The residential sector of existing buildings has great potential in energy savings and the improvement of indoor conditions. The modernization of buildings is of particular concern to the policies of the European Union, local governments, and building users. The aim of this paper is to present an analysis of indoor parameters and energy consumption for heating for an apartment located in a pre-war tenement building before and after thermomodernization. The analysis was conducted for winter conditions and was based on measurements and simulations. Originally, the building had not undergone any thermomodernization actions since its reconstruction after WWII. Interior, exterior, and surface temperatures were recorded to describe the thermal conditions of the apartment, while gas meter readings were used to estimate energy consumption for heating purposes. WUFI Plus software (v.3.2.0.1) was used to estimate energy consumption and perform energy simulations for the apartment over an extended period of time. The best thermomodernization effect resulted from the replacement of windows and the inefficient heating system, avoiding surface condensation and reducing final energy consumption by more than 50%. The extended options resulted in energy savings higher than 70%. The presented analysis shows the importance of retrofit measures and proves that even a small improvement can bring significant benefits. Full article

Background: Lockdowns and other health protective measures, such as social distancing, imposed during the COVID-19 pandemic nurtured unprecedented levels of stress and social isolation around the world. This scenario triggered an increase in suicide thoughts and self-harm behaviours among children and young people. However, the longer-term impact of the pandemic on children’s and adolescents’ mental health, especially with regard to self-harm, is still to be fully discovered. Methods: We carried out a retrospective study where we collected data related to suicide ideation and self-harm behaviours in all patients aged under 18 that required on-call psychiatric services at the General Hospital Accident and Emergency (A&E) department in Salamanca, Spain, during 2019 (pre-pandemic) and in both 2021 and 2022 to capture possible variation at different time points during the post-pandemic period. Results: A total of 316 patients aged under 18 were seen by on-call psychiatric services at the A&E department during the three time periods: 78 in 2019, 98 in 2021 and 140 in 2022. The mean age was 15.12 (SD 2.25) and females represented more than twice the number of males each year. More than half of all patients assessed during 2022 disclosed suicide thoughts, whilst in 2019, it was near 25%. This increase in suicide ideation rates was more marked among females (X² = 15.127; p = 0.001), those aged over 15 (X² = 16.437; p < 0.001) and/or those with a previous history of mental health problems (X² = 17.823; p < 0.001). We identified an increase in the proportion of males with suicide ideas, especially between 2021 and 2022 (X² = 8.396; p = 0.015). Conclusions: Our study suggests that children’s and adolescents’ demand for urgent mental healthcare and their clinical presentations in A&E departments with suicide thoughts and/or self-injuries do not seem to be declining after the pandemic but increasing over time. More research is warranted to understand possible factors involved in this sustained upward trend. Full article

Acetylsalicylic acid or aspirin is the most commonly used drug in the world and is taken daily by millions of people. There is increasing evidence that chronic administration of low-dose aspirin of about 75–100 mg/day can cause iron deficiency anaemia (IDA) in the absence of major gastric bleeding; this is found in a large number of about 20% otherwise healthy elderly (>65 years) individuals. The mechanisms of the cause of IDA in this category of individuals are still largely unknown. Evidence is presented suggesting that a likely cause of IDA in this category of aspirin users is the chelation activity and increased excretion of iron caused by aspirin chelating metabolites (ACMs). It is estimated that 90% of oral aspirin is metabolized into about 70% of the ACMs salicyluric acid, salicylic acid, 2,5-dihydroxybenzoic acid, and 2,3-dihydroxybenzoic acid. All ACMs have a high affinity for binding iron and ability to mobilize iron from different iron pools, causing an overall net increase in iron excretion and altering iron balance. Interestingly, 2,3-dihydroxybenzoic acid has been previously tested in iron-loaded thalassaemia patients, leading to substantial increases in iron excretion. The daily administration of low-dose aspirin for long-term periods is likely to enhance the overall iron excretion in small increments each time due to the combined iron mobilization effect of the ACM. In particular, IDA is likely to occur mainly in populations such as elderly vegetarian adults with meals low in iron content. Furthermore, IDA may be exacerbated by the combinations of ACM with other dietary components, which can prevent iron absorption and enhance iron excretion. Overall, aspirin is acting as a chelating pro-drug similar to dexrazoxane, and the ACM as combination chelation therapy. Iron balance, pharmacological, and other studies on the interaction of iron and aspirin, as well as ACM, are likely to shed more light on the mechanism of IDA. Similar mechanisms of iron chelation through ACM may also be implicated in patient improvements observed in cancer, neurodegenerative, and other disease categories when treated long-term with daily aspirin. In particular, the role of aspirin and ACM in iron metabolism and free radical pathology includes ferroptosis, and may identify other missing links in the therapeutic effects of aspirin in many more diseases. It is suggested that aspirin is the first non-chelating drug described to cause IDA through its ACM metabolites. The therapeutic, pharmacological, toxicological and other implications of aspirin are incomplete without taking into consideration the iron binding and other effects of the ACM. Full article

