To support flood mitigation management, flood damage reduction and saving human lives, and their critical infrastructures, a flood risk assessment and constructing a flood risk map are crucial. As frequent flooding events and urban water logging were observed at Sungai Pinang Watershed due to the urbanization development, and climate changes reported in the past, hence, in this work, physical flood hazard, vulnerability and risk of the critical infrastructures such as infrastructures and utilities, transportation, institution and public facilities, residential, commercial and industrial areas located at Sungai Pinang river basin, Malaysia were assessed and their maps were constructed which has not been reported. Initially, the flood hazard maps generated using a combination of 2D hydrodynamic models, Digital Elevation Model (DEM), and GIS base maps and with the results of the 2D hydraulic analysis, the flood depth was calculated. Thereafter, an integration of Geographic Information System (GIS) and Multi Criteria Decision Analysis (MCDA) namely Rank Sum and Analytical Hierarchical Process (AHP) were used to develop a Flood Vulnerability Index (FVI) map based on the results of the questioner surveys investigated from the professionals and government agencies panellists regarding the operational works prior, during and after the flood events. In order to construct the flood risk map, initially the flood damage of the critical infrastructures was estimated by multiplying the unit damage rates of each infrastructure for a range of flood return periods of 2200 year ARI by the relevant damage factors, then, the flood risk index was computed by multiplying the estimated flood damages by the probability of the flood occurrences. Each pixel of the flood risk map was produced by sum up the obtained flood risk indices and lastly, the estimated flood damage rates classified into the several flood risk degrees and colour coded to produce the flood risk map. The results obtained from the constructed flood hazard maps showed that flood hazard increased spatially and in magnitude with the rise of flood return periods and the results obtained from the developed critical physical infrastructure FVI maps demonstrated that the more vulnerable areas were mainly from the Infrastructures and Utilities category with the area of 0.531 km2 indicated as very high range of vulnerability with the index of 0.2488 while the least vulnerable areas were from the Industrial Areas category with the vulnerability index of 0.0768 and the area of 0.361 km2. It was concluded that the results of flood risk analysis were consistent with the past real flood events occurred and hit most of the critical infrastructures located in urban area of Sungai Penang basin in November 2017.

Environmental high flows, or e-floods, released from dams to restore aquatic and riparian habitats are a key management strategy to mitigate the impacts of dam regulation. While there is extensive literature on the design and implementation of e-floods, the role of instream large wood—downed trees, trunks, branches, and root wads—in enhancing e-flood outcomes in regulated rivers has not been adequately explored. This paper presents insights from the Spöl River in the Swiss Alps, where years of observations highlight the significant impact of large wood on the success of e-floods. Large wood contributes to geomorphological dynamics, increases habitat complexity, and enhances ecosystem resilience, yet it has been largely overlooked in e-flood planning. The study argues that the inclusion of instream wood can define the difference between success and failure in e-floods by supporting the continuity of the wood regime, which, along with flow and sediment regimes, is crucial for ecological integrity, and emphasizes the importance of integrating wood management into e-flood design. The Spöl River serves as a case study, demonstrating how wood management during e-floods can restore or sustain essential functions, ultimately improving the ecological health of river systems. The insights gained can be applied to the management of other regulated mountain rivers.

Two neural networks with two features (SNR and mutual information) are applied to link adaptation that is targeted for meeting the WLAN standard. The usefulness of neural-network-based link adaptation is validated for the WLAN and also the performance (throughput and latency) is analysed to obtain some practical gain of link adaptation based on neural networks over the traditional approach.

High Resolution Range Profiles (HRRP) have become a key area of focus in the domain of Radar Automatic Target Recognition (RATR). Despite the success of deep learning based HRRP recognition, these methods needs a large amount of training samples to generate good performance, which could be a severe challenge under non-cooperative circumstances. Currently, deep learning based models treat HRRP as sequences, which may lead to ignorance of the internal relationship of range cells. This letter introduces HRRPGraphNet, whose pivotal innovation is the transformation of HRRP data into a novel graph structure, utilizing a range cell amplitude-based node vector and a range-relative adjacency matrix. This graph-based approach facilitates both local feature extraction via one-dimensional convolution layers, global feature extraction through a graph convolution layer and a attention module. Experiments on the aircraft electromagnetic simulation dataset confirmed HRRPGraphNet’s superior accuracy and robustness, particularly in limited training sample environments, underscoring the potential of graph-driven innovations in HRRP-based RATR. Codes are available at: https://github.com/MountainChenCad/HRRPGraphNet.

