with the lost vision to navigate, orient themselves in their surroundings and avoid obstacles when moving. The system can be largely made with digitally distributed manufacturing using low-cost 3-D printing/milling. It conveys point-distance information by utilizing the natural active sensing approach and modulates measurements into haptic feedback with various vibration patterns within the distance range of 3 m. The developed system allows people with lost vision to solve the primary tasks of navigation, orientation, and obstacle detection (>20 cm stationary, moving up to 0.5 m/s) to ensure their safety and mobility. Sighted blindfolded participants successfully demonstrated the device for eight primary everyday navigation and guidance tasks including indoor and outdoor navigation and avoiding collisions with other pedestrians.

The urbanisation phenomenon and related cities expansion and transport networks entail preventing the increase of population exposed to environmental pollution. Regarding noise exposure, the Environmental Noise Directive demands on main metropolis to produce noise maps. While based on standard methods, these latter are usually generated by proprietary software and require numerous input data concerning, for example, the buildings, land use, transportation network and traffic. The present work describes an open source implementation of a noise mapping tool fully implemented in a Geographic Information System compliant with the Open Geospatial Consortium standards. This integration makes easier at once the formatting and harvesting of noise model input data, cartographic rendering and output data linkage with population data. An application is given for a French city, which consists in estimating the impact of road traffic-related scenarios in terms of population exposure to noise levels both in relation to a threshold value and level classes.

Thermal sterilization is generally avoided for 3-D printed components because of the relatively low deformation temperatures for common thermoplastics used for material extrusion-based additive manufacturing. 3-D printing materials required for high-temperature heat sterilizable components for COVID-19 and other applications demands 3-D printers with heated beds, hot ends that can reach higher temperatures than polytetrafluoroethylene (PTFE) hot ends and heated chambers to avoid part warping and delamination. There are several high temperature printers on the market, but their high costs make them inaccessible for full home-based distributed manufacturing required during pandemic lockdowns. To allow for all these requirements to be met for under $1,000, the Cerberus – an open source three-headed self-replicating rapid prototyper (RepRap) was designed and tested with the following capabilities: i) 200^oC-capable heated bed, ii) 500^oC-capabel hot end, iii) isolated heated chamber with 1kW space heater core and iv) mains voltage chamber and bed heating for rapid start. The Cereberus successfully prints polyetherketoneketone (PEKK) and polyetherimide (PEI, ULTEM) with tensile strengths of 77.5 and 80.5 MPa, respectively. As a case study, open source face masks were 3-D printed in PEKK and shown not to warp upon widely home-accessible oven-based sterilization.

The experience of ego dissolution and self-transcendence induced by psychedelic substances offers a profound challenge to our conventional understanding of the self and our relationship with the natural world. This paper delves into the philosophical underpinnings and implications of this phenomenon, exploring how the temporary breakdown of ego boundaries during a psychedelic experience may foster a sense of profound interconnectedness with nature. Drawing from Western and Eastern philosophical traditions, as well as recent insights from neuroscience and consciousness studies, we examine the potential of psychedelic-induced self-transcendence to catalyze a shift in our perspectives on the human-nature relationship. The paper investigates the philosophical implications of this experience, including its resonance with deep ecological philosophies and its potential to inspire more ecocentric ethical frameworks. Furthermore, we explore the possible practical implications of fostering a sense of ecological connectedness through psychedelics, such as promoting environmentally sustainable behaviors and addressing the pressing challenges of climate change and ecological degradation. Ultimately, this exploration highlights the value of engaging with altered states of consciousness as a means to reconsider our place within the intricate web of life on Earth.

OpenToolFlux is an open-source software to estimate soil gas fluxes from gas concentration time-series data generated by automatic chamber systems. This paper describes the physical equipment used as well as software design and workflow. The software is a command-line application that imports tabular time-series data from the analyzer following the instructions specified in a configuration file by the user, performs configurable data-cleaning operations, and outputs a data file with volumetric flux estimates as well as diagnostic plots. The software can be configured according to the specifics of physical equipment and experimental setup and is therefore applicable in a wide range of studies.

Commonly, professors, students and researchers from universities around the world use software distributed under a license agreement for computer simulation purposes, which requires a computer with considerable hardware capabilities. Consequently, this implies a high cost to conduct simulations that require implementing numerical methods in all areas of engineering, particularly in the field of robotics and nonlinear control. This paper presents the design and results analysis of a low-cost and open-source frugal computer simulation tool with applications to robotic nonlinear control, for instance, for numerical simulations of manipulator robot control based on dynamic models. Using a single board minicomputer with with reduced computing power, Raspberry Pi, together with free software, GNU-Octave, trajectory tracking control simulations in the joint space of a Selective Conformal Assembly Robot Arm (SCARA) are achieved by solving a system of nonlinear differential equations, represented in matrix form, which includes the control law and the system model. The results of the proposed alternative are compared by running the same simulation code on a laptop computer using MATLAB and GNU Octave, which show minimal deviations and reasonable time complexity. Moreover, considering the frugality curve calculated for this approach, in addition to the low acquisition cost of the simulation software tool, it would allow the creation of a simulation laboratory in some universities with budgetary constraints for educational and research purposes.

DARPA, the Defense Advanced Research Projects Agency from the United States, has started the Spectrum Collaboration Challenge with the aim to encourage research and development of coexistence and collaboration techniques of heterogeneous networks in the same wireless spectrum bands. Team SCATTER has been participating in the challenge since its beginning, back in 2016. SCATTER’s open-source software-defined physical layer (SCATTER PHY) has been developed as a standalone application, with the ability to communicate with higher layers of SCATTER’s system via ZeroMQ, and uses USRP X310 software-defined radio devices to send and receive wireless signals. SCATTER PHY relies on USRP’s ability to schedule timed commands, uses both physical interfaces of the radio devices, utilizes the radio’s internal FPGA board to implement custom high-performance filtering blocks in order to increase its spectral efficiency as well as enable reliable usage of neighboring spectrum bands. This paper describes the design and main features of SCATTER PHY and showcases the experiments performed to verify the achieved benefits.

Barriers to inventing electronic devices involve challenges of iterating electronic designs due to long lead times for professional circuit board milling or high-costs of commercial milling machines. To overcome these barriers this study provides open source (OS) designs for a low-cost circuit milling machine. First, design modifications for mechanical and electrical sub-systems of the OS D3D Robotics prototyping system are provided. Next, Copper Carve, an OS custom graphical user interface, is developed to enable circuit board milling by implementing backlash and substrate distortion compensation. The performance of the OS D3D circuit mill is then quantified and validated for: positional accuracy, cut quality, feature accuracy and distortion compensation. Finally, the return on investment is calculated for inventors using it. The results show by properly compensating for motion inaccuracies with Copper Carve, the machine achieves a motion resolution of 10 microns, which is more than adequate for most circuit designs. The mill is at least five times less expensive than all commercial alternatives and the material costs of the D3D mill are repaid from fabricating 20-43 boards. The results show that the OS circuit mill is of high-enough quality to enable rapid invention and distributed manufacturing of complex products containing custom electronics.