With climate change and urbanization expansion, wetlands, which are some of the largest carbon stocks in the world, are facing threats such as shrinking areas and declining carbon sequestration capacities. Wetland carbon stocks are at risk of being transformed into carbon sources, especially those of wetlands with strong land use–natural resource conservation conflict. Moreover, there is a lack of well-established indicators for evaluating the health of wetland carbon stocks. To address this issue, we proposed a novel framework for the safety assessment of wetland carbon stocks using the Super Slack-Based Measure (Super-SBM), and we then conducted an empirical study on the Quanzhou Bay Estuary Wetland (QBEW). This framework integrates the unexpected output indicator (i.e., carbon emissions), the expected output indicators, including the GDP per capita and carbon stock estimates calculated via machine learning (ML)-based remote sensing inversion, and the input indicators, such as environmental governance investigations, climate conditions, socio-economic activities, and resource utilization. The results show that the annual average safety assessment for carbon pools in the QBEW was a meager 0.29 in 2015, signaling a very poor state, likely due to inadequate inputs or excessive unexpected outputs. However, there has been a substantial improvement since then, as evidenced by the fact that all the safety assessments have exceeded the threshold of 1 from 2018 onwards, reflecting a transition to a “weakly effective” status within a safe and acceptable range. Moreover, our investigation employing the Super-SBM model to calculate the “slack variables” yielded valuable insights into optimization strategies. This research advances the field by establishing a safety measurement framework for wetland carbon pools that leverages efficiency assessment methods, thereby offering a quantitative safeguard mechanism that supports the achievement of the “3060” dual-carbon target. Full article

Recombinant adeno-associated virus (rAAV) has emerged as a prominent vector for in vivo gene therapy, owing to its distinct advantages. Accurate determination of the rAAV genome titer is crucial for ensuring the safe and effective administration of clinical doses. The evolution of the rAAV genome titer assay from quantitative PCR (qPCR) to digital PCR (dPCR) has enhanced accuracy and precision, yet practical challenges persist. This study systematically investigated the impact of various operational factors on genome titration in a single-factor manner, aiming to address potential sources of variability in the quantitative determination process. Our findings revealed that a pretreatment procedure without genome extraction exhibits superior precision compared with titration with genome extraction. Additionally, notable variations in titration results across different brands of dPCR instruments were documented, with relative standard deviation (RSD) reaching 23.47% for AAV5 and 11.57% for AAV8. Notably, optimal operations about DNase I digestion were identified; we thought treatment time exceeding 30 min was necessary, and there was no need for thermal inactivation after digestion. And we highlighted that thermal capsid disruption before serial dilution substantially affected AAV genome titers, causing a greater than ten-fold decrease. Conversely, this study found that additive components of dilution buffer are not significant contributors to titration variations. Furthermore, we found that repeated freeze–thaw cycles significantly compromised AAV genome titers. In conclusion, a comprehensive dPCR titration protocol, incorporating insights from these impact factors, was proposed and successfully tested across multiple serotypes of AAV. The results demonstrate acceptable variations, with the RSD consistently below 5.00% for all tested AAV samples. This study provides valuable insights to reduce variability and improve the reproducibility of AAV genome titration using dPCR. Full article

