Control Points Research Articles

Vendor Return Process for Indirect Materials in Extended Warehouse Management: Configuration and Implementation

The vendor return process in Extended Warehouse Management (EWM) presents significant challenges for supply chain operations, particularly for indirect materials. This article explores the configuration requirements and implementation strategies necessary for optimizing return workflows within EWM systems. Beginning with purchase order configuration and the critical role of confirmation control keys, the discussion progresses through inbound delivery creation, goods receipt processes, return categorization mechanisms, and post-receipt handling procedures. The examination of these interconnected components reveals how proper system configuration directly impacts inventory accuracy, processing efficiency, and financial outcomes. Through structured implementation approaches focusing on specific control points, organizations can achieve substantial improvements in return processing while reducing operational costs. The integration between EWM and inventory management systems emerges as a crucial factor in successful return management, with specialized reason codes and movement types serving as essential elements in the configuration framework.

Enhanced APT detection with the improved KAN algorithm: capturing interdependencies for better accuracy

In real-world network environments, advanced persistent threats (APTs) are characterized by their complexity and persistence. Existing APT detection methods often struggle to comprehensively capture the complex and dynamic network relationships and covert attack patterns involved in the attack process, and they also suffer from insufficient detection effectiveness. To address this, we propose a model that combines bidirectional dynamic graph attention with the improved KAN network. The improved KAN model smoothly connects control points by using the interpolation properties of the Catmull–Rom spline function. This model also combines the feature extraction capabilities of graph neural networks with a bidirectional dynamic graph attention mechanism. By dynamically updating the states of network nodes, it captures multi-step, cross-node, and highly covert attack features in APT attacks. Experimental results show that this method achieves an accuracy of 97.10% in APT attack detection, with false positive and false negative rates of 0.2% and 9.02%, respectively. The effectiveness of the model in extracting complex behavioral features of APT attacks has been validated, providing a reliable solution for APT detection in complex network environments.

Energy Saving in Building Air-Conditioning Systems Based on Hippopotamus Optimization Algorithm for Optimizing Cooling Water Temperature

When traditional HVAC (heating, ventilation, and air-conditioning) systems are in operation, they often run according to the designed operating conditions. In fact, they operate under part-load conditions for more than 90% of the time, resulting in energy waste. Therefore, studying the optimization and regulation of their operating conditions during operation is necessary. Given that the control set point for cooling tower outlet water temperature differentially impacts chiller and cooling tower energy consumption during system operation, optimization of this parameter becomes essential. Therefore, this study focuses on optimizing the cooling tower outlet water temperature control point in central air-conditioning systems. We propose the Hippopotamus Optimization Algorithm (HOA), a novel population-based approach, to optimize cooling tower outlet water temperature control points for energy consumption minimization. This optimization is achieved through a coupled computational methodology integrating building envelope dynamics with central air-conditioning system performance. The energy consumption of the cooling tower was analyzed for varying outlet water temperature set points, and the differences between three control strategies were compared. The results showed that the HOA strategy successfully identifies an optimized control set point, achieving the lowest combined energy consumption for both the chiller and cooling tower. The performance of HOA is better compared to other algorithms in the optimization process. The optimized fitness value is minimal, and the function converges after five iterations and completes the optimization in a single time step when run in MATLAB in only 1.96 s. Compared to conventional non-optimized operating conditions, the HOA strategy yields significant energy savings: peak daily savings reach 4.5%, with an average total daily energy reduction of 3.2%. In conclusion, this paper takes full account of the mutual coupling between the building and the air-conditioning system, providing a feasible method for the simulation and optimization of the building air-conditioning system.

Mesh-based simulation of knitted dresses with loop units

The three-dimensional simulation of knitted garments is an integral part of the three-dimensional visualization of textile garments. To realize the three-dimensional structure simulation and dressing simulation of knitted dresses, this paper proposes a fast three-dimensional simulation method of knitted dresses based on mesh division and loop units. Based on studying the process characteristics of knitted dresses, the dress pattern is quantified and meshed, and the loop unit’s geometric and mesh models are established. The spatial matrix is used to calculate the spatial transformation relationship of each pair of triangles in the flat model and surface model of the dress, and the spatial transformation relationship is used to calculate the position of the loop mesh point in the triangular mesh of the surface model, the three-dimensional coordinates of the loop unit control point are obtained, and the loop is drawn. Based on C# technology, the model data of the personalized human body model and knitted dress are read, and the three-dimensional graphics library OpenGL and loop drawing method are used to realize the three-dimensional simulation of the knitted dress based on loop structure. The simulation effect of a V-neck dress and high-neck dress under different particle spacing is used as an example to test the simulation method. The results show that when the mesh of the dress model is divided under the particle spacing of 20 mm, the three-dimensional simulation of the dress based on the loop unit can be realized quickly and with high quality.