Untargeted metabolomics is a powerful tool for measuring and understanding complex biological chemistries. However, employment, bioinformatics and downstream analysis of mass spectrometry (MS) data can be daunting for inexperienced users. Numerous open-source and free-to-use data processing and analysis tools exist for various untargeted MS approaches, including liquid chro-matography (LC), but choosing the ‘correct’ pipeline isn’t straight-forward. This tutorial, in con-junction with a user-friendly online guide presents a workflow for connecting these tools to process, analyse and annotate various untargeted MS datasets. The workflow is intended to guide explor-atory analysis in order to inform decision-making regarding costly and time-consuming down-stream targeted MS approaches. We provide practical advice concerning experimental design, organisation of data and downstream analysis, and offer details on sharing and storing valuable MS data for posterity. The workflow is editable and modular, allowing flexibility for updated/ changing methodologies and increased clarity and detail as user participation becomes more common. Hence, the authors welcome contributions and improvements to the workflow via the online repository. We believe that this workflow will streamline and condense complex mass-spectrometry approaches into easier, more manageable, analyses thereby generating opportunities for researchers previously discouraged by inaccessible and overly complicated software.

There are important challenges for modeling large electrical distribution circuits, even more with the presence of distributed renewable generation. Constructing simulations for assessing the effect of the penetration of distributed generation on electrical distribution networks has become of great importance for Distribution Network Operators (DNOs). This paper proposes a simulation strategy based on open-source platforms and the integration of scripting tools for the rapid modeling of large-scale electrical distribution circuits with distributed renewable generation. The implementation is based on the adaptation of a tool called QGIS2OpenDSS, which creates OpenDSS distribution network models directly from an open-source geographic information system, QGIS. The plugin’s capabilities are demonstrated using a real distribution feeder with more than 60% penetration of renewable generation based on photovoltaic systems. These simulations are carried out using real data from a circuit provided by a DNO in the Dominican Republic, which is used to demonstrate how this approach provides a more accessible and flexible way to simulate and assess the effect of Distributed Energy Resources (DERs) in Medium Voltage (MV) and Low Voltage (LV) networks, enabling utilities to evaluate system performance and identify potential issues.

We introduce Get Free Copy (getfreecopy.com), a web-based platform designed to streamline the search for biomedical literature across major repositories like arXiv, bioRxiv, medRxiv, and PubMed Central (PMC). Addressing challenges posed by paywalls and fragmented databases, it offers a unified interface for efficient retrieval of free, legitimate copies of biomedical literature. The platform's implementation involves a Node.js backend and dynamic front-end display, enhancing accessibility and research efficiency. As an open-source project, Get Free Copy represents a significant contribution to the open-access movement, inviting global researcher collaboration for further development.

Although solar photovoltaic (PV) system costs have declined, capital cost remains a barrier to widespread adoption. Do-it-yourself (DIY) system designs can decrease costs by about 50% by reducing labor costs, but if not attached to a building structure demand ground penetration for conventional footings. This is not technically and economically feasible at all sites. To overcome these challenges, this study details systems designed to eliminate drilling holes and pouring concrete. Two different designs for both fixed tilt and variable tilt PV racking are investigated to assess their structural integrity, constructability, and economic cost when fabricated with a ballast-supported foundation. The ballast-supported foundations are analyzed for eight such systems by proposing two separate ballast designs: one for single line of post systems, and one for double line of post systems built on a 4-kW basis. The results of the analysis found that both designs are slightly more expensive than typical in-ground concrete systems by 25%, but the overall DIY systems costs remain economically advantageous. Sensitivity analyses are conducted to show how modifications to the dimensions including clearances and distances between gabions influence the weight of the system and thus change the economic value of the design, so users can trade dimensional freedom for cost-savings, and vice versa. Overall, all the wood-based PV racking system designs provide users with cost-effective and easy DIY alternatives to conventional metal racking, and the novel ballast systems presented provide more versatility for PV systems installations.

Optical Character Recognition (OCR) on historical printings is a challenging task mainly due to the complexity of the layout and the highly variant typography. Nevertheless, in the last few years great progress has been made in the area of historical OCR, resulting in several powerful open-source tools for preprocessing, layout recognition and segmentation, character recognition and post-processing. The drawback of these tools often is their limited applicability by non-technical users like humanist scholars and in particular the combined use of several tools in a workflow. In this paper we present an open-source OCR software called OCR4all, which combines state-of-the-art OCR components and continuous model training into a comprehensive workflow. A comfortable GUI allows error corrections not only in the final output, but already in early stages to minimize error propagations. Further on, extensive configuration capabilities are provided to set the degree of automation of the workflow and to make adaptations to the carefully selected default parameters for specific printings, if necessary. Experiments showed that users with minimal or no experience were able to capture the text of even the earliest printed books with manageable effort and great quality, achieving excellent character error rates (CERs) below 0.5%. The fully automated application on 19th century novels showed that OCR4all can considerably outperform the commercial state-of-the-art tool ABBYY Finereader on moderate layouts if suitably pretrained mixed OCR models are available. The architecture of OCR4all allows the easy integration (or substitution) of newly developed tools for its main components by standardized interfaces like PageXML, thus aiming at continual higher automation for historical printings.

Agricultural production needs technologies that assist the management of natural resources, for example, the collection of real-time data on soil, water, weather, crops, and biodiversity conditions. Sensor technology solutions and open-source software are appropriate for promoting more sustainable agricultural production. Among the advantages of using open-source technologies and software is its potential for extension, collaboration, customization, flexibility, maintenance cost, transparency, speed, and better security. Given the above, the objective of this research was to find, in different electronic databases, exclusively open-source software for precision agriculture, offering a systematic review, and addressing considerations and challenges. This survey considers up-to-date open-source software available in repositories such as GitHub and GitLab, to understand its characteristics and application formats.

