Abstract Japanese cedar pollen (Cryptomeria japonica) is a major cause of seasonal allergic rhinitis in Japan, and Cry j 1 has been identified as its principal allergen. Although current treatments provide symptomatic relief, they do not prevent sensitization, highlighting the need for novel preventive strategies. Nanosized electrostatically atomized water particles (NEAWPs) are nanometer-scale water droplets containing reactive oxygen species (ROS) that have demonstrated antimicrobial activity; however, their effects on airborne allergens remain unclear. Therefore, this study investigated whether NEAWPs could reduce the allergenicity of Cry j 1 in human bronchial epithelial cells (BEAS-2B) and monocytic antigen-presenting cells (THP-1). Briefly, Cry j 1 was exposed to NEAWPs for 24–48 h, and allergenicity was assessed by ELISA, calcium imaging, flow cytometry, and cytokine analyses. NEAWPs treatment markedly reduced Cry j 1 antigenicity in a time-dependent manner, achieving 98.6% reduction after 48 h. In BEAS-2B cells, untreated Cry j 1 induced significant Ca²⁺ influx and upregulated IL-8, TNF-α, and IL-6 expression, whereas NEAWP-treated Cry j 1 failed to elicit these responses. Similarly, in THP-1 cells, NEAWP-treated Cry j 1 decreased CD11c+CD86+ cells and inflammatory cytokine production. These results indicate that NEAWPs denature Cry j 1, preventing epithelial activation and antigen presentation, thereby attenuating downstream immune responses. This study provides the first evidence that NEAWPs can effectively reduce the allergenicity of Japanese cedar pollen, suggesting a potentially non-invasive, environmentally friendly approach for allergy prevention. Therefore, future studies are required to explore the molecular mechanisms, in vivo efficacy, and safety of NEAWPs exposure to establish its translational potential in managing pollinosis and other airborne allergies.
Low temperature engineering. Cryogenic engineering. Refrigeration
The application of latent thermal energy storage with heat pumps has been extensively studied in recent years. The combination of phase change heat storage and a heat pump can improve the performance of the heat pump and the utilization of renewable energy; however, further cost reduction and efficiency increase are required. Therefore, this study reviews the progress of heat pumps coupled with solid-liquid phase change materials and summarizes the applicable conditions and characterization methods for phase change materials applied to heat pumps. The optimization approaches for the performance of the heat pump system are summarized, including the selection and improvement of phase change materials, the optimal setting of the heat exchanger, and the dynamic optimization control strategy of the system. The outstanding performance of heat pumps with cascade heat storage in improving the supply-side comfort and utilization rate of renewable energy indicates the broad prospect of cascade heat storage being applied to heat pump energy storage systems. Herein, mixed, non-eutectic phase change materials are proposed as alternative materials for cascade heat storage. Notably, summarizing and developing new methods for adjusting the thermophysical properties of phase change materials for energy storage is necessary for adapting the selection and improvement of phase change materials to the optimization of the thermodynamic cycle of cascade heat storage devices and further improving the heating decarbonization ability of latent heat storage heat pumps.
Heating and ventilation. Air conditioning, Low temperature engineering. Cryogenic engineering. Refrigeration
Recent advances in code generation models have demonstrated impressive capabilities in automating software development tasks, yet these models still struggle in real-world software engineering scenarios. Although current training methods, particularly post-training, excel at solving competitive programming problems, they fail to adequately prepare models for the complexities of practical software development. This misalignment raises the critical question: Are existing alignment training methods well suited for real-world software engineering tasks? In this study, we identify this issue and propose SEAlign, a novel alignment framework designed to bridge the gap between code generation models and real-world software development tasks. SEAlign leverages the unique characteristics of software engineering processes, including high-quality workflow steps, to enhance model capabilities. Our framework further employs Monte Carlo Tree Search for fine-grained alignment in multi-step decision processes, followed by preference optimization on critical actions to ensure models meet real-world requirements. We evaluate SEAlign on three standard agentic benchmarks for real-world software engineering, including HumanEvalFix, SWE-Bench-Lite, and SWE-Bench-Verified. Experimental results demonstrate state-of-the-art performance with minimal training overhead. In addition, we develop an agent-based software development platform using SEAlign, which successfully automates the creation of several small applications. Human evaluations of these applications highlight significant improvements in both task performance and user experience. Our findings underscore the potential of SEAlign to accelerate the adoption of large code models in real-world software development. We believe that this research makes a meaningful step towards fully automated software engineering.