The escalation of mining activities in the karst regions of Guizhou Province has heightened the occurrence of water-inrush incidents in deep coal mines. This study focused on water-inrush phenomena within the Xinhua mining area of Jinsha County, Guizhou Province, aiming to investigate the sources of these incidents. The findings indicated that the overlying limestone of the Changxing Formation in the coal seam served as a vulnerable aquifer under certain conditions, leading to water inrushes. The analysis of the spatiotemporal distribution patterns of water-inrush incidents at the working face indicated that previous mining operations damaged the shallow Changxing Formation limestone, resulting in the accumulation of goaf water and the formation of numerous mining-induced fractures. These fractures served as rapid conduits for water inrushes from both atmospheric precipitation and underground sources at the deep working face. The examination of surface water and mine water quality demonstrated that both exhibited similar characteristics, predominantly featuring bicarbonate, sulfate, and sodium compositions. Investigation into the relationship between mine water inflow and atmospheric precipitation established that atmospheric precipitation influenced the mine water supply cycle, with a replenishment period of ~10 months during the operational phase of the Jinyuan Coal Mine and about one month post-closure. The fractures induced by mining activities within the Changxing Formation limestone facilitated water flow, with atmospheric precipitation serving as the primary water source for the mine. This study offered a valuable scientific foundation for addressing water-related damage resulting from atmospheric precipitation in mines susceptible to water inrushes under analogous hydrogeological conditions. Full article

Corrosion of conventional steel reinforcement is responsible for numerous structurally deficient bridges, which is a multi-billion-dollar challenge that creates a vicious cycle of maintenance, repair, and replacement of infrastructure. Repair of existing structures with fiber-reinforced polymer (FRP) has become widespread due to multiple advantages. Carbon FRP’s superior tensile strength and stiffness make it particularly effective in shear and flexural strengthening of reinforced concrete (RC) beams. This experimental study incorporates carbon fiber polymer composite bars and wraps to study and report on the flexural behavior of RC beams. By employing a combination of CFRP bar and wrap for strengthening RC beams, this study observed an approximate 95% improvement in flexural load capacity relative to control RC beams without strengthening. This substantial enhancement highlights the effectiveness of integrating CFRP in structural applications. Nevertheless, the key observation is the failure mode due to this combination providing significant insights into the changes facilitated by this combination approach. Full article

Infectious diseases caused by trypanosomatids, including African trypanosomiasis (sleeping sickness), Chagas disease, and different forms of leishmaniasis, are Neglected Tropical Diseases affecting millions of people worldwide, mainly in vulnerable territories of tropical and subtropical areas. In general, current treatments against these diseases are old-fashioned, showing adverse effects and loss of efficacy due to misuse or overuse, thus leading to the emergence of resistance. For these reasons, searching for new antitrypanosomatid drugs has become an urgent necessity, and different metabolic pathways have been studied as potential drug targets against these parasites. Considering that trypanosomatids possess a unique redox pathway based on the trypanothione molecule absent in the mammalian host, the key enzymes involved in trypanothione metabolism, trypanothione reductase and trypanothione synthetase, have been studied in detail as druggable targets. In this review, we summarize some of the recent findings on the molecules inhibiting these two essential enzymes for Trypanosoma and Leishmania viability. Full article