We present a generic and open-source framework for the numerical modeling of the expected transport and storage mechanisms in unconventional gas reservoirs. These unconventional reservoirs typically contain natural fractures at multiple scales. Considering the importance of these fractures in shale gas production, we perform a rigorous study on the accuracy of different fracture models. The framework is validated against an industrial simulator and is used to perform a history-matching study on the Barnett shale. This work presents an open-source code that leverages cutting-edge numerical modeling capabilities like automatic differentiation, stochastic fracture modeling, multi-continuum modeling and other explicit and discrete fracture models. We modified the conventional mass balance equation to account for the physical mechanisms that are unique to organic-rich source rocks. Some of these include the use of an adsorption isotherm, a dynamic permeability-correction function, and an embedded discrete fracture model (EDFM) with fracture-well connectivity. We explore the accuracy of the EDFM for modeling hydraulically-fractured shale-gas wells, which could be connected to natural fractures of finite or infinite conductivity, and could deform during production. Simulation results indicates that although the EDFM provides a computationally efficient model for describing flow in natural and hydraulic fractures, it could be inaccurate under these three conditions: 1. when the fracture conductivity is very low. 2. when the fractures are not orthogonal to the underlying Cartesian grid blocks, and 3. when sharp pressure drops occur in large grid blocks with insufficient mesh refinement. Each of these results are very significant considering that most of the fluids in these ultra-low matrix permeability reservoirs get produced through the interconnected natural fractures, which are expected to have very low fracture conductivities. We also expect sharp pressure drops near the fractures in these shale gas reservoirs, and it is very unrealistic to expect the hydraulic fractures or complex fracture networks to be orthogonal to any structured grid. In conclusion, this paper presents an open-source numerical framework to facilitate the modeling of the expected physical mechanisms in shale-gas reservoirs. The code was validated against published results and a commercial simulator. We also performed a history-matching study on a naturally-fractured Barnett shale-gas well considering adsorption, gas slippage & diffusion and fracture closure as well as proppant embedment, using the framework presented. This work provides the first open-source code that can be used to facilitate the modeling and optimization of fractured shale-gas reservoirs. To provide the numerical flexibility to accurately model stochastic natural fractures that are connected to hydraulically-fractured wells, it is built atop other related open-source codes. We also present the first rigorous study on the accuracy of using EDFM to model both hydraulic fractures and natural fractures that may or may not be interconnected.

The way people innovate and create new ideas and bring them to the market is undergoing a fundamental change from closed innovation to open innovation. Why and how do firms perform open innovation? Firms’ open innovation is measured through the levels of firms’ joint patent applications. Next, we analyze network structures and characters of firms’ joint patent applications such as betweenness and degree centrality, structure hole, and closure. From this research, we drew conclusions as follows. First, the structure of collaboration networks has both direct and indirect effects on firms’ innovative performance. Second, in the process of joint patent applications, there is a long tail phenomenon in networks of joint patent applications. Third, the number of patents and International Patent Classification (IPC) subclasses together constitute a meaningful measure of the innovation performance of firms.

Quantum theory predicts violations of Bell’s inequality. This implies a contradiction with at least one of three statistical conditions, known as “Realism” (joint distribution of relevant observables), “Locality” (conditional separability of pairwise observations, given a set of hidden variables), and “Free Will” (statistical independence between hidden variables and measurement settings). Here we describe a classical system with “clockwork” properties that is unquestionably local. It produces maximal violations of the Clauser-Horne-Shimony-Holt (CHSH) inequality. It contradicts every one of the three listed formal conditions. Nonetheless, it expresses the qualitative markers of ontological Realism, ontological Locality, and ontological Free Will, all at the same time. In other words, the three listed conditions do not correspond to the three ontological concepts with the same names. Therefore, there is no conflict between quantum theory and Local Realism.

Atta capiguara is a grass-cutting ant species frequently found in Cerrado biome. However, little is known about the giant nest architecture of this ant. In this study, we investigated the architecture of three A. capiguara nests from the fragment of cerrado in Botucatu, São Paulo, Brazil. Casts were made of the nests by filling them with cement to permit better visualization of internal structures such as chambers and tunnels. After excavation, the depth and dimensions (length, width, and height) of the chambers were measured. The results showed the typical shape of Atta capiguara nests consisting of mounds of loose soil with unique features resembling a conic section. The fungus chambers were found outside the apparent main part of the nest and were spaced apart and distributed laterally at ground level. The waste chambers were located beneath the largest mound of loose soil. Both the fungus and waste chambers exhibited a sectoral distribution. Our study contributes to a better understanding of the so far unknown nest architecture of the grass-cutting ant A. capiguara.

Exposure of experimental rodents to controlled cycles of light, food, and temperature is important when investigating alterations in circadian cycles that profoundly influence health and disease. However, applying such stimuli simultaneously is difficult in practice. Our aim was to design, build, test, and open-source describe a simple device that subjects a conventional mouse cage to independent cycles of physiologically relevant environmental variables. The device is based on a box enclosing the rodent cage to modify the light, feeding, and temperature environments. The device provides temperature-controlled air conditioning (heating or cooling) by a Peltier module and includes programmable feeding and illumination. All functions are set by a user-friendly front panel for independent cycle programming. Bench testing with a model simulating the CO2 production of mice in the cage showed: a) suitable air renewal (by measuring actual ambient CO2), b) controlled realistic illumination at the mouse enclosure (measured by a photometer), c) stable temperature control, and d) correct cycling of light, feeding, and temperature. The cost of all the supplies (retail purchased by e-commerce) was &lt; 300 US$). Detailed technical information is open-source provided, allowing for any user to reliably reproduce or modify the device. This approach can considerably facilitate circadian research since using one of the described low-cost devices for any mouse group with a given light-food-temperature paradigm allows for all the experiments to be performed simultaneously, thereby requiring no changes in the light/temperature of a general-use laboratory.

Significant earthquakes frequently occur in Indonesia. Indonesia is situated over three active tectonic plates, resulting in the formation of faults and trenches on the land and ocean floor. For the last 120 years since 1900, there have been more than 1,250 significant earthquake events in Indonesia. In this study, we analyse Indonesia's significant earthquake events using geostatistical and geovisualisation methods to produce an appropriate geospatial analysis platform using the RShiny package to build the WebGIS application. The results show that the earthquake events were spatially distributed from the Sumatera fault in the western part of Indonesia to the southern part of Indonesia, where the Java trench was located and the eastern part of Indonesia. The WebGIS application received a positive evaluation by respondents, with a mean value of 1.617 for pragmatic quality, 1.808 for hedonic quality, and 1.713 for overall quality. This means that the WebGIS application is of good quality based on respondents' impressions. The users also more easily gained insight into information as a result of geostatistical methods. The information gained by the users during the user interaction with the WebGIS platform overlapped with the information that the researcher started with, that is, the spatial cluster of significant earthquakes in Indonesia.