Omitted variable bias occurs when a statistical model leaves out variables that are relevant determinants of the effects under study. This results in the model attributing the missing variables' effect to some of the included variables -- hence over- or under-estimating the latter's true effect. Omitted variable bias presents a significant threat to the validity of empirical research, particularly in non-experimental studies such as those prevalent in empirical software engineering. This paper illustrates the impact of omitted variable bias on two illustrative examples in the software engineering domain, and uses them to present methods to investigate the possible presence of omitted variable bias, to estimate its impact, and to mitigate its drawbacks. The analysis techniques we present are based on causal structural models of the variables of interest, which provide a practical, intuitive summary of the key relations among variables. This paper demonstrates a sequence of analysis steps that inform the design and execution of any empirical study in software engineering. An important observation is that it pays off to invest effort investigating omitted variable bias before actually executing an empirical study, because this effort can lead to a more solid study design, and to a significant reduction in its threats to validity.
We construct a quantum critical Otto engine that is powered by finite temperature baths. We show that the work output of the engine shows universal power law behavior that depends on the critical exponents of the working medium, as well as on the temperature of the cold bath. Furthermore, higher temperatures of the cold bath allows the engine to approach the limit of adiabatic operation for smaller values of the time period, while the corresponding power shows a maximum at an intermediate value of the cold bath temperature. These counterintuitive results stems from thermal excitations dominating the dynamics at higher temperatures.
Marcos Kalinowski, Daniel Mendez, Görkem Giray
et al.
Context: Machine learning (ML)-enabled systems are being increasingly adopted by companies aiming to enhance their products and operational processes. Objective: This paper aims to deliver a comprehensive overview of the current status quo of engineering ML-enabled systems and lay the foundation to steer practically relevant and problem-driven academic research. Method: We conducted an international survey to collect insights from practitioners on the current practices and problems in engineering ML-enabled systems. We received 188 complete responses from 25 countries. We conducted quantitative statistical analyses on contemporary practices using bootstrapping with confidence intervals and qualitative analyses on the reported problems using open and axial coding procedures. Results: Our survey results reinforce and extend existing empirical evidence on engineering ML-enabled systems, providing additional insights into typical ML-enabled systems project contexts, the perceived relevance and complexity of ML life cycle phases, and current practices related to problem understanding, model deployment, and model monitoring. Furthermore, the qualitative analysis provides a detailed map of the problems practitioners face within each ML life cycle phase and the problems causing overall project failure. Conclusions: The results contribute to a better understanding of the status quo and problems in practical environments. We advocate for the further adaptation and dissemination of software engineering practices to enhance the engineering of ML-enabled systems.
Large Language Models (LLMs) like GPT-3 and GPT-4 have emerged as groundbreaking innovations with capabilities that extend far beyond traditional AI applications. These sophisticated models, trained on massive datasets, can generate human-like text, respond to complex queries, and even write and interpret code. Their potential to revolutionize software development has captivated the software engineering (SE) community, sparking debates about their transformative impact. Through a critical analysis of technical strengths, limitations, real-world case studies, and future research directions, this paper argues that LLMs are not just reshaping how software is developed but are redefining the role of developers. While challenges persist, LLMs offer unprecedented opportunities for innovation and collaboration. Early adoption of LLMs in software engineering is crucial to stay competitive in this rapidly evolving landscape. This paper serves as a guide, helping developers, organizations, and researchers understand how to harness the power of LLMs to streamline workflows and acquire the necessary skills.
In this 4-page manuscript we discuss the problem of long-term AI Safety from a Software Engineering (SE) research viewpoint. We briefly summarize long-term AI Safety, and the challenge of avoiding harms from AI as systems meet or exceed human capabilities, including software engineering capabilities (and approach AGI / "HLMI"). We perform a quantified literature review suggesting that AI Safety discussions are not common at SE venues. We make conjectures about how software might change with rising capabilities, and categorize "subproblems" which fit into traditional SE areas, proposing how work on similar problems might improve the future of AI and SE.