Ceramisite lightweight concrete has excellent performance and relatively light self-weight characteristics. At the same time, the recent development of green high-performance concrete and prefabricated components has also brought the abundant utilization of these mineral mixture. An interfacial transition zone exists between the hardened cement paste and the aggregate, which is the weakest part of the concrete, characterized by high porosity and low strength. In order to study the effect of slag content on the interfacial transition zone in lightweight high-strength concrete, experiments were designed to replace cement with slag at different contents (0%, 5%, 10%, 15%). A series of studies was conducted on its macro-strength, microstructure, and composition. The results indicated that the addition of slag improved the porosity and width of the interfacial transition zone. Adding slag did not reduce the thickness of the concrete interfacial transition zone significantly at 3 d, but it led to significant improvement in the thickness of the interfacial transition zone at 28 d, and the thickness of the interfacial zone at 28 d was reduced from 19 μm to 8.5 μm, a reduction of 55%. The minimum value of microhardness in the slurry region of the interfacial specimens also increased from 19 MPa to 26 MPa, an increase of 36%. In addition, the structural density of the interfacial region was further increased, resulting in varying degrees of improvement in the macroscopic anti-splitting strength. One of the important reasons for this phenomenon is that the addition of slag optimizes the chemical composition of the interface and promotes the continuation of the pozzolanic reactivity, which further enhances the hydration at the interface edge. Full article

It is well known that the brain is quite vulnerable to oxidative stress, initiating neuronal loss after ischemia-reperfusion (IR) injury. A potent protective mechanism is ischemic preconditioning (IPC), where proteins are among the primary targets. This study explores redox-active proteins’ role in preserving energy supply. Adult rats were divided into the control, IR, and IPC groups. Protein profiling was conducted to identify modified proteins and then verified through activity assays, immunoblot, and immunohistochemical analyses. IPC protected cortex mitochondria, as evidenced by a 2.26-fold increase in superoxide dismutase (SOD) activity. Additionally, stable core subunits of respiratory chain complexes ensured sufficient energy production, supported by a 16.6% increase in ATP synthase activity. In hippocampal cells, IPC led to the downregulation of energy-related dehydrogenases, while a significantly higher level of peroxiredoxin 6 (PRX6) was observed. Notably, IPC significantly enhanced glutathione reductase activity to provide sufficient glutathione to maintain PRX6 function. Astrocytes may mobilize PRX6 to protect neurons during initial ischemic events, by decreased PRX6 positivity in astrocytes, accompanied by an increase in neurons following both IR injury and IPC. Maintained redox signaling via astrocyte-neuron communication triggers IPC’s protective state. The partnership among PRX6, SOD, and glutathione reductase appears essential in safeguarding and stabilizing the hippocampus. Full article

With the progression of smart vehicles, i.e., connected autonomous vehicles (CAVs), and wireless technologies, there has been an increased need for substantial computational operations for tasks such as path planning, scene recognition, and vision-based object detection. Managing these intensive computational applications is concerned with significant energy consumption. Hence, for this article, a low-cost and sustainable solution using computational offloading and efficient resource allocation at edge devices within the Internet of Vehicles (IoV) framework has been utilised. To address the quality of service (QoS) among vehicles, a trade-off between energy consumption and computational time has been taken into consideration while deciding on the offloading process and resource allocation. The offloading process has been assigned at a minimum wireless resource block level to adapt to the beyond 5G (B5G) network. The novel approach of joint optimisation of computational resources and task offloading decisions uses the meta-heuristic particle swarm optimisation (PSO) algorithm and decision analysis (DA) to find the near-optimal solution. Subsequently, a comparison is made with other proposed algorithms, namely CTORA, CODO, and Heuristics, in terms of computational efficiency and latency. The performance analysis reveals that the numerical results outperform existing algorithms, demonstrating an 8% and a 5% increase in energy efficiency. Full article

This study adapted and tested an approach to identifying areas that are particularly vulnerable to climate-related hazards using the example of the post-industrial city of Knurów in Poland. This study applied a multi-criteria method using the analytical hierarchy process based on GIS map data. The analysis was divided into statistical regions defined for the city. Fifteen attributes were defined for each statistical region. The applied methods provided verified spatial information related to specific climate change hazards. The results showed that the most vulnerable areas were the areas with intensive development in the city center and in the southwestern part of the city. Among the 15 attributes, the most significant were T1 (number of inhabitants in zones with a higher potential thermal risk index by statistical district) with a value of 0.163, G2 (percentage of the sum of tree-shaded areas in built-up areas within the territory of a given statistical district) with 0.143 and H3 (number of buildings in areas of drainless basins and 100-year water). This method effectively identified the most vulnerable areas. The use of such a method can help in the preparation of planning documents and urban adaptation plans by determining the thermally and hydrologically vulnerable areas with the least developed green infrastructure as an exposure-mitigating factor. Full article