Open-vocabulary learning has recently gained prominence as a means to enable image segmentation for arbitrary categories based on textual descriptions. This advancement has extended the applicability of segmentation systems to a broader range of generally purpose scenarios. However, current methods often revolve around specialized architectures and parameters tailored to specific segmentation tasks, resulting in a fragmented landscape of segmentation models. In response to these challenges, we introduce OVAMTSeg, a versatile framework designed for Open-Vocabulary and Multitask Image Segmentation. OVAMTSeg harnesses adaptive prompt learning to empower the model to capture category-sensitive concepts, enhancing its robustness across diverse multi-task and scenario contexts. Text prompts are employed to effectively capture semantic and contextual features of the text, while cross-attention and cross-modal interactions enable the fusion of image and text features. Furthermore, a transformer-based decoder is incorporated for dense prediction. Extensive experimental results underscore the effectiveness of OVAMTSeg, showcasing its state-of-the-art performance and superior generalization capabilities across three segmentation tasks. Notable achievements include a 47.5 mIoU in referring expression segmentation, 51.6 mIoU on Pascal-VOC with four unseen classes, 46.6 mIoU on Pascal-Context in zero-shot segmentation, 65.9 mIoU on Pascal-5i, and 35.7 mIoU on COCO-20i datasets for one-shot segmentation.

The open data market is growing, driven by laws requiring governments to make data publicly available. However, the true value of this market lies in the products and services derived from open data. In Slovenia, the open data market has been growing since 2015, especially in the field of mobility. Platforms such as Avtolog.si facilitate the retrieval of vehicle data via vehicle identification numbers, while tocen.si, ojpp.si, and brezavta.si aggregate mobility data, focusing on sustainable and micromobile public transportation services. These platforms use open government data and private sector open data, and are freely accessible. This study examines the use of open data in the Slovenian mobility applications and similar solutions developed in other countries. By mapping these applications, we gain valuable insights into potential advances in the field, and provide a useful resource for future developers worldwide. By focusing on the socio-economic impact of these innovations, the study identifies methods for evaluating such applications. This approach highlights how transforming open data into user-friendly products and services can deepen our understanding of their broader societal and economic benefits. While open data is valuable in its own right, its full transformative potential is realized through innovative products that support sustainable lifestyles and promote environmentally conscious behavior.

Open-source 3-D printing has played a pivotal role in revolutionizing the additive manufacturing (AM) landscape, by making distributed manufacturing economic, democratizing access, and fostering far more rapid innovation than antiquated proprietary systems. Unfortunately, some 3-D printing manufacturing companies began deviating from open-source principles and violating licenses for the detriment of the community. To determine if a pattern has emerged of companies patenting clearly open-source innovations, this study presents three case studies from the three primary regions of open-source 3-D printing development (EU, U.S. and China) as well as three aspects of 3-D printing technology (AM materials, an open-source 3-D printer, and core open-source 3-D printing concepts used in most 3-D printers). The results of this review have shown that non-inventing entities called patent parasites are patenting open-source inventions already well-established in the open source community and in the most egregious cases commercialized by one (or several) firms at the time of the patent filing. Patent parasites are able to patent open-source innovations by using a different language, vague patent titles and broad claims that encompass enormous swaths of widely diffused open-source innovation space. This practice poses a severe threat to innovation and several approaches to irradicate the threat are discussed.

Recent advancements in cloud-computing and social-networking are influencing how we communicate professionally, work collaboratively, and approach data-science tasks. Here we show how the groundwater modeling field is well positioned to benefit from these advancements. We present a case study detailing a vertically-integrated, collaborative modeling framework jointly developed by participants at the American Samoa Power Authority and at the University of Hawaii Water Resources Research Center. The framework components include direct collection and analysis of climatic and streamflow data, development of a water budget model, and initiation of a dynamic groundwater modeling process. The framework is entirely open-source and applies newly available data-science infrastructure using Python-based tools compiled with Jupyter Notebooks and cloud computing services such as GitHub. These resources allow for seamless integration of multiple computational components into a dynamic cloud-based workflow that is immediately accessible to stakeholders, resource managers, or anyone with an internet connection

Although many physical activity (PA) interventions for older adults have proven ef-fective in controlled research settings, optimal implementation in real life remains challenging. This study identifies determinants perceived by stakeholders when im-plementing community-based PA interventions for older adults. We interviewed 31 stakeholders guided by the Consolidated Framework for Implementation Research (CFIR). Results showed that stakeholders are very specific about the role they can play in implementation making collaboration between stakeholders crucial. Barriers and motivators were identified in the CFIR intervention characteristics domain (relative advantage, complexity and costs, evidence quality and strength, and adaptability and trialability), in the outer setting domain (cosmopolitism, patient needs, and external policy and incentives), in the inner setting domain (implementation climate, relative priority, compatibility and organizational incentives and rewards) and in the individ-ual characteristics domain (knowledge and beliefs, and other personal attributes). An overarching theme was the stakeholders' emphasis on aiming for broad health goals in interventions, as they perceive PA as a means to reach these goals rather than an end in itself. Another overarching theme requiring attention in future implementation ef-forts is the need to tailor implementation efforts to the specific needs of older adults as the end users of the intervention.

Abstract: This review addresses the complexities of type 1 diabetes (T1D)and its associated complications, with a par-ticular focus on diabetic retinopathy (DR). This review outlines the progression from non-proliferative to proliferative diabetic retinopathy and diabetic macular edema, highlighting the role of dysglycemia in the pathogenesis of these conditions. A significant portion of the review is devoted to technological advances in diabetes management, particu-larly the use of Hybrid Closed Loop systems (HCLS) and to the potential of open-source HCLS systems, which could be easily adapted to different patiens’needs using big data analytics and machine learning. Personalized HCLS algorithms that integrate factors such as patient lifestyle, dietary habits, and hormonal variations are highlighted as critical to reducing the incidence of diabetes-related complications and improving patient outcomes.

The increasing complexity of the design and operation evaluation process of multi-energy grids (MEGs) requires tools for the coupled simulation of power, gas and district heating grids. Most tools analyzed in this paper either do not allow coupling of infrastructures, simplify the grid model or are not publicly available. We introduce the open source piping grid simulation tool pandapipes that – in interaction with pandapower - fulfills three crucial criteria: clear data structure, adaptable MEG model setup and performance. In an introduction to pandapipes we illustrate how it fulfills these criteria through its internal structure and demonstrate how it performs in comparison to STANET®. Then we show two case studies that have been performed with pandapipes already. The first case study demonstrates a peak shaving strategy as interaction of a local electricity and district heating grid in a small settlement. The second case study analyzes the potential of a power-to-gas device to serve as flexibility in a power grid under consideration of gas grid constraints. They both show the importance of a clear database, a simple simulation setup and good performance to set up different large and complex studies on grid infrastructure design and operation.

This paper explores the role of open-source large language models in IoT cybersecurity world. The threats of malicious activity on the Internet and the loss of private information are very real and lead to serious consequences. The purpose of this paper is to investigate how open source-large language models can help to defend against the growing threat of cyber-crimes. We conducted our experiments in two directions. The first one is a security assistant that helps with cybersecurity best practices advices. The second one is a how large language model can simulate a vulnerable IoT system. For both types of experiments, the interactive mode of operation of the language model is used. In the context of the cybersecurity research, a major advantage of the locally installed open-sourced large language models is that they do not share sensitive data with a remote system in a cloud. The paper concludes by discussing the potential impact of open-source large language models on cybersecurity research and recommends future research directions.