System performances with different packings (wire mesh corrugated, metal hole plate, ceramic corrugated, paper wet curtain, and plastic S-type) were examined to study the effect of packing on the performance of ice slurry wet pre-cooling systems. Key indicators are the temperature and humidity in the pre-cooling room, the pre-cooling process duration, the temperature variation coefficient, and the weight loss rate. The results showed that the final temperature of the circulating air in the precooling room could reach -1 ℃ with all types of packing, and the relative humidity of the air could be stabilized above 90%, meeting the precooling process requirements of pleurotuseryngii. When the ceramic corrugated and paper wet curtain packings were used in the pre-cooling room, the temperature variation coefficients were 0.26% and 0.28%, respectively, which are significantly less than the other packings (P<0.05), indicating that the pre-cooling of pleurotuseryngii was more uniform. When the wire mesh corrugated packing was used in the pre-cooling room, the pre-cooling process duration was significantly less than the other four packings (P<0.05), which was 70.2 min. When the wire mesh corrugated packing and metal hole plate were used in the precooling room, their weight losses were significantly lower than the other three packings (P<0.05), which were 2.65% and 2.85%, respectively, indicating that the weight loss of pleurotuseryngii was smaller than the others.
Heating and ventilation. Air conditioning, Low temperature engineering. Cryogenic engineering. Refrigeration
These thoughts are offered as a reminder that Tribology is not all about the normal contact of fractal surfaces, and indeed, not all about elastic contact of rubber and polymers, or even about dry contact. Machines do still contain metal surfaces sliding past each other, hopefully separated by an oil film; and sometimes, when tolerances have been pushed too far, or running with starved lubrication when the oil or grease supply is inadequate, with somemetal tometal contact. Fortunately this is not always disastrous: surfaces do often run-in, so that after running with contact and a contribution of dry-contact friction, there is steady wear and contacts no longer occur. The traditional design criterion for gears and ball races was, and still is, the 3 − ratio: the ratio of the predicted film thickness for smooth surfaces to the rms roughness. Certainly a3−ratio of 3 ormore1 usually leads to full-film lubrication: but to anyone with the slightest background in surface roughness this is an absurd rule. Assuming, as is usually done, that the predicted smooth-surface film thickness refers to the distance between the mean planes of the roughness, the rms roughness says nothing about the how much contact there will be. And if running-in is successful, and the high points of the surface wear away, the rms (and the 3 − ratio) may hardly change, but there will be successful operation. But when will running-in be successful? What determines when instead of running-in there will be scuffing, and disaster? The traditional picture of the “mixed friction” regime is that when the local film thickness falls to zero, additives (or perhaps happy accidents) provide a boundary lubricant in the oil: some form of long chain polymer, which has a reactive end which attaches itself to the metal, and carries the load on its free ends: with low friction but, more importantly, preventing metal to metal contact. The Blok scuffing criterion was that the maximum surface temperature must be below a specific value: and there was the problem, what should it be? In Bowden and Tabor’s laboratory experiments, using a known, pure, organic compound, clear links with the known properties could be found; but in engineering practice perhaps all that can be done is to ensure that the calculated maximum temperature in a new application is no more than in an existing application: the ISO guide concentrates on the temperature calculation, not on the temperature found. But what happens when boundary lubrication fails? Fortunately it seems that we do not move completely into the dry wear scenario. The failure will usually be local, and the dry wear process interrupted. An earlier work (Sakmann et al., 1944) reported that in a pin on disc experiment, flooding the surface with a plain mineral oil halved the transfer at a light load, but produced only a small reduction at a heavier load. But flooding with oleic acid largely eliminated transfer. Here it seems desirable to review what has been learnt about dry wear, and perhaps, forgotten.
Industrial applications involving formal methods are still exceptions to the general rule. Lack of understanding, employees without proper education, difficulty to integrate existing development cycles, no explicit requirement from the market, etc. are explanations often heard for not being more formal. This article reports some experience about a game changer that is going to seamlessly integrate formal methods into safety critical systems engineering.