The legislation for regional environmental collaboration is of significant importance in enhancing the effectiveness of environmental protection. The existing literature focuses on the power struggle between central and local governments regarding environmental regulation within the realm of regional environmental governance, lacking an examination of the collaborative governance mechanisms and their effectiveness. Therefore, this study takes China’s regional environmental collaborative legislation as its research object. It employs a difference-in-differences model to test the effectiveness of regional environmental collaborative legislation concerning environmental governance and conducts a qualitative analysis to examine the current practical challenges facing regional environmental collaborative legislation. The quantitative analysis results indicate that regional environmental collaborative legislation can effectively suppress the emission of environmental pollutants. Specifically, the implementation of regional environmental collaborative legislation results in a 19.7% reduction in prefecture-level wastewater emissions and a 26.6% reduction in sulfur dioxide emissions. Qualitative analysis results show that regional environmental collaborative legislation currently faces challenges such as localism, difficulties in legislative authority allocation, and a lack of cooperation mechanisms. Therefore, this paper proposes to establish a collaboration platform, balance the interests of stakeholders, and improve the allocation mechanism of environmental regulatory powers in order to better optimize the regional environmental collaborative legislation and enhance the government’s environmental governance capacity. Full article

Apurinic/apyrimidinic endonuclease 1 (APE1) is involved in DNA repair and transcriptional regulation mechanisms. This multifunctional activity of APE1 should be supported by specific structural properties of APE1 that have not yet been elucidated. Herein, we applied atomic force microscopy (AFM) to characterize the interactions of APE1 with DNA containing two well-separated G-rich segments. Complexes of APE1 with DNA containing G-rich segments were visualized, and analysis of the complexes revealed the affinity of APE1 to G-rich DNA sequences, and their yield was as high as 53%. Furthermore, APE1 is capable of binding two DNA segments leading to the formation of loops in the DNA–APE1 complexes. The analysis of looped APE1-DNA complexes revealed that APE1 can bridge G-rich segments of DNA. The yield of loops bridging two G-rich DNA segments was 41%. Analysis of protein size in various complexes was performed, and these data showed that loops are formed by APE1 monomer, suggesting that APE1 has two DNA binding sites. The data led us to a model for the interaction of APE1 with DNA and the search for the specific sites. The implication of these new APE1 properties in organizing DNA, by bringing two distant sites together, for facilitating the scanning for damage and coordinating repair and transcription is discussed. Full article

The development of active food packaging is desirable for food safety and to avoid food loss and waste. In this work, we developed antioxidant bilayer films combining extrusion and electrospinning techniques. These films consisted of a first layer of thermoplastic cornstarch (TPS), incorporated with microcrystalline cellulose (MCC). The second layer consisted of gallic acid (GA) encapsulated at different concentrations in 1:1 chitosan/poly(ethylene-co-vinyl alcohol) (CS/EVOH) nanofibers. This layer was directly electrospun onto the TPS/MCC film. The morphological, structural, wettability, permeability to oxygen, and antioxidant properties were investigated for the first layer and the bilayer films. Water contact angle measurements revealed the hydrophobic nature of the first layer (θ₀ = 100.6°). The oxygen permeability (OP) was accessed through the peroxide value (PV) of canola oil, kept in containers covered by the films. PV varied from 66.6 meq/kg for the TPS/MCC layer to 60.5 meq/kg for a bilayer film. Intermolecular hydrogen bonds, mediated by GA, contributed slightly to improving the mechanical strength of the bilayer films. The bilayer film incorporated with GA at 15.0% reached a radical scavenging activity against the DPPH radical of (903.8 ± 62.2) μmol.L⁻¹.Eq. Trolox.g⁻¹. This result proved the effectiveness of the GA nanoencapsulation strategy. Full article