Digital Elevation Models (DEMs) are widely used in geographic and environmental studies. In the current work, the fusion of multi-source DEMs is investigated to improve the overall accuracy of public domain DEMs. Multi-scale decomposition is an important analytical method in data fusion. Three multi-scale decomposition methods – the wavelet transform (WT), bidimensional empirical mode decomposition (BEMD) and nonlinear adaptive multi-scale decomposition (N-AMD) - are applied to the 1-arc-second Shuttle Radar Topography Mission Global digital elevation model (SRTM-1 DEM) and the Advanced Land Observing Satellite World 3D – 30 m digital surface model (AW3D30 DSM) in China. Of these, the WT and BEMD are popular image fusion methods. A new approach for DEM fusion is developed using N-AMD (which is originally invented to remove the cycle from sunspots). Subsequently, a window-based rule is proposed for the fusion of corresponding frequency components obtained by these methods. Quantitative results show that N-AMD is more suitable for multi-scale fusion of multi-source DEMs, taking the ice cloud and land elevation satellite (ICESat) global land surface altimetry data as a reference. The vertical accuracy of the fused DEM shows significant improvements of 29.6% and 19.3% in a mountainous region and 27.4% and 15.5% in a low-relief region, compared to the SRTM-1 and AW3D30 respectively. Furthermore, a slope position-based linear regression method is developed to calibrate the fused DEM for different slope position classes, by investigating the distribution of the fused DEM error with topography. The results indicate that the accuracy of the DEM calibrated by this method is improved by 16% and 13.6%, compared to the fused DEM in the mountainous region and low-relief region respectively, proving that it is a practical and simple means of further increasing the accuracy of the fused DEM.

The management of large medical files is a critical challenge in the health sector. Conventional systems have security, scalability, and efficiency deficiencies. This project proposes a hybrid architecture between blockchain and cloud computing to address these challenges. Blockchain ensures the immutability and traceability of medical records, while the cloud allows scalable and efficient storage. Together, these technologies can transform data management in electronic health record applications. The essential objective of this research is to thoroughly look at the existing strategies, devices, and conventions that encourage a secure interaction between blockchain applications and the cloud. Special emphasis is set on maintaining the integrity and security of the blockchain while tackling the potential and efficiency of cloud infrastructures. Through a meticulous investigation of these approaches, along with their successful usage and encountered challenges, this paper offers a comprehensive overview of the present state of this integration. Altogether, this paper does not propose new concepts or developments. Its central focus is to provide a comprehensive and insightful examination of the modern landscape concerning the integration of blockchain and cloud advances. By shedding light on the existing approaches and assessing their viability, this work aims to highlight the current challenges and build up a solid establishment for future development. This, in turn, will cultivate a consistent integration of blockchain security with the dynamic potential of cloud computing while guaranteeing information integrity and security remain uncompromised. In conclusion, this paper serves as a important resource for analysts, specialists, and partners looking for to dig into and development the integration of blockchain and cloud innovations, subsequently contributing to a more secure and productive cloud environment.

The use of Learning Management Systems (LMS) has had a rapid growth over the last decades. Great efforts have been recently made to assess the level of performance of the students online due to the COVID-19 pandemic. Faculty members with limited experience in the use of LMS such as Moodle, Edmodo, MOOC, Blackboard and Google Classroom can have some problems creat-ing online tests. In this work, a new plugin for Moodle is presented: FastTest PlugIn. This plugin is based on a Microsoft® Excel spreadsheet and it can be used to export questions to Moodle. Us-ers of FastTest PlugIn can create question pools in an easy and intuitive way. A literature review about plugins used to import/export questions in Moodle is carried out. Then, the characteristics of FastTest PlugIn are presented. At the end, the characteristics of the main plugins found in the literature are discussed and compared with the ones of FastTest PlugIn.

Broadcasting a message from one to many processors in a network corresponds to concurrent reading on a random access shared memory parallel machine. Computing the trees of a forest, the level of each node in its tree and the path between two nodes are problems that can easily be solved with concurrent reading in a time logarithmic in the maximum height of a tree. Solving such problems with exclusive reading requires a time logarithmic in the number of nodes, implying message passing between disjoint pairs of processors on a distributed system. Allowing concurrent reading in parallel algorithm design for distributed computing might be advantageous in practice if these problems are faced on shallow trees with some specific constraints. We show an application to LZC-compressed file decoding, whose parallelization employs these computations on such trees for realistic data. On the other hand, zipped files do not have such advantage since they are compressed by the Lempel-Ziv sliding window technique.

The quantification of sea surface temperature (SST) through space platforms has revolutionized how we obtain information at a global level. However, the main disadvantage of obtaining SST with satellite images consists of its inherent coarse spatial resolution. One solution could be the use of downscaling algorithms to create sequences of matrices at a higher resolution. We used the same SST data source from the MODIS-Aqua sensor at three spatial resolutions of 9 km, 4.5 km, and 1 km in the Gulf of California. Based on an open-source algorithm, the original SST images were downscaled to 4.5 km, 1 km, 500 m, 250 m, and 125 m per pixel scales. Results indicate a strong linear relationship between the original SST-MODIS data and the modeled data for all spatial resolutions. This study demonstrates the feasibility of an open-source downscaling algorithm to enhance the spatial resolution of SST images in a marginal sea.

Context: Anomaly detection in a data center is a challenging task, having to consider different services on various resources. Current literature shows the application of artificial intelligence techniques to either log files or monitoring data: the former created by services at run time, while the latter produced by specific sensors directly on the physical or virtual machine. Objectives: We propose a model that exploits information both in log files and monitoring data to identify patterns and detect anomalies over time. Methods: The key idea is to use on one side natural language processing solutions to detect problems at service level, extracting words that represent anomalies. Clustering and topic modeling techniques have been used to identify patterns and group them with respect to topics. On the other side time series anomaly detection technique has been applied to sensors data in order to combine problems found in the log files with problems stored in the monitoring data. Results: We have tested our approach on a real data center equipped with log files and monitoring data that can characterize the behaviour of physical and virtual resources in production. We have observed a correspondence between anomalies in log files and monitoring data, e.g. an increase in memory usage or machine load. The results are extremely promising. Conclusion: Our model requires to integrate site administrators' expertise in order to consider all critical scenario in the data center and understand results properly.