Thermal processes are one of the most common systems in the industry, making its understanding a mandatory skill for control engineers. So, multiple efforts are focused on developing low-cost and portable experimental training rigs recreating the thermal process dynamics and controls, usually limited to SISO or low order 2x2 MIMO systems. This paper presents PHELP, a low-cost, portable, and high order MIMO educational platform for uniformity temperature control training. The platform is composed of an array of 16 Peltier modules as heating elements, with a lower heating and cooling times, resulting in a 16x16 high order MIMO system. A low-cost real-time infrared thermal camera is employed as a temperature feedback sensor instead of a standard thermal sensor, ideal for high order MIMO system sensing and temperature distribution tracking. The control algorithm is developed in Matlab/Simulink and employs an Arduino board in hardware in the loop configuration to apply the control action to each Peltier module in the array. A temperature control experiment is performed, showing that the platform is suitable for teaching and training experiences not only in the classroom but also for engineers in the industry. Furthermore, various abnormal conditions can be introduced so that smart control engineering features can be tested.
Machine learning inference engine is of great interest to smart edge computing. Compute-in-memory (CIM) architecture has shown significant improvements in throughput and energy efficiency for hardware acceleration. Emerging non-volatile memory technologies offer great potential for instant on and off by dynamic power gating. Inference engine is typically pre-trained by the cloud and then being deployed to the filed. There are new attack models on chip cloning and neural network model reverse engineering. In this paper, we propose countermeasures to the weight cloning and input-output pair attacks. The first strategy is the weight fine-tune to compensate the analog-to-digital converter (ADC) offset for a specific chip instance while inducing significant accuracy drop for cloned chip instances. The second strategy is the weight shuffle and fake rows insertion to allow accurate propagation of the activations of the neural network only with a key.
UML Class diagram is very important to visualize the whole software we are working on and helps understand the whole system in the easiest way possible by showing the system classes, its attributes, methods, and relations with other objects. In the real world, there are two types of Class diagram engineers work with namely 1) Forward Engineered Class Diagram (FwCD) which are hand-made as part of the forward-looking development process, and 2). Reverse Engineered Class Diagram (RECD) which are those diagrams that are reverse engineered from the source code. In the software industry while working with new open software projects it is important to know which type of class diagram it is. Which UML diagram was used in a particular project is an important factor to be known? To solve this problem, we propose to build a classifier that can classify a UML diagram into FwCD or RECD. We propose to solve this problem by using a supervised Machine Learning technique. The approach in this involves analyzing the features that are useful in classifying class diagrams. Different Machine Learning models are used in this process and the Random Forest algorithm has proved to be the best out of all. Performance testing was done on 999 Class diagrams.
Model-based Systems Engineering (MBSE) has been widely utilized to formalize system artifacts and facilitate their development throughout the entire lifecycle. During complex system development, MBSE models need to be frequently exchanged across stakeholders. Concerns about data security and tampering using traditional data exchange approaches obstruct the construction of a reliable marketplace for digital assets. The emerging Distributed Ledger Technology (DLT), represented by blockchain, provides a novel solution for this purpose owing to its unique advantages such as tamper-resistant and decentralization. In this paper, we integrate MBSE approaches with DLT aiming to create a decentralized marketplace to facilitate the exchange of digital engineering assets (DEAs). We first define DEAs from perspectives of digital engineering objects, development processes and system architectures. Based on this definition, the Graph-Object-Property-Point-Role-Relationship (GOPPRR) approach is used to formalize the DEAs. Then we propose a framework of a decentralized DEAs marketplace and specify the requirements, based on which we select a Directed Acyclic Graph (DAG) structured DLT solution. As a proof-of-concept, a prototype of the proposed DEAs marketplace is developed and a case study is conducted to verify its feasibility. The experiment results demonstrate that the proposed marketplace facilitates free DEAs exchange with a high level of security, efficiency and decentralization.
