Bar Code Research Articles

An unsupervised map of excitatory neuron dendritic morphology in the mouse visual cortex

Neurons in the neocortex exhibit astonishing morphological diversity, which is critical for properly wiring neural circuits and giving neurons their functional properties. However, the organizational principles underlying this morphological diversity remain an open question. Here, we took a data-driven approach using graph-based machine learning methods to obtain a low-dimensional morphological “bar code” describing more than 30,000 excitatory neurons in mouse visual areas V1, AL, and RL that were reconstructed from the millimeter scale MICrONS serial-section electron microscopy volume. Contrary to previous classifications into discrete morphological types (m-types), our data-driven approach suggests that the morphological landscape of cortical excitatory neurons is better described as a continuum, with a few notable exceptions in layers 5 and 6. Dendritic morphologies in layers 2–3 exhibited a trend towards a decreasing width of the dendritic arbor and a smaller tuft with increasing cortical depth. Inter-area differences were most evident in layer 4, where V1 contained more atufted neurons than higher visual areas. Moreover, we discovered neurons in V1 on the border to layer 5, which avoided deeper layers with their dendrites. In summary, we suggest that excitatory neurons’ morphological diversity is better understood by considering axes of variation than using distinct m-types.

398 Phage Wars: Uncovering the resistance strategies of Escherichia coli O157:H7

Objectives/Goals: The goal of this work is to understand the physiological profile of phage susceptibility and identify candidate phage defense mechanisms. Additionally, it aims to determine the host receptors targeted by bacteriophages to infect E. coli O157:H7 through random bar code transposon-site sequencing (RB-TnSeq). Methods/Study Population: A collection of 109 E. coli O157:H7 strains from environmental, food, and animal sources were analyzed, representing phylogenetic lineages corresponding to clades 2, 3, 5, 6, 7, and 8. Phage susceptibility profiles were determined using 23 bacteriophages, assessing plaque morphology. Using the O157:H7 genomes, a genomic analysis was conducted with the Prokaryotic Antiviral Defense Locator (PADLOC), which identified putative phage defense systems through sequence homology. Additionally, 5 RB-TnSeq libraries were generated in representative strains to study loss-of-function mutations. These libraries will be screened against a subset of diverse phage to identify the receptors involved in phage adsorption. Results/Anticipated Results: The phage resistance patterns showed susceptibility varied across clades, suggesting distinct mechanisms. Several defense systems were identified using PADLOC, including restriction-modification, Cas, Lamassu, and Druantia. Phage defense candidate (PDC) systems were identified, showing homology to known systems, though their specific function remains unknown. Clade 7.2 exhibited higher phage resistance and a greater presence of PDCs compared to the other clades. Five saturated RB-TnSeq libraries were constructed in O157:H7, achieving 84.5–89% gene coverage. These libraries will facilitate the identification of receptors involved in phage adsorption and resistance. Discussion/Significance of Impact: This study deepens our understanding of phage resistance in E. coli O157:H7 by identifying key defense systems and receptors. The discovery of novel antiviral mechanisms offers promising targets for phage-based interventions, potentially enhancing strategies for controlling this dangerous pathogen.

On The Design of a Novel Smart Medicine Box Towards Detecting the Medicine Expiry Date and Facilitating Medication Planning for Visually Challenged

Population growth has led to the increase of different types of medication, burden on nurses and pharmacy clerks. Studies have shown that on an average a person takes about five different types of medication for any illness. This medication has led to several other medication errors as the patient is taking wrong medicine at the wrong time in a day. This is highly prevalent in people who are older in age and for the people, who are visual impaired or challenged. These people face difficulty in checking the expiry date of the medication because of smaller text size and fonts. It is well known that consumption of an expired product is fatal. To prevent this medication error, forgetting medicine intake and consumption of expired medication; the Smart Medicine Box idea is used. It is a boxlike structure with certain compartments. The compartment has LCD screen that displays the name of the medicine stored and the date of expiration for that medicine. In addition, the box contains speaker to announce the name of the medicine and date of expiration. To assist the visually impaired to take the correct medication vibration mechanism has been set up where the compartment containing the medicine to be taken at that time vibrates indicating to the user. Image processing technique is used to process and analyse the bar code of the medication for the expiration date and the name of the medication. Ultrasonic Sensors are used to detect the pending number of pills within the compartment; a microcontroller is used to control the process. In this research effort, after a critical overview of the state-of-the-art developments in this important field we outline in detail the proposed architecture for such an efficient smart medicine box, defining its components and its preliminary UML related diagrams.