Access to nasopharyngeal swabs for sampling remain a bottleneck in some regions for COVID-19 testing. This study develops a distributed manufacturing solution using only an open source manufacturing tool chain consisting of two types of open source 3-D printing and batch UV curing, and provides a parametric fully free design of a nasopharyngeal swab. The swab was designed using parametric OpenSCAD in two components (a head with engineered break point and various handles), which has several advantages: i) minimizing print time on relatively slow SLA printers, ii) enabling the use of smaller print volume open source SLA printers, iii) reducing the amount of relatively expensive UV resin, and iv) enabling production of handle on more accessible material extrusion 3-D printers. A modular open source UV LED box was designed, fabricated for $45 and tested for batch curing. Swabs can be fabricated for $0.06-$0.12/swab. The results of the mechanical validation tests showed that the swabs could withstand greater forces than would be expected in normal clinical use. The swabs were also able to absorb a significant amounts of synthetic mucus materials and passed abrasion and handling tests. The results show the open source swab are promising candidates for clinical trials.

Background: Endovascular treatment of popliteal aneurysms (PA) has increased in the last few years, quickly becoming the main treatment in many vascular centers, based on the acceptable and promising outcomes reported in the literature. However, endograft infections are the most dangerous complication as a serious local compromise and usually require open surgical conversion and device explantation to preserve the affected extremity. Case report: We reported two patients admitted to the emergency room for pain and edema in the lower leg. Both patients have undergone exclusion of ruptured PA a few years before by endovascular graft. CTA showed a significant volume of fluid-corpuscular collection related to perianeurysmal abscess collection in both cases. Blood cultures and drained material cultures were positive for Staphylococcus Capitis in the first case and S. Aureus in the second. The antibiotics prophylaxis was performed for 10 days, then, patients underwent an open surgical conversion with a complete explantation of endovascular material and a femoro-popliteal bypass using an autologous vein in the first case and biological bovine pericardium prosthesis in the other case. Furthermore, we have questioned the literature and found eight more cases described in case report article referred to popliteal graft infections by different microorganisms, mostly presenting acute limb ischemia as the first symptom and suggesting endograft explantation with open conversion and autologous vein bypass as the commonest therapeutic choice. Conclusions: Open surgical conversion of popliteal endograft infection is the best strategy to manage peripheral infection of the popliteal stent.

Due to resource constraints, most Diamond Open Access journals publish less than 25 articles per year, and 75% of journals are not able to provide their content in XML and HTML, primarily providing only PDFs (Bosman et al., 2021, p. 7-8). In order to keep up with larger commercial publishers, a high degree of automation and streamlining of processes is necessary. The Open Source Academic Publishing Suite (OS-APS) project funded by the German Federal Ministry of Education and Research aims to achieve this. OS-APS automatically extracts the underlying XML from Word manuscripts and offers optimization and export options in various formats (PDF, HTML, EPUB). The professional corporate design, e.g., of the PDFs, is managed automatically by using templates or creating one's own using a Template Development Kit. OS-APS will also connect to scholarly-led and community-driven publishing platforms such as Open Journal Systems (OJS), Open Monograph Press (OMP), and DSpace: the software will be able to be integrated into a wide range of publication processes, whether at small, low-resource commercial Open Access Publishers, or institutional and Diamond Open Access Publishers. References: Bosman, J., Frantsvåg, J. E., Kramer, B., Langlais, P.‑C., &amp; Proudman, V. (2021). Oa Diamond Journals Study. Part 1: Findings. https://doi.org/10.5281/zenodo.4558703

Conventional fertilization practices can lead to many ecological problems, such as nutrient imbalance, soil acidity, and reduced soil fertility in natural rubber plantations. To address these challenges, a field investigation was strategically carried out to substitute inorganic fertilizer with organic fertilizers consisted of six treatments, i.e., no fertilization (CK), inorganic fertilizer (NPK), 25 % replacement of inorganic through organic (25%M), 50 % replacement of inorganic through organic (50%M), 75 % replacement of inorganic through organic (75%M), and 100% organic fertilizer (100%M). The soil physicochemical properties (SOC, TN, AN, C:N, pH, NH4+-N, and NO3--N) and carbon and nitrogen converting enzymes (BG, NAG, and LAP) were all determined. The partial substitution of inorganic fertilizers with organic fertilizers (i.e., 75%M at surface soil layer) showed higher SOC (14.52 g.kg-1), TN (1.06 g.kg-1), AN (20.07 mg.kg-1), C:N (14.63), NH4+-N (10.63 mgkg-1), and NO3--N(11.06 mg.kg-1) than NPK and CK. Such increase in physicochemical properties in partial replacement of inorganic with organic fertilizers plots resulted from higher carbon and nitrogen enzymes activities (BG (143.17 nmol.g-1.h-1), NAG (153.96 nmol.g-1.h-1), and LAP (153.48 nmol.g-1.h-1)) compared to NPK and CK, and further the person correlation and RDA analysis confirmed a significant positive correlation between SOC, AN, and soil enzymes. This study presents a new strategy for assessing the impact of partially replacing inorganic fertilizers with organic fertilizers in rubber plantations, mainly by modifying the soil nutrient composition in tropical regions.

Abstract In order to solve the problem that it is difficult to obtain the accurate trigger signal moment when using the time difference of UAV flight acoustic signals collected by acoustic sensors arranged in advance to locate the position of UAVs when they cannot be tracked by radar and are difficult to be observed by the human eye, an acoustic source localisation method with improved empirical modal decomposition (REMD) under an adaptive frequency window is proposed. Firstly, the collected UAV flight signals are smoothed and filtered, then the robust empirical modal decomposition (REMD) is used for IMF modal decomposition and spectral analysis of the collected signals, and a panning frequency window with variable bandwidth is introduced for corresponding frequency locking and extracting the IMFs; the GWO optimisation is used and the sliding metrics are set to determine the position of the panning frequency window automatically; finally, the extracted Finally, the extracted IMF components are reconstructed according to the criterion, and the trigger signal moments in the reconstructed IMF components are resolved and recorded, and the algorithm is used to calculate the difference between the reception moments of different sensors; for the traditional sound source localisation algorithms with a small detection range, which are prone to fall into the no-solution or false-solution, i.e., unable to achieve the localisation, a weighted least-squares-based Chan-Taylor algorithm is proposed for the localisation computation, and a weighted least-squares algorithm is proposed for the localisation computation, through the Inputting the sensor delay parameter and solving the linear equation system to get the target position information; finally, this paper verifies the robustness and performance of the design method with simulated and actual signals. The results show that the maximum positioning error is no more than 5% in an area with a side length of 15m in the measurement area. With the improved accuracy of time delay estimation, the positioning simulation results meet the positioning requirements even though the positioning error is further expanded when the measurement area is further expanded.