Cardiovascular disease (CVD) is the most frequent cause of death worldwide. The alterations in the microcirculation may predict the cardiovascular mortality. The retinal vasculature can be used as a model to study vascular alterations associated with cardiovascular disease. In order to quantify microvascular changes in a non-invasive way, fundus images can be taken and analysed. The central retinal arteriolar (CRAE), the venular (CRVE) diameter and the arteriolar-to-venular diameter ratio (AVR) can be used as biomarkers to predict the cardiovascular mortality. A narrower CRAE, wider CRVE and a lower AVR have been associated with increased cardiovascular events. Dynamic retinal vessel analysis (DRVA) allows the quantification of retinal changes using digital image sequences in response to visual stimulation with flicker light. This article is not just a review of the current literature, it also aims to discuss the methodological benefits and to identify research gaps. It highlights the potential use of microvascular biomarkers for screening and treatment monitoring of cardiovascular disease. Artificial intelligence (AI), such as Quantitative Analysis of Retinal vessel Topology and size (QUARTZ), and SIVA–deep learning system (SIVA-DLS), seems efficient in extracting information from fundus photographs and has the advantage of increasing diagnosis accuracy and improving patient care by complementing the role of physicians. Retinal vascular imaging using AI may help identify the cardiovascular risk, and is an important tool in primary cardiovascular disease prevention. Further research should explore the potential clinical application of retinal microvascular biomarkers, in order to assess systemic vascular health status, and to predict cardiovascular events. Full article

In order to meet the growing demand for food and achieve food security development goals, contemporary agriculture increasingly depends on plastic coverings such as agricultural plastic films. The remote sensing-based identification of these plastic films has gradually become a necessary tool for agricultural production management and soil pollution prevention. Addressing the challenges posed by the complex terrain and fragmented land parcels in karst mountainous regions, as well as the frequent presence of cloudy and foggy weather conditions, the extraction efficacy of mulching films is compromised. This study utilized a DJI Mavic 2 Pro UAV to capture visible light images in an area with complex terrain features such as peaks and valleys. A plastic film sample dataset was constructed, and the U-Net deep learning model parameters integrated into ArcGIS Pro were continuously modified and optimized to achieve precise plastic film identification. The results are as follows: (1) Sample quantity significantly affects recognition performance. When the sample size is 800, the accuracy of plastic film extraction notably improves, with area accuracy reaching 91%, a patch quantity accuracy of 96.38%, and an IOU and F1-score of 85.89% and 94.20%, respectively, compared to the precision achieved with a sample size of 300; (2) Different learning rates, batch sizes, and iteration numbers have a certain impact on the training effectiveness of the U-Net model. The most suitable model parameters improved the training effectiveness, with the highest training accuracy achieved at a learning rate of 0.001, a batch size of 10, and 25 iterations; (3) Comparative experiments with the Support Vector Machine (SVM) model validate the suitability of U-Net model parameters and sample datasets for precise identification in rugged terrains with fragmented spatial distribution, particularly in karst mountainous regions. This underscores the applicability of the U-Net model in recognizing plastic film coverings in karst mountainous regions, offering valuable insights for agricultural environmental health assessment and green planting management in farmlands. Full article

The benefits of denosumab as an antiresorptive therapy and in reducing fragility fractures are well documented. However, its association with atypical femur fractures (AFFs), especially in the absence of prior bisphosphonate use, remains poorly understood and warrants further investigation. This case report presents a rare instance of bilateral AFFs in a 78-year-old bisphosphonate-naïve patient with a history of long-term denosumab therapy for previous metastatic breast cancer. Management involved intramedullary nail fixation after initial presentation with a unilateral AFF and a recommendation to cease denosumab therapy. However, the patient subsequently experienced a contralateral periprosthetic AFF below a total hip implant 5 months thereafter and was treated with open reduction internal fixation. This case report highlights the critical need for orthopedic surgeons to maintain a high level of suspicion and vigilance in screening for impending AFFs, especially in patients with a prolonged history of denosumab therapy without prior bisphosphonate use. Furthermore, the growing report of such cases emphasizes the urgent need for comprehensive research aimed at refining treatment protocols that balance the therapeutic benefits of denosumab and its associated risks of AFFs. Full article