A study to assess the awareness and utilization regarding government scheme “Janani Suraksha Yojana” (JSY) among general public in New Delhi

Maternal health remains a pressing public health challenge in India, with high maternal and neonatal mortality rates influenced by poverty, limited healthcare access, and cultural barriers. To address these issues, the Government of India introduced the Janani Suraksha Yojana (JSY) in 2005, a conditional cash transfer program promoting institutional deliveries to reduce mortality rates. Despite its significance, awareness and utilization of the scheme remain low among the public. So, in this concern an quantitative and descriptive research was conducted, the aim of the study aimed to evaluate the awareness and utilization of JSY among attendees of the antenatal outpatient department at Lal Bahadur Shastri Hospital, New Delhi with 112 participants selected through convenient sampling. Data were gathered using a structured questionnaire distributed via a Google Form link and Bar Code. The data were analyzed using descriptive statistics, including frequencies, percentages, means, and chi-square tests. The results revealed that 57.1% of respondents were unaware of JSY, and 77.7% had not utilized the scheme. No significant association was found between demographic factors and awareness levels. Knowledge regarding Janani Suraksha Yojna was disseminated through charts, posters, pamphlets and nukkad natak among the general public. The study highlights the need to increase awareness and utilization of JSY among the general public in New Delhi. Health education programs and awareness campaigns can be implemented to promote the scheme and improve maternal and child health outcomes.

Near-Field Direct Write Electrospinning of PET-Carbon Quantum Dot Solutions.

Electrospinning of polymer material has gained a lot of interest in the past decades. Various methods of electrospinning have been applied for different applications, from needle electrospinning to needleless electrospinning. A relatively new variation of electrospinning, namely near-field electrospinning, has been used to generate well-defined patterns. This variation of electrospinning, also known as near-field direct-write electrospinning, allows for precise control of the fiber deposition, sacrificing on the thickness of the resulting fibers. Typically, for this method, melt electrospinning is preferred, since it provides a higher viscosity of the polymer and thereby better control of the fiber deposition. However, when mixing additives into the spinning dope, a solution spinning approach is preferable since it provides a more homogeneous distribution of the additives in the spinning dope. A fluorescent spinning dope of dissolved PET with fluorescent carbon quantum dots has been used to generate the fluorescent patterns. These can be used to generate logos, bar codes, or QR codes to encode information about the material, such as watermarks or counterfeiting tags.

Analysis of antinuclear antibody in 9 528 pregnant women during early pregnancy in a hospital in Qingdao City

To analyze the positivity rate and titer of antinuclear antibody (ANA), as well as nuclear pattern and target antigen of ANA in healthy pregnant women during early pregnancy in Qingdao area. A prospective cohort study design was used to include a total of 9 528 healthy pregnant women registered at the Women and Children's Hospital Affiliated to Qingdao University from March 2023 to June 2024.Indirect immunofluorescence assay (IIF) was used to detect ANA, its titer and cell staining pattern. Fifteen specific antibodies were tested using the magnetic bar code immunofluorescent luminescence method. Logistic regression model was used to analyze the risk factors of pregnancy with autoimmune disease(AID). The results showed that among 9 528 pregnant women in early pregnancy, 1 346 cases (14.1%) were positive of ANA, including 1 011 cases with a titer of 1∶100 (10.6%), 236 cases (2.5%) with a titer of 1∶320, and 99 cases (1.0%) were detected at a titer >1∶320. Among the 1 346 ANA-positive pregnant women, nuclear granular type accounted for the highest proportion (483 cases, 35.9%), followed by speckled type (347 cases, 25.8%) and cytoplasmic type (176 cases, 13.1%).Then, pregnant women with ANA titers ≥1∶100 were detected 15 specific antibodies.Anti-SSA was tested in 121 cases accounted for the majority, followed by 110 cases with anti-Ro-52, 56 cases with anti-SSB, 51 cases with anti-mitochondrial M2 subtype antibodies and 37 cases with anti-centromere B. In conclusion,in healthy pregnant women in Qingdao area, ANA positivity rate was 14.1%, and the titer of ANA was mainly at 1∶100.The predominant nuclear patterns were nuclear granular and speckled types.The specific autoantibodies were mainly anti-SSA antibodies and anti-Ro-52 antibodies.The detection of ANA and specific autoantibodies is of great significance for early prediction, diagnosis, and intervention of autoimmune diseases during pregnancy.