Surveillance of Antimicrobial Resistance in the Asian Seabass (Lates calcarifer) Supply Chain Using Nanopore Sequencing

Intensive fish farming worldwide has increased reliance on antibiotics to control bacterial pathogens, raising concerns about antimicrobial resistance (AMR) in aquaculture. These resistant bacteria can persist and pass through the food supply chain, from farms to consumers. Despite this risk, antimicrobial resistance genes (ARGs) in aquaculture environments and fish products have not been elucidated. This study aimed to detect ARGs found in the Asian seabass (Lates calcarifer), an economically important fish in Thailand, collected from farms, fish container vehicles, and markets, using Nanopore metagenomic sequencing. We detected multiple ARGs in all sample types. Water samples harbored the rpsL gene conferring streptomycin resistance. Container samples exhibited the highest diversity of ARGs, including multiple beta-lactamases and the rsmA gene, conferring resistance to fluoroquinolones, diaminopyrimidines, and phenicol antibiotics. Fish samples generally lacked ARGs, except for one sample harboring rsmA. Non-metric multidimensional scaling revealed distinct microbial communities in water, compared with those found in container and fish samples, indicating potential cross-contamination during handling or storage. Our findings emphasize that containers could be critical control points for minimizing AMR spread. Overall, this study highlights the interconnection between environmental, fish, and human health, highlighting the importance of integrated AMR surveillance and management in aquaculture systems.

Multi-Level Particle System Modeling Algorithm with WRF

In the fields of meteorological simulation and computer graphics, precise simulation of clouds has been a recent research hotspot. The existing cloud modeling methods often ignore the differentiated characteristics of cloud layers at different heights, and suffer from high computational costs under long-range conditions, making them unsuitable for large-scale scenes. Therefore, we propose a multi-level particle system 3D cloud modeling algorithm based on the Weather Research and Forecasting Model (WRF), which combines particle weight adjustment with a Proportional Integral Derivative (PID) feedback mechanism to represent cloud features of different heights and types. Based on the multi-scale mean-shift clustering algorithm, Adaptive Kernel Density Estimation (AKDE) is introduced to map density to bandwidth, achieving adaptive adjustment of clustering bandwidth while reducing computational resources and improving cloud hierarchy. Meanwhile, selecting the optimal control points based on the correlation between particle density in the edge region and cloud contour can ensure the integrity of the internal structure of the cloud and the clarity of the external contour. To improve modeling efficiency, cascade Bezier curves are designed at different line-of-sights (LoSs), utilizing the weight information of boundary particles to optimize cloud contours. Experimental results show that, compared with similar algorithms, our algorithm reduces the average running time by 37.5%, indicating enhanced computational efficiency and real-time capability, and the average number of required particles by 30.1%, reducing the cost of long-range computing. Our algorithm can fully demonstrate cloud characteristics and interlayer differences, significantly improve modeling efficiency, and can be used for accurate modeling of large-scale cloud scenes, providing strong support for meteorological and climate prediction.

Hybrid Path Planning Method for USV Based on Improved A-Star and DWA

This paper presents a hybrid path planning method that integrates an enhanced A-Star algorithm with the Dynamic Window Approach (DWA). The proposed approach addresses the limitations of conventional A-Star algorithms in global path planning, particularly their inability to adaptively avoid obstacles in real-time. To improve navigation safety, the A-Star search strategy is enhanced by avoiding paths that intersect with obstacle vertices or pass through narrow channels. Additionally, a node optimization technique is introduced to remove redundant nodes by checking for collinearity in consecutive nodes. This optimization reduces the path length and ensures that the path maintains a safe distance from obstacles using parallel lines. An advanced Bézier curve smoothing method is also proposed, which adaptively selects control points to improve path smoothness and driving stability. By incorporating these improvements, the enhanced A-Star algorithm is combined with DWA to facilitate dynamic obstacle avoidance while generating global paths. The method accounts for the kinematic characteristics of the USV, as well as physical constraints such as linear and angular velocities, enabling effective handling of obstacles in dynamic environments and ensuring safe navigation. Simulation results demonstrate that the proposed algorithm generates secure global paths, significantly optimizing node count, path length, and smoothness, while effectively avoiding dynamic obstacles, thus ensuring safe navigation of the USV.