Ground freezing has been used extensively in the last ten years for the construction of transit tunnel cross passages and SEM tunnels, as well as short adits for utility tunnels. Quite often the ground freezing design requirements are more complex than in conventional shafts. The frozen earth structures are frequently located in urban areas where freezing forces against structures and utilities are common. Additional considerations must be given to frost heave and thaw consolidation. This paper discusses the design procedures related to frost action. Case histories are presented that indicate how frost effects can be controlled with heating pipes, coolant control, insulation methods, and in some cases additional structural bracing. A unique project is discussed where building columns required the installation of a jacking system to accommodate the heave and settlement. 1.2 Mechanical properties of frozen soil When designing ground freezing projects, focus is typically given to the strength and thermal properties of the frozen soil. Constant strain rate and constant stress creep compression tests are used to determine the required size of the frozen mass. The thermal properties are evaluated to determine the duration and associated refrigeration load required to form the frozen mass. A majority of frozen earth projects completed in last 30 years were shafts in remote areas or vacant city lots where frost heave and thaw consolidation were not considered. The design guidelines prepared by the International Symposium on Ground Freezing (ISGF) (Andersland et al. 1991) referred to two testing methods for evaluating the potential for frost susceptibility of soils by using the segregation potential or the CRREL (U.S. Army Cold Regions and Research Engineering Laboratory). These methods provided a qualitive approach to determine whether or not a soil would be subject to frost action but provided no values that could be used to evaluate the potential heave, settlement, or pressure on adjacent structures when artificial ground freezing is used. These procedures were published well before numerical modeling was used in ground freezing design. Current models such as PLAXIS afford the capability of using the volumetric change in a soil upon freezing or thawing to act as an actual parameter in the input file. One simple method of determining the volumetric expansion is to simply measure the length and several circumferences of the specimen and compute the volume prior to and after freezing. The volumetric expansion is considered while computing the stresses and deformations of frozen earth structures using PLAXIS. PLAXIS utilizes a system of staged construction in the computation process. One of the stages often labeled the freezing stage is the activation of the frozen soil zone that includes the volumetric expansion. PLAXIS permits the evaluation of the deformations during that phase as shown in Figure 1. Figure 1. Initial volumetric expansion. It should be noted that this method only accounts for the primary expansion upon freezing and does not account for the formation of ice lenses, which is not typically considered a factor in artificial ground freezing as previously noted. There are a few problems with the simplification of the described method of measuring frost expansion. Figure 2 illustrates the mechanics of heave during ground freezing. Figure 2. Frost pressures generated during freezing. This figure shows the vertical and lateral soil and hydrostatic pressures that resist heave. Different soil types exert varying pressures while frozen and can be measured in a laboratory. Vertical heave can only occur when the pressures generated by the expansion of the pore water through freezing exceed the horizontal and vertical stresses of the in-situ soil conditions. The simplified approach for measuring volumetric expansion does not account for the imposed lateral and vertical in-situ pressures. The author proposes a new method that is a modification of tests developed at Tufts University (Huang & Swan 2017) illustrated in Figure 3. 2 APPLICATIONS IN TUNNELING 2.1 Frozen cross passages Figure 3. Heave/consolidation cell. The advantage of this method is that it permits the application of both horizontal and vertical loads, providing a more realistic value of the anticipated in-situ frost heave and thaw consolidation. Ground freezing is often the only method available to provide temporary earth support and groundwater control for cross passages that are not only very deep but exist in high permeability, cohesionless soils. A typical cross passage ranges in length from 3 to 8 m. Cross Passage 23 on the Seattle Northgate Link Tunnel is illustrated in Figure 4. Figure 4. CP-23 frozen cross passage. While the actual design of the frozen earth structure to support the cross passage excavation including structural and thermal analyses is not the topic of this paper, the frost pressures generated by the freezing process warrant discussion. The individual refrigeration pipes can be drilled and installed from within the tunnel(s) as shown in Figure 4 or from the ground surface. Regardless of the method used, the expansion of soil during the freezing process will exert considerable pressure on the segments of the two tunnels. Figure 5a. Finite element mesh. Figure 5b. Tunnel displacements. The three-dimensional mesh shown in Figure 5a is used to simulate the frozen zone. When that zone is activated in the model using a value of volumetric expansion from the laboratory tests, the resulting forces and displacements on the tunnels are computed as shown in Figure b. In this particular application, the volumetric expansion of the frozen soil was 3.1 percent, resulting in maximum forces of 4.28 kN/m2 and a maximum displacement of the tunnel segments of 0.017 m. With the knowledge of these forces prior to freezing, sufficient bracing similar to that illustrated in Figure 4 can be installed. 