Utilizing an Adhar Card for the Smart Bus Ticketing System

Since public transit is the least expensive and most dependable mode of transportation in India, the public has always found it to be appealing. India’s public transportation system relies heavily on buses as one of its main modes of transit. An increasing number of people depend on public transportation to get to work, school, hospitals, and other places, which has led to a progressive progression in the transportation system in daily life. A sophisticated and dependable system is still required, even though the services offered by public transportation buses have been moderately adequate. Issues with bus tickets are the main source of contention on local buses, frequently resulting in confrontations between riders and drivers. With this in mind, we’re creating an Android app that will make bus ticketing quick and easy for both users (passengers) and service providers (conductors). Using QR Code technology for fast money transfers, the Android application offers an interface for the bus ticketing system. The most widely used method of storing and transferring data between devices is the Quick Response Code, or QR Code. With greater capacity than UPC codes, it is a kind of matrix bar code. Commonly scanned and decoded by a smartphone with a camera, but it can also be created or decoded by any camera device that uses QR decoding logic. With the use of this application, passengers can travel cashless, and the conductor won’t have to worry about finding change for the bus fee that they paid. We can reduce the use of paper tickets by using this program, which will benefit India’s environmental efforts.

Dental Implant Identification Methods

Dental implants are a well-accepted prosthetic alternative for missing teeth. After implant restoration, they will need maintenance in due course of time due to biological and mechanical complications, during which information about the implant system is required. Until today there is no well-established method for implant identification and conventional tools such as interpretation from radiographs need time and effort. Researchers have proposed several methods for implant identification and the review focuses on a comprehensive discussion of the proposed methods. For this review, comprehensive data from databases, including PubMed, Scopus, Web of Science, Cochrane, and Google Scholar, was thoroughly examined ensuring the most up-to-date and relevant information regarding implant identification. The proposed methods include an interpretation from radiographs based on the implant design specifications listed, implant records, implant recognition software, retrieving implant information through a wireless reader from a radiofrequency chip fitted into an implant screw hole, QR-encoded implant identification wallet, bar code encryption by implant manufacturers, incorporating laser-etched batch and serial numbers in implant collars, Sharma Jhingta system of implant identification and artificial intelligence methods. Amongst existing methods, AI research shows potential in offering a quick and accurate method of implant identification however developing a robust AI model with a comprehensive database is a complex task and requires considerable effort and time.

Construction of an Iterated Function System on ℝ2 whose Attractor is a QR Code

A QR code is a two-dimensional bar code that encodes a message into a finite collection of black and white squares which are arranged in a square region with a specific order. Considering a QR code as a compact subset of R 2 , we construct an Iterated Function System (IFS) on R 2 whose attractor is the given QR code.

Pengaruh Model Pembelajaran LOK-R Berbantuan Media Kode Batang terhadap Keterampilan Membaca Cerita fantasi

This study aims to determine the effect of the LOK-R learning model assisted by bar code media on the ability to read fantasy stories. The research was conducted at SMP Muhammadiyah 19 Sawangan using a sample of 56 students divided into two groups, namely class VII.3 as an experimental group consisting of 28 students and class VII.1 as a control group consisting of 28 students. This research uses quantitative methods (true experiment) with post-test-only research design. The results showed a significant difference between the experimental class that used the LOC-R learning model assisted by bar code media and the control class that did not use the LOC-R learning model assisted by bar code media. Statistical analysis using the t-test formula showed that the sig. (2-tailed) = 0.000 <0.05, and the calculated t- value obtained is 6.756 with df = 54. At the 5% significance level, the t- table value is 1.674.Based on the value of t-count > t-table, Ho is rejected, and Ha is accepted. Therefore, it can be concluded that the application of the LOC-R learning model assisted by bar code media has a significant effect on fantasy story reading skills.