Longitudinal optical trapping and manipulation of multiple particles via structured optical coherence

Flexible beam shaping is crucial for enhancing the versatility of optical manipulation. Structured optical coherence enables focused light beams to exhibit multiple controllable focal points along the longitudinal direction, making them ideal for longitudinal optical trapping and manipulation. By controlling the longitudinal intensity distribution, these beams can trap and manipulate multiple particles simultaneously along the same axis. This demonstrates the feasibility of using optical coherence engineering for longitudinal multi-particle trapping and manipulation, thereby expanding the control capabilities beyond traditional optical tweezers.

Monitoring Fast-Growing Megacities in Emerging Countries Through the PS-InSAR Technique: The Case of Addis Ababa, Ethiopia

In the past three decades, the city of Addis Ababa, a capital city of Africa, has grown significantly in population, facilities, and infrastructure. The area involved in the recent urbanization is prone to slow natural subsidence phenomena that can be accelerated due to anthropogenic factors such as groundwater overexploitation and loading of unconsolidated soils. The main aim of this study is to identify and monitor the areas most affected by subsidence in a context, such as that of many areas of emerging countries, characterized by the lack of geological and technical data. In these contexts, advanced remote sensing techniques can support the assessment of spatial and temporal patterns of ground instability phenomena, providing critical information on potential conditioning and triggering factors. In the case of subsidence, these factors may have a natural or anthropogenic origin or result from a combination of both. The increasing availability of SAR data acquired by the Sentinel-1 mission around the world and the refinement of processing techniques that have taken place in recent years allow one to identify and monitor the critical conditions deriving from the impressive recent expansion of megacities such as Addis Ababa. In this work, the Sentinel-1 SAR images from Oct 2014 to Jan 2021 were processed through the PS-InSAR technique, which allows us to estimate the deformations of the Earth’s surface with high precision, especially in urbanized areas. The obtained deformation velocity maps and displacement time series have been validated using accurate second-order geodetic control points and compared with the recent urbanization of the territory. The results demonstrate the presence of areas affected by a vertical rate of displacement of up to 21 mm/year and a maximum displacement of about 13.50 cm. These areas correspond to sectors that are most predisposed to subsidence phenomena due to the presence of recent alluvial deposits and have suffered greater anthropic pressure through the construction of new buildings and the exploitation of groundwater. Satellite interferometry techniques are confirmed to be a reliable tool for monitoring potentially dangerous geological processes, and in the case examined in this work, they represent the only way to verify the urbanized areas exposed to the risk of damage with great effectiveness and low cost, providing local authorities with crucial information on the priorities of intervention.

An Analysis of Powder, Hard-Packed, and Wet Snow in High Mountain Areas Based on SAR, Optical Data, and In Situ Data

The following study presents the results obtained from a comparative analysis of dry (powder and hard snow) and wet snow based on satellite data and in situ data methods for monitoring in the high mountain belt of Bulgaria. The aim of the study is to analyze the effectiveness of different spectral indices based on satellite data from Synthetic Aperture Radar (SAR), high-resolution (HR) imagery, and spectrometer data for assessing the state and dynamics of the snow cover. The methods studied and the results obtained were validated by instrument-based field observations, with instruments using thermal imaging cameras, spectrometer measurements, ground control points, and HR imagery. Satellite data offer an ever-widening view of trends in snow distribution over time. All these data combined provide a detailed picture of surface temperature and snow properties, which are crucial for understanding snowmelt processes and the energy balance in the high-altitude belt. The findings suggest that a multi-method approach, utilizing the combined advantages of SAR satellite data, offers the most comprehensive and accurate framework for satellite-based snow cover monitoring in the high mountain regions of Bulgaria, such as Rila Mountain. This integrative strategy not only improves the precision of snow cover estimates but can also support many water resource-related studies, such as snowmelt runoff studies, snow avalanche modeling, and better-informed decisions in the management and maintenance of winter tourism resorts.