In this paper, using the discrete time model, we consider the average age of all files for a cached-files-updating system where a server generates N files and transmits them to a local cache. In order that the cached files are fresh, in each time slot the server updates files with certain probabilities. The age of one file or its age of information (AoI) is defined as the time the file stays in cache since it was last time sent to cache. Assume that each file in cache has corresponding request popularity. In this paper, we obtain the distribution function of the popularity-weighted average age over all files, which gives a complete description of this average age. For the random age of single file, both the mean and its distribution have been derived before by establishing a simple Markov chain. Using the same idea, we show that an N dimensional stochastic process can be constituted to characterize the changes of N file ages simultaneously. By solving the steady-state of the resulting process, we obtain the explicit expression of stationary probability for an arbitrary state-vector. Then, the distribution function of the popularity-weighted average age can be derived by mergering a proper set of stationary probabilities. For the possible applications, the distribution function can be utilized to calculate the probability that the average age violates certain statistical guarantee.

Macrophages as a source and target of GDF-15

This work assesses sea-level rise using three different models created on Free and Open-Source Software for Geographic Information System (FOSS4GIS). Based on regional projections of Special Report on Climate Change and Oceans and Cryosphere (SROCC) of the Intergovernmental Panel on Climate Change (IPCC), the models were applied to a case of study on Rio Grande do Sul coast – Brazil under different sea-level rise scenarios by the end of this century. The End Point Rate for QGIS (EPR4Q), calculates a shoreline projection using End Point Rate method. The Uncertainty Bathtub Model (uBTM), analyses the sea-level rise impact by the uncertainty of sea-level projec-tions and vertical error of the Digital Elevation/Terrain Model (DEM/DTM). The Bruun Rule for Google Earth Engine Model (BRGM) predicts the shoreline position with sea-level rise, using topographic and bathymetric data from Unmanned Aerial Vehicles (UAV) and Coastal Modelling System (SMC – Brazil), respectively. The results indicated a maximum shoreline retreat for 2100 of -502 m and -1727 m using EPR4Q and BRGM, correspondingly. The uBTM using the land-use of Mapbiomas showed a maximum of 44.57 km2 of urban area impacted by the sea-level flood. This research highlights the possibility of performing coastal management analysis in GIS environ-ment using non-commercial software.

Strong-aroma Baijiu is a traditional Chinese spirit distilled from grains that undergo solid-state fermentation. At the end of each fermentation cycle, a significant quantity of Huangshui accumulates at the bottom of the fermentation pit, constituting one of the primary by-products in the brewing process of strong-flavor liquor. In this report, the chemical component analysis of Huangshui obtained from a strong-flavor liquor factory revealed a diverse array of organic acids, alcohols, esters, starch, reducing sugars, amino acids, and other compounds present in Huangshui. Additionally, two specialized solid-state fermentation models were developed to investigate the formation process of Huangshui. Our findings demonstrate a positive correlation between the yield of Huangshui and the initial moisture content of fermented grains. It is concluded that Huangshui is the percolate produced during the solid-state brewing process of strong-flavor liquor, with its water content originating from the initial moisture of fermented grains.

The atomic structures of Zn and Na borophosphate glasses were studied by X-ray and neutron diffraction. Peaks assigned to the B−O, P−O, and O−O distances confirm that only BO4 units co-exist with the PO4 tetrahedra. The Zn−O and Na−O coordination numbers are found to be a little larger than four. The narrowest peaks of the Zn−O first-neighbor distances exist for the glasses along a line connecting the Zn(PO3)2 and BPO4 compositions (50 mol% P2O5) which is explained by networks of ZnO4, BO4, and PO4 tetrahedra with twofold coordinated oxygens. Calculated amounts of the available oxygen support this interpretation. Broadened peaks occur for glasses with lower P2O5 contents, consistent with the presence of threefold coordinated oxygens. The two distinct P−O peak components of the Zn and Na borophosphate glasses differ in their relative abundances which is interpreted by Na+ cations that coordinate oxygens in some P−O−B bridges, something not seen for the Zn2+ ions.

This paper aims to address the exponential stability and stabilization problems for a class of delayed nonlinear Markov jump systems under randomly occurring Denial-of-Service (DoS) attack and packet loss. Firstly, the stochastic characteristics of DoS attack and packet loss are depicted by the attack success rate and packet loss rate. Secondly, a Period Observation Window (POW) method and a hybrid-input strategy are proposed to compensate for the impact of DoS attack and packet loss on the system. Thirdly, A Dynamic Event-triggered Mechanism (DETM) is introduced to save more network resources and ensure the security and reliability of systems. Then, by constructing a general common Lyapunov functional and combining with the DETM and other inequality analysis techniques, the less conservative stability and stabilization criteria for the underlying systems are derived. In the end, the effectiveness of our result is verified through a numerical example.

Purpose: Early glottic cancer is a highly curable malignancy. Disease control is achieved by resec-tion or external beam radiation with similar long-term results according survival. Surgery is predominantly performed by transoral endoscopic approach, due to reduced complication rates when compared to open cordectomy. Open cordectomy might still be warranted in cases of inad-equate surgical accessibility. Aim of the present study was to compare endoscopic versus open approach in relation to complications and outcome in an up-to-date patient group. Methods: 219 patients underwent primary tumor resection in early glottic cancer (UICC stages I-II). 168 opera-tions were performed endoscopically, 51 operations were open transcervical cordectomies. We compared survival data with non-parametric methods and functional outcome according to need of tracheostomy, feeding tube and voice functional outcome following ELS protocol. Results: There were no significant differences in overall survival (OS). 2 years OS after endoscopic surgery was 90.5% vs 95.3% after transcervical resection. As expected, OS in T1b and T2 tumors was worse than in T1a tumors. We found a statistically significant difference in disease free survival (DFS) within the T1a and T1b/T2 group (Log rank test: p=0.006) but no relevant difference be-tween the two surgical modalities, even when the data was stratified by T-categories performing a Cox regression (hazard ratio 1.21, p=0.712). Patients who underwent open surgery had a sig-nificantly worse peri- and postoperative course with longer hospital stay, higher frequency of tracheotomies and longer need for nasogastric tubes. Functional results were comparable within the two patient groups while higher tumor size / stage was an unfavorable predictor for voice re-habilitation. Conclusion: Open cordectomy leads to more complications but offers comparable oncological and functional outcome when compared to transoral endoscopic approach in early glottic cancer. Open surgery therefore continues to be a valid treatment option when endoscopic resection is not possible.

Open-source devices are nowadays used in a vast number of research fields like medicine, education, agriculture, and sports among others. In this work, an open-source, portable, low cost pH logger, appropriate for in situ meas-urements was designed and developed to assist in experiments on agricultural produce manufacturing. Τhe device was calibrated manually using pH buffers for values of 4.01 and 7.01. Then it was tested by manually measuring pH from the juice of citrus fruits. A waterproof temperature sensor was added to the device for temperature compen-sation when measuring pH. A formal method comparison process between the open-source device and a Hanna HI9024 Waterproof pH Meter was designed to assess their agreement. We derived indices of agreement and graph-ical assessment tools using mixed-effects models. Advantages and disadvantages for interpreting agreement through the proposed procedure are discussed. In our illustration, indices reported mediocre agreement and the subsequent similarity analysis revealed a fixed bias of 0.22 pH units. After recalibration, agreement between the devices im-proved to excellent levels. The process can be followed in general to avoid misleading or over-simplistic results of studies reporting solely correlation coefficients for formal comparison purposes.