Fruit and vegetable self-billing system based on image recognition

Introduction: Shopping centers have become a necessary aspect of living, especially for city dwellers. To realize the identification and settlement of fruits and vegetables lacking bar codes is a major problem in supermarket self-service settlement. Methods: In this study, we proposed a novel Garra Rufa fish-optimized multi-objective convolutional neural network (GRFO-MCNN) for fruit and vegetable detection and freshness recognition. To improve feature identification performance, the GRFO-MCNN integrates the CBAM, which consists of the CAM and the SAM. Freshness recognition and fruit and vegetable detection are greatly enhanced by the CBAM by focusing on pertinent regions of images. Results: The proposed model integrate with the automated settlement system which transform the fruits and vegetable purchases by streamline identification and payment process. The Raspberry Pi, a microcontroller with a camera unit, makes up the suggested model to automate the billing system. For this study, we used a Raspberry Pi module to automatically acquire image data of fruits and vegetables. Conclusions: The suggested approach is contrasted with the other traditional approaches. The result shows the suggested approaches outperformed in accuracy (0.93), MAE (0.11), and RMSE (0.53). The fruits and vegetables that are arranged for automatic weighing are captured by the camera module. The microprocessor receives as an input the cost of various products per kilogram automatically. Consequently, the Raspberry Pi automatically calculates and shows the overall lprice of the products on the monitor

Improved Nursing Workload by Introducing a Traceability System to Manage Medical Materials.

Improved Nursing Workload by Introducing a Traceability System to Manage Medical Materials.

Bar codes of persistent cohomology and Arrhenius law for $p$-forms Bar codes of persistent cohomology and Arrhenius law for $p$-forms

Bar codes of persistent cohomology and Arrhenius law for $p$-forms Bar codes of persistent cohomology and Arrhenius law for $p$-forms

Complex Patterns of Antihypertensive Treatment Changes in Long-Term Care Residents

Complex Patterns of Antihypertensive Treatment Changes in Long-Term Care Residents

Information encryption driven by strength-switchable circular dichroism in vanadium dioxide based chiral metasurfaces

Information encryption driven by strength-switchable circular dichroism in vanadium dioxide based chiral metasurfaces

Development of a crowdsourcing- and gamification-based mobile application to collect epidemiological information and promote healthy lifestyles in Mexico

We developed a mobile application to promote healthy lifestyles and collect non-communicable disease (NCD) data in Mexico. Its theoretical foundations are supported by a framework-guided literature review. With design sprints, Scrum, Model-View-Controller, and Representational State Transfer architecture, we operationalized evidence-based nutrition/physical activity information into a crowdsourcing- and gamification-based application. The application was piloted for three months to monitor the response of 520 adults. Potential improvements were characterized, considering benchmarking, expert guidance, and standards. Salud Activa (English: Active Health) has two crowdsourcing modules: Nutritional scanner, scanning products' bar codes, providing nutritional data, and allowing new product registry feeding our databases; Surveys, comprising gradually-released NCD questions. Three intervention modules were generated: Drinks diary, a beverage assessment component to receive hydration recommendations; Step counter, monitoring users’ steps via Google Fit/Health—iOS; Metabolic Avatar, interconnecting modules and changing as a function of beverage and step records. The 3-month median of Salud Activa use was seven days (IQR = 3–12), up to 35% of participants completed a Survey section, and 157 food products were registered through Nutritional scanner. Better customization might benefit usability and user engagement. Quantitative and qualitative data will enhance Salud Activa’s design, user uptake, and efficacy in interventions delivered through this platform.

Sprint Team Approach Yields Rapid Improvement in Leapfrog Quality Indicators.