ASSESSMENT OF THE COMPETENCE OF DEPARTMENTAL LABORATORIES OF ENTERPRISES FOR QUALITY CONTROL OF PRODUCTS FOR VETERINARY MEDICINE BY THE LEVEL OF COMPLIANCE WITH REGULATORY REQUIREMENTS REGULATING THEIR ACTIVITIES

The quality of research (tests) conducted by departmental laboratories of veterinary medicine enterprises to confirm the quality of products, in particular veterinary drugs, feed additives, concerns not only the well-being of livestock and poultry farming, but also human health and ensuring environmental safety. Therefore, the regulatory provisions enshrined in the Law of Ukraine “On Veterinary Medicine”, DSTU ISO/IEC-17025 (2019) regulate specific measures to improve the work of testing laboratories, including products for veterinary medicine and animal husbandry. It should be borne in mind that the quality of preventive and therapeutic measures depends not only on the quality of the direct implementation of these measures, but primarily on the quality of medicines, feed additives, which are already used in clinical and diagnostic practice. Accordingly, this work should focus on ensuring guarantees of the reliability of research (tests) carried out by product quality control laboratories, in particular departmental laboratories of veterinary medicine enterprises, through strict compliance with the normative and regulatory requirements of their work, which should be reflected in the quality guidelines as a guiding document for the provision of testing services. And perhaps the main priority in their activities should be specifically fixed personal responsibility of both the manager and each laboratory employee for impeccable objectivity in conducting research (tests) of products on quality indicators, as well as the responsibility of employees of enterprises who select and deliver product samples from control points according to production technology or suppliers of the relevant pharmaceutical raw materials. Accordingly, the requirements for the qualification of employees of the departmental laboratory should be approved in accordance with the established procedure. As for the competence of departmental laboratories to conduct research (testing) of products for veterinary medicine and animal husbandry for quality, according to the Regulation on the Institute, confirmation of the competence of such laboratories is entrusted to the State Committee for Veterinary Medicine and Feed Additives. Confirmation of the competence of laboratories certifies its capabilities for research (testing) of products manufactured by veterinary medicine enterprises, which are their priority, namely: – official recognition of the level of quality, conformity and competence; – guarantees of the reliability of research (testing) of products; – minimizing the possibility of obtaining and issuing erroneous results; – participation in the development and implementation of a comprehensive product quality management system at the enterprise. It is characteristic that the requirements for laboratory competence should be implemented in the practice of its work not chaotically, but logically, consistently and completely, reflecting the full life cycle of conducting research (testing) of products for quality.

DNA Replication in Time and Space: The Archaeal Dimension

The ability of a nucleic acid molecule to self-replicate is the driving force behind the evolution of cellular life and the transition from RNA to DNA as the genetic material. Thus, the physicochemical properties of genome replication, such as the requirement for a terminal hydroxyl group for de novo DNA synthesis, are conserved in all three domains of life: eukaryotes, bacteria, and archaea. Canonical DNA replication is initiated from specific chromosomal sequences termed origins. Early bacterial models of DNA replication proposed origins as regulatory points for spatiotemporal control, with replication factors acting on a single origin on the chromosome. In eukaryotes and archaea, however, replication initiation usually involves multiple origins, with complex spatiotemporal regulation in the former. An alternative replication initiation mechanism, recombination-dependent replication, is observed in every cellular domain (and viruses); DNA synthesis is initiated instead from the 3′ end of a recombination intermediate. In the domain archaea, species including Haloferax volcanii are not only capable of initiating DNA replication without origins but grow faster without them. This raises questions about the necessity and nature of origins. Why have archaea retained such an alternative DNA replication initiation mechanism? Might recombination-dependent replication be the ancestral mode of DNA synthesis that was used during evolution from the primordial RNA world? This review provides a historical overview of major advancements in the study of DNA replication, followed by a comparative analysis of replication initiation systems in the three domains of life. Our current knowledge of origin-dependent and recombination-dependent DNA replication in archaea is summarised.

Moving Sounds Increase Postural Visual Dependence in Adults With Chronic Traumatic Brain Injury.

This cross-sectional study aimed to (1) establish the safety and tolerability of head-mounted display (HMD) assessment of sensory integration for postural control in participants with chronic traumatic brain injury (TBI); (2) investigate whether responses to visual and auditory cues differ between persons with TBI and healthy controls; and (3) evaluate the relationship between postural responses, postural visual dependence, and self-reported perception of disability. 20 healthy adults and 19 participants with TBI completed an HMD assessment of with visual and auditory perturbations. Head sway was quantified as a directional path in the anteroposterior and mediolateral directions. Participants also completed the Simulator Sickness Questionnaire (SSQ) and the Dizziness Handicap Inventory (DHI). All participants completed testing. The average change in SSQ scores from pre to post postural control assessment was 0.8 points for healthy controls and 3.2 points for participants with TBI. Head sway in the TBI group was consistently higher in both directions, especially with dynamic visuals. In addition, a significant sound by visual by group interaction in the mediolateral direction indicates that participants with TBI responded more to the visual perturbations when sounds were present. Under the most challenging conditions, people with mild-to-moderate dizziness handicap showed little head sway, while those with severe symptoms were more variable. HMD assessment of participants with TBI is feasible and provides a clinic-based assessment of postural visual dependence in this population. This assessment carries the potential to evaluate postural control and monitor progress of participants with TBI.