2.2 Frozen tunnel adits Tunnel adit construction is somewhat similar to cross passage installation but can often be considerably longer. An example of using ground freezing for adit construction at the First Street Tunnel in Washington, DC is presented in Figure 6. Figure 6. Frozen adit connection. In this case, ground freezing was used to make the connection from a micro tunneled adit to the main tunnel. The drilling and installation of refrigeration pipes was completed from the ground surface on a roadway laden with utilities including water and sewer lines. The frost susceptibly varies for different soil types. Sand and gravel soils typically exhibit minimal frost heave and thaw consolidation as compared with clay and silt soils (Andersland & Ladanyi 2004). Review of the soils indicated they were not frost susceptible at this particular location. No mitigation techniques were implemented when the freezing process was initiated but a heave monitoring program was in place. During the initial freezing, unanticipated heaving was observed at the road surface. The contractor was faced with the situation of needing to maintain the freezing system to form the frozen mass at depth while at simultaneously limiting the growth of the frozen zone near the utilities. If it was known in advance that the non-frost susceptible soils would have behaved uncharacteristically and expanded while freezing, protection of the utilities could have been implemented in advance. The most expedient and effective method to limit the growth of the frozen mass and minimize heaving was to insulate the refrigeration pipes in the zone near the affected utilities. This process typically consists of the top 7 to 10 m of the pipe and is installed during the drilling and installation process. Heave was observed at the road surface during the freezing process. This data was unfortunately not reported until the magnitude of the heave reached a near-threshold level. The heave values are shown in Figure 7. Figure 7. Frozen adit connection. As the magnitude of the heave continued to increase, it was necessary to act in order to prevent additional heaving and/or damage to the utilities. Since it was too late to install insulation on the refrigeration pipes, the contractor’s only reasonable option was to turn off a few of the redundant refrigeration pipes and then drill/install heating pipes to prevent additional growth of the frozen zone and reduce the size of the already frozen area. Each vertical bar on the graph represents a various phase in controlling the heave. The first bar represents the time at which the contractor was informed that heave was occurring. Five days after notification and confirmation of the data, the redundant refrigeration pipes were turned off. Heave subsided very briefly as the heating pipes were being drilled and installed. The heating pipes were initiated to a depth of 6 m three days later and heave was once again briefly reduced but continued. It was then necessary to heat the ground even deeper to a depth of 12 m. The deeper heating pipes were effective, as shown on the graph. The heating pipes were essentially the same design of the refrigeration pipes: a steel pipe sealed at the bottom and filled with calcium chloride solution. An electric heating element was installed within each pipe and set to a temperature of approximately 35oC. A time-dependent heat transfer finite element model was used to evaluate the effects of the heat pipes and determine required energy to maintain the 35oC temperature. This heave was measured at the road surface and not at the utilities. The mitigation using the heating pipes resulted in no measurable heave at the two utilities. After this connection, there were two other zones on the project that required freezing from the ground surface. Due to the unanticipated heave at this site, the refrigeration pipes were insulated on the subsequent projects. There was no measurable ground movement using the insulation. 2.3 Freezing near foundatio
Govind Paneru, Sandipan Dutta, Takahiro Sagawa
et al.
Understanding noisy information engines is a fundamental problem of non-equilibrium physics, particularly in biomolecular systems agitated by thermal and active fluctuations in the cell. By the generalized second law of thermodynamics, the efficiency of these engines is bounded by the mutual information passing through their noisy feedback loop. Yet, direct measurement of the interplay between mutual information and energy has so far been elusive. To allow such examination, we explore here the entire phase-space of a noisy colloidal information engine, and study efficiency fluctuations due to the stochasticity of the mutual information and extracted work. We find that the average efficiency is maximum for non-zero noise level, at which the distribution of efficiency switches from bimodal to unimodal, and the stochastic efficiency often exceeds unity. We identify a line of anomalous, noise-driven equilibrium states that defines a refrigerator-to-heater transition, and test the generalized integral fluctuation theorem for continuous engines.