Patient safety and quality care are two critical areas that every healthcare organization strives to grow and improve upon. At Scripps Health, specific efforts reviewed for this article were implemented to reduce hospital-acquired conditions and hospital readmissions that are components of Centers for Medicare & Medicaid Services programs and Leapfrog Hospital Survey scores. Sprint teams, a novel approach to rapidly develop a checklist for lower-performing care improvement areas, were implemented after an internal review of existing tools and an evidence-based literature review. These areas included catheter-associated urinary tract infections (CAUTIs), central-line associated bloodstream infections (CLABSIs), Clostridioides difficile (C. diff.) and methicillin-resistant Staphylococcus aureus (MRSA) infections, chronic obstructive pulmonary disease (COPD) and heart failure readmissions, surgical site infections and handwashing, bar coding, and the computerized physician order entry components of Leapfrog scoring. The checklist for each area served as a teaching tool for staff and a guideline for case review to ensure that standard work was routinely performed. The sprint teams showed dramatic results in the initial focus areas. From a baseline standardized infection ratio (SIR) of 1.141 for CLABSIs, the sprint team reduced the SIR to 0.885 in Year 1 of the program and to 0.687 in Year 2. For CAUTIs, the SIR decreased from a baseline of 1.391 in Year 1 to 0.720 in Year 2. C. diff. infections fell from 0.422 to 0.315 in Year 1 and to 0.260 in Year 2. While the MRSA SIR did not improve during the first year, the MRSA reduction sprint team showed success in Year 2 with a decrease in the SIR from 0.537 to 0.245. Readmission reduction sprint teams focused on heart failure, COPD, and total hip and knee complications. The teams also achieved positive results in reducing readmissions by following checklists and reviewing each readmission case for justification. Rapid change can be safely and effectively implemented with multidisciplinary sprint teams. Developed with an evidence-based, case review approach, sprint team checklists can help to standardize processes for the review of any infections or readmissions that occur in the inpatient arena.

Beyond Hospital-Level Aggregated Data: A Methodology to Adapt Clinical Data From the Electronic Health Record for Nursing Unit-Level Research.

Studies of nurse staffing frequently use data aggregated at the hospital level that do not provide the appropriate context to inform unit-level decisions, such as nurse staffing. Describe a method to link patient data collected during the provision of routine care and recorded in the electronic health record (EHR) to the nursing units where care occurred in a national dataset. We identified all Veterans Health Administration acute care hospitalizations in the calendar year 2019 nationwide. We linked patient-level EHR and bar code medication administration data to nursing units using a crosswalk. We divided hospitalizations into segments based on the patient's time-stamped location (ward stays). We calculated the number of ward stays and medication administrations linked to a nursing unit and the unit-level and facility-level mean patient risk scores. We extracted data on 1117 nursing units, 3782 EHR patient locations associated with 1,137,391 ward stays, and 67,772 bar code medication administration locations associated with 147,686,996 medication administrations across 125 Veterans Health Administration facilities. We linked 89.46% of ward stays and 93.10% of medication administrations to a nursing unit. The average (standard deviation) unit-level patient severity across all facilities is 4.71 (1.52), versus 4.53 (0.88) at the facility level. Identification of units is indispensable for using EHR data to understand unit-level phenomena in nursing research and can provide the context-specific information needed by managers making frontline decisions about staffing.

Financial Modeling Based on Book Store Management

The old billing software’s used in supermarkets, will have a lot of manual work and they don’t have the capacity to produce reports needed. The Billing software designed can generate a lot number of reports needed and there is no need of manual work. This billing software is a web application, it can store a lot of records in the database and the bar code scanner are also available. It’s a user-friendly software which can be used for both wholesale and Retail. It has an unlimited storage and application can be used in both online and offline. Reports for billing can be generated by data wise or price wise.

RANCANG BANGUN SISTEM PRESENSI KULIAH MENGGUNAKAN QRCODE BERBASIS ESP32CAM

Rapid Response Codes are a kind of digital bar code that are becoming more and more popular since they can store a lot of data fast and in big quantities. This research aims to design a device for collecting attendance data using QR codes. This QR code contains information about the user's identity and location when used. We may determine the user's distance from the designated area using this location data. This location information is used to find out how far the user is from the area we have set.The presence method used the ESP Cam device to scan a QR code from the user which contains information on student identification number, date and location (latitude and longitude).Before scanning the QR code, users must confirm via the Telegram application which has been prepared in advance to carry out the attendance process at each class session.Ifthe information matches that is stored in the database and the user's location is still within the radius of the reader device, the user's identity data is then uploaded to the online presence system.After the hardware and software have been prepared, it continues with testing on Electrical Engineering students at Muhammadiyah University of Surakarta as attendance at the Electrical Engineering Laboratory.Scanning this QR code takes an average reading time of 3.5 seconds with the fastest estimated time being 3 seconds and the longest 5 seconds.