Stress-Responsive Spatial Voronoi Optimization for Lightweight Architectural Shell Structures

Gradient porous structures (GPS) offer significant mechanical and functional advantages over homogeneous counterparts. This paper proposes a computational design framework utilizing spatial Voronoi diagrams to create lightweight, stress-responsive spatial frames optimized for architectural double-curvature arched shell roofing components. The method integrates Solid Isotropic Material with Penalization (SIMP)-based topology optimization (TO) to establish initial stress-informed material distributions, adaptive Voronoi control point (CP) placement guided by localized stress data, and a bi-objective genetic algorithm (GA) optimizing maximum and average displacement. Following optimization, a weighted Lloyd relaxation (LR) refines Voronoi cells into spatial frameworks with varying densities corresponding to stress gradients. Finite Element Analysis (FEA) demonstrates that the optimized Voronoi-driven GPS achieves notable improvements, revealing up to 79.7% material volume reduction and significant improvement in structural efficiency, achieving a stiffness-to-weight ratio (SWR) exceeding 2200 in optimized configurations. Furthermore, optimized structures consistently maintain maximum von Mises (MVM) stresses below 20 MPa, well within the allowable yield strength of the Polyethylene Terephthalate Glycol (PETG) material (53 MPa). The developed framework effectively bridges structural performance, material efficiency, and aesthetic considerations, offering substantial potential for application in advanced, high-performance architectural systems.

Soil Fertility after an Oil Pipeline Spill in Niger Delta, Nigeria

Studies on soil fertility were carried out following an oil spill incidence caused by crude oil theft at Ahoada East in the Niger Delta region of Nigeria. The objective was to evaluate the state of soil fertility in the affected area which is crucial for developing effective remediation strategies to restore soil health and support sustainable agricultural practices in Ahoada. Soil samples were collected from both oil-impacted and non-impacted control sites, at two depths (0-15cm and 15-30cm), using a stainless-steel auger. Subsequently, laboratory analyses were conducted to evaluate pH, electrical conductivity, chloride, and concentrations of the selected micronutrients such as iron (Fe), manganese (Mn), zinc (Zn), and copper (Cu); and primary macronutrients such as nitrogen (N), phosphorus (P) and potassium (K). Other fertility indicators like Organic carbon and organic matter were also evaluated. Findings revealed a notable decrease in essential nutrients, particularly Cu, Zn, and Mn. The pH values for the contaminated soils varied between 5.3 and 6.65, while the electrical conductivity (EC) ranged from 9 to 48 µS/cm. These and other key indicators were higher in the control soils. However, total organic matter (TOM) ranged from 1.04-12.62% in the contaminated soils, while the control point ranged from 0.86-2.42%, indicating a decrease in TOM. These conditions generally imply low soil fertility, which in turn implies low agricultural productivity and reduced source of livelihood in the affected area. To restore the contaminated area and sustain agricultural productivity, there is need for immediate and efficient clean up exercise, beyond the sand filling observed at the site. The soil-pH should be adjusted to a range of 6.0 – 6.5 by the addition of calcitic lime, followed by the application of appropriate and sufficient inorganic N-P-K fertilizer to restore the carbon to nutrient ratios to the optimum level required to stimulate and sustain microbial activity.

Levels and transport behavior of ionic per- and polyfluoroalkyl substances in the atmosphere of urban pollution scenario: An in-situ investigation of a wastewater treatment plant in Wuxi, China.

Levels and transport behavior of ionic per- and polyfluoroalkyl substances in the atmosphere of urban pollution scenario: An in-situ investigation of a wastewater treatment plant in Wuxi, China.