Researchers need to delineate the shoreline for different applications with no access to costly resources such as topographic maps and high-resolution satellite images. With the increase of open source data, this study aims to present a methodology to use open source data in the best possible way to map the shoreline. Several methods have been tested using open source remote sensing data (Landsat and Aster), such as supervised classification, unsupervised classification, manual mapping, and by applying some spectral indices, among others. The accuracy of the extracted shoreline data was verified using high-resolution open database images (such as Google Earth basemap). The results showed that the manually mapped shoreline through applying spectral index (green- near infrared/green+ near infrared) is the most accurate, although it remains important to modify it using high-resolution images of open databases. Open-source data showed acceptable accuracy in mapping the shoreline.

Amazon Simple Storage Service (Amazon S3) has become a widely used and reliable platform for storing large biomedical datasets. However, unintended changes to the original data can occur during the data writing and transmission, ultimately altering the original contents of the object transferred and producing unexpected results when later accessed. Despite the interest in verifying end-to-end data integrity, there are no existing open-source and easy-to-use tools to accomplish this mission. To bridge this gap, here we present aws-s3-integrity-check, a user-friendly, lightweight and reliable bash tool to verify the integrity of a dataset stored within an Amazon S3 bucket. By using this tool, we completed the integrity verification of 1,045 records ranging between 5 Bytes and 10 Gigabytes (GB) in size and occupying a total of ~935 GigaBytes (GB) of Amazon S3 cloud storage space in ~114 minutes. The aws-s3-integrity-check tool also provides file-by-file on-screen and log-file-based information about the status of each individual integrity check. To the best of our knowledge, the aws-s3-integrity-check bash tool is the only open-source tool that allows verifying the integrity of a dataset uploaded to the Amazon S3 Storage system in a quick, reliable and efficient manner. The aws-s3-integrity-check tool is freely available for download and use at https://github.com/SoniaRuiz/aws-s3-integrity-check and https://hub.docker.com/r/soniaruiz/aws-s3-integrity-check.

Excessive nutrient discharge to tropical island coastlines drives eutrophication and algal blooms with significant implications for reef ecosystem condition and provision of ecosystem services. Management actions to address nutrient pollution in coastal ecosystems include setting water quality standards for discharging surface waters. However, these standards do not account for the effects of groundwater discharge, variability in flow, or dilution, all of which may influence assessment of true nutrient impacts on nearshore reef habitats. We developed a method to estimate dissolved inorganic nitrogen (DIN) loads to coastal zones by integrating commonly available datasets within a geospatial modeling framework for Tutuila, American Samoa. The DIN loading model integrated an open-source water budget model, water sampling results, and publically available streamflow data to predict watershed-scale DIN loading to the island’s entire coastline. When compared to surface water pathways, submarine groundwater discharge (SGD) was determined to be the most important coastal delivery mechanism of terrigenous DIN, which supports findings from other tropical islands. Onsite wastewater disposal systems were also found to be the primary anthropogenic sources DIN to coastal waters. Our island-wide DIN loading model provides a simple and robust metric to define spatially-explicit sources and delivery mechanisms of nutrient pollution to nearshore reef habitats. Understanding the sources and primary transport modes of inorganic nitrogen to nearshore reef ecosystems can have significant implications for place-based management interventions aimed at increasing the adaptive capacity of unique island ecosystems to environmental variation and disturbances.

The study investigated the usage of open data in public organizations, focusing on the motives, preferences, and governance ideals that determine their quality. The study shed light on how open data platforms are created and improved, as well as their influence on government operations. The primary goal was to understand the motivations behind the usage of open data, evaluate gov-ernance ideals, and examine institutions' efforts to standardize data formats. Hierarchical regres-sion analysis divides variables into core reasons and different preferences, demonstrating a need for "diversification" in order to use open data effectively. Efficiency, accountability, community impact, knowledge, and high-quality service delivery are all emphasized in governance value analysis. The institution's dedication to standardizing open data formats is evidenced by legislative measures and the integration of many technologies. The findings illustrate the institution's dual strategy of em-ploying traditional techniques and new technologies for effective data management. The report suggests increasing data openness and standardization, investing in ongoing training, upgrading alerting and awareness systems, and adopting specific regulations for open data use. Monitoring and feedback techniques are critical for adjusting and refining open data services to satisfy de-velopment needs. This study adds to the scientific knowledge of open data use by highlighting important motives, preferences, and governance ideals. The offered guidelines provide practical insights for public organizations looking to improve their open data platforms by promoting openness, efficiency, and community participation.

In an effort to enhance the efficiency and safety of open-pit mines, this study explores the optimization of end slope road parameters and slope structures, specifically focusing on unmanned driving lanes.A significant aspect of the study is the development of a truck trajectory offset model, which considers the different reaction times between automated sensors and human drivers in adapting to environmental changes. To test these concepts, the study uses numerical simulations to confirm the stability of the proposed end slope designs. Using Victory West Mine No. 1 as a case study, the research determines the optimized width for unmanned driving lanes and the maximum angle for safe steepening of end slopes. The findings indicate that the optimized unmanned lane width for NTE240 mining dump trucks is 1743 mm, allowing for a 2-degree increase in the slope angle at the south end slope. This optimization leads to a steep mining stripping volume of 3.2735 million m³ and a coal output of 2.49628 million tons, maintaining a stripping ratio of 1.31m³/t. These results demonstrate that the unmanned driving road width optimization not only ensures slope safety but also significantly boosts the economic benefits of steep mining in open-pit mines.

To assist firefighters and other first responders to use their existing equipment for respiration during the COVID-19 pandemic without using single-use, low-supply, masks, this study outlines an open source kit to convert a 3M-manufactured Scott Safety self-contained breathing apparatus (SCBA) into a powered air-purifying particulate respirator (PAPR). The open source PAPR can be fabricated with a low-cost 3-D printer and widely available components for less than $150, replacing commercial conversion kits saving 85% or full-fledged proprietary PAPRs saving over 90%. The parametric designs allow for adaptation to other core components and can be custom fit specifically to fire-fighter equipment, including their suspenders. The open source PAPR has controllable air flow and its design enables breathing even if the fan is disconnected or if the battery dies. The open source PAPR was tested for air flow as a function of battery life and was found to meet NIOSH air flow requirements for 4 hours, which is 300% over expected regular use.