In this paper, we propose a daily living situation where objects in a kitchen can be grasped and stored in specific containers using a virtual robot arm operated by different myoelectric control modes. The main goal of this study is to prove the feasibility of providing virtual environments controlled through surface electromyography that can be used for the future training of people using prosthetics or with upper limb motor impairments. We propose that simple control algorithms can be a more natural and robust way to interact with prostheses and assistive robotics in general than complex multipurpose machine learning approaches. Additionally, we discuss the advantages and disadvantages of adding intelligence to the setup to automatically assist grasping activities. The results show very good performance across all participants who share similar opinions regarding the execution of each of the proposed control modes. Full article

Tomographic Synthetic Aperture Radar (TomoSAR) building object height inversion is a sparse reconstruction problem that utilizes the data obtained from several spacecraft passes to invert the scatterer position in the height direction. In practical applications, the number of passes is often small, and the observation data are also small due to the objective conditions, so this study focuses on the inversion under the restricted observation data conditions. The Analytic Learned Iterative Shrinkage Thresholding Algorithm (ALISTA) is a kind of deep unfolding network algorithm, which is a combination of the Iterative Shrinkage Thresholding Algorithm (ISTA) and deep learning technology, and it has the advantages of both. The ALISTA is one of the representative algorithms for TomoSAR building object height inversion. However, the structure of the ALISTA algorithm is simple, which has neither the excellent connection structure of a deep learning network nor the acceleration format combined with the ISTA algorithm. Therefore, this study proposes two directions of improvement for the ALISTA algorithm: firstly, an improvement in the inter-layer connection of the network by introducing a connection similar to residual networks obtains the Extragradient Analytic Learned Iterative Shrinkage Thresholding Algorithm (EALISTA) and further proves that the EALISTA achieves linear convergence; secondly, there is an improvement in the iterative format of the intra-layer iteration of the network by introducing the Nesterov momentum acceleration, which obtains the Fast Analytic Learned Iterative Shrinkage Thresholding Algorithm (FALISTA). We first performed inversion experiments on simulated data, which verified the effectiveness of the two proposed algorithms. Then, we conducted TomoSAR building object height inversion experiments on limited measured data and used the deviation metric P to measure the robustness of the algorithms to invert under restricted observation data. The results show that both proposed algorithms have better robustness, which verifies the superior performance of the two algorithms. In addition, we further analyze how to choose the most suitable algorithms for inversion in engineering practice applications based on the results of the experiments on measured data. Full article

There are many species of Lepidoptera, but few complete mitochondrial genomes of Lepidoptera have been included in databases. Here, the complete mitochondrial genome sequence of Salassa thespis was isolated and characterized. It was 15,302 bp in length and contained 13 protein-coding genes (PCGs), two rRNA genes, 22 tRNA genes and an A + T-rich region. Among the 13 PCGs, the initiation codon of cytochrome c oxidase subunit 1 (cox1) was CGA, and the rest were ATN. The cox1 and cox2 genes had an incomplete stop codon T, while the rest terminated with TAA. Codon usage analysis showed that Phe, Ile, Leu and Asn were the most frequent amino acids, while Trp was the least. Like other Lepidopterans, some conserved motifs were found in the A + T-rich region, including a 17 bp poly-T guided by ATAGA, the AT-rich area and a poly-A element. Bayesian inference and maximum likelihood phylogenetic tree analysis based on 13 PCGs of S. thespis confirmed that it belonged to the Saturniidae family and showed the following relationship: (S. thespis + (Rhodinia fugax + Samia canningi)). The enrichment of mitochondrial DNA provides reference information for the study of the evolution and diversity of Lepidoptera insects. Full article