Bridging Gaps in Satellite Observations of River and Delta Landscapes Using Image Warping

AbstractSatellite images are increasingly used to monitor changes in fluvial landscapes such as channel migration, bar development, and avulsion. Yet, spatial and temporal gaps in image data — due to intervals between observations, cloud cover, or sensor malfunctions — limit their applicability. This study tests whether image warping, a well‐established technique that generates smooth transitions between images, can bridge these gaps in observations of fluvial landscapes. The approach applies several steps to satellite images: (a) creating channel masks, (b) delineating channel topology, (c) correlating topologic components and defining control points, (d) calculating transformations between image pairs using control points, and (e) warping channel masks based on these transformations. This approach produces intermediate channel configurations from pairs of input images. We apply this technique to two case studies: the rapidly migrating Ucayali River in Peru and the actively prograding Wax Lake Delta in Louisiana. The reconstructions show channel migration and/or progradation that are consistent with actual observations, indicating reasonable estimates to fill gaps between satellite observations. Importantly, the accuracy of the reconstructions depends on the careful selection of the input images to avoid abrupt geomorphic changes that could compromise the warping process. By combining the surface reconstruction for the Ucayali River with a simple model for channel and floodplain aggradation, we construct a stratigraphic model directly informed by the satellite observations. These case studies suggest that applying image warping to Earth‐surface observations has the potential to overcome gaps in satellite data availability and translate observations directly to models for fluvio‐deltaic stratigraphy.

Application of an updated methodology to estimate the burden of healthcare-associated infections in Italy, 2022.

BackgroundAccurate burden estimates are necessary to inform priority setting and rational resource allocation. Weighting prevalence inversely proportional to time-at-risk has been proposed as a solution for length-biased sampling, an important limitation affecting prevalence to incidence conversion for healthcare-associated infections (HAIs).AimThis study aimed to update Italian burden estimates by calculating HAI incidence, attributable mortality and disability-adjusted life years (DALYs). Further, we describe an adapted methodology for burden estimations.MethodsWe used data from the latest European Centre for Disease Prevention and Control (ECDC) point prevalence survey (PPS) of HAIs, conducted in Italy in November 2022, to calculate the burden of five major HAIs at national level. We adapted the Burden of Communicable Diseases in Europe (BCoDE) methodology to include inverse probability weighting and compared results of naïve and weighted calculations.ResultsThe national sample included 18,397 patients. Overall, 564.8 DALYs per 100,000 general population resulted from weighted calculations (95% uncertainty interval (UI): 450.04-694.38), with an annual incidence of 685.42 cases per 100,000 general population (95% UI: 611.09-760.86) and 33.23 deaths per 100,000 general population per year (95% UI: 28.62-38.33). Concerning naïve estimates, overall 1,017.81 DALYs per 100,000 general population were calculated (95% UI: 855.16-1,190.59). In both calculations, healthcare-acquired bloodstream infections had the highest burden in terms of DALYs per 100,000 hospitalised and general population.ConclusionOur study confirmed the substantial burden of HAIs in Italy and renews the need to prioritise resources for infection prevention and control interventions.

Testing Program Critical Control Points (TP-CCP): characterizing and optimizing decision-making power in food safety testing.

Foodborne illness affects 48 million people annually in the U.S., resulting in 128,000 hospitalizations and 3,000 deaths, and an estimated economic burden of $17.6 billion. To address this important public health issue, ongoing industry efforts have been undertaken to promote a proactive food safety culture that focuses on prevention-based approaches to food safety. In the 1960s, Good Manufacturing Processes (GMPs) and Hazard Analysis and Critical Control Points (HACCP) were introduced to provide a systematic process to identify and mitigate physical, chemical, and biological risks, and quickly became standard components of a comprehensive quality and food safety program. In 2011, the Food Safety Modernization Act (FSMA) introduced Hazard Analysis and Risk-Based Preventative Controls (HARPC), an expansion of HACCP to products regulated by the United States Food and Drug Administration. This article proposes a complementary program using the HACCP/HARPC construct for the systematic characterization and assessment of analytical tools used in monitoring critical steps in food processes. The Testing Program Critical Control Point (TP-CCP) framework extends the comprehensive HACCP/HARPC model to microbiological monitoring programs (e.g., sampling, testing methodology) to define the theoretical operating limits and realized performance of testing systems. TP-CCP identifies risk mitigation opportunities, supports broad prevention-based control efforts, and establishes a missing feedback loop for continuous improvement in food safety. The proposed TP-CCP ensures a robust network that the food industry can use to obtain a more efficient and reliable testing system to advance public health.

Molecular detection of Leptospira spp. in goat's milk produced in a semiarid region.

Molecular detection of Leptospira spp. in goat's milk produced in a semiarid region.