Ransomware is a persistent threat to cybersecurity, leveraging encryption and compression techniques to obscure malicious data, making detection increasingly challenging for traditional systems. The novel approach presented in this article introduces a convolutional neural network (CNN) designed to address the limitations of existing detection methods by efficiently identifying ransomware-affected data even when strong encryption and compression algorithms are employed. Through a threelayer CNN architecture, the proposed method captures both lowlevel and high-level patterns within the file structure, enabling accurate and real-time classification of ransomware-affected files without requiring manual intervention or predefined signatures. Performance evaluations revealed significant improvements over baseline models, with the CNN achieving higher accuracy, precision, and recall, while also reducing processing time for large datasets. This advancement demonstrates the importance of automated machine learning systems in responding to increasingly sophisticated ransomware attacks, providing a scalable and practical solution for real-world applications. The ability of the CNN model to generalize across various ransomware variants further highlights its adaptability, making it an essential tool for organizations seeking to mitigate the risks posed through encrypted and compressed ransomware.

Localization provides the fundamental capabilities for the various autonomous mobile robots. It is due to the fact that it provides uncertainty in acting, sensing and environmental factors of the Robot and hence it loses localization. If we lose the Localization, Deep Reinforcement Learning helps to find the patterns in the particles. The patterns can be mixed with the weak classifiers from the particle set and observe the sensors to estimate the localization using boosted learning. In order to provide an efficient navigation, the robots are used to implement the localization strategy effectively. The comparative analysis has been analyzed for various approaches in mobile robots. We propose an extended Kalman filter (EKF) based localization algorithm scheme for robot localization, focusing on its performance and practicability. Our algorithm takes advantage of the EKF’s ability to handle non-linear motion and measurement models. By incorporating these models into the EKF framework, we can effectively estimate the robot’s pose (position and orientation) in real-time. The localization performance and practicability of the developed robot localization algorithm, extended kalman filter based localization algorithm scheme is proposed.

Associative theories of creativity posit that high-creativity individuals possess flexible semantic memory structures that allow broad access to varied information. However, the semantic memory structure characteristics and neural substrates of creative writing are unclear. Here, we explored the semantic network (SN) features and the predictive whole-brain functional connectivity (FC) associated with creative writing and generated mediation models. Participants completed two creative story continuation tasks. We found that keywords from written texts with superior creative writing performance were highly interconnected, and encompassed more semantic categories. Connectome predictive modeling (CPM) was conducted with resting-state (rs) functional magnetic resonance imaging (fMRI) data to identify whole-brain functional connectivity (FC) patterns related to creative writing. FC was found to mediate the relationship of creative writing and SN features. These results highlight how semantic memory structure and the internal thought-oriented brain functional connectivity pattern support creative writing performance. Our findings extend prior research on the role of semantic memory structure and the default mode network (DMN) in creativity, expand upon previous research on semantic creativity, and provide insight into the cognitive and neural foundations of creative writing.

Emotional states influence postural control, but previous studies have primarily focused on postural dynamics during quiet standing while viewing emotional pictures, using the center of pressure as a measure. However, the effects of emotions on neuromuscular activities related to postural control remain unclear. During quiet standing, neuromuscular activities of ankle plantarflexors are crucial for maintaining postural balance, both in terms of and synchronized muscle activity. This study aimed to clarify the emotional effects on the individual and synchronized neuromuscular activities of ankle plantarflexors during quiet standing. Twenty-four healthy male participants were instructed to view emotional pictures for 72 seconds while standing. The task was repeated four times with four picture conditions, which composed of two arousals (High and Low) and two valences (Pleasant and Unpleasant). During the task, electromyograms (EMG) of the tibialis anterior (TA), soleus (SOL), and medial (MG) and lateral gastrocnemius muscles (LG) were recorded. The EMG signals were rectified, and mean amplitude was calculated to assess individual neuromuscular activity. Inter-muscular coherence (IMC) between ankle plantarflexors was calculated to assess synchronized neuromuscular activity, with mean IMC calculated at 0–4 Hz and 8–12 Hz. Results showed that aroused emotions induced a reduction in SOL neuromuscular activity, leading to partial backward body leaning. Furthermore, synchronized neuromuscular activities at 8–12 Hz in the SOL-MG and MG-LG pairs were increased under aroused emotional states, indicating enhanced physiological tremor and a reduced capacity for postural adjustment. These findings deepen our understanding of the emotional impacts on standing postural control.

Background: A majority of patients with psychosis have experienced trauma, but trauma-focused (TF) treatment is not routinely offered. As new studies are published continuously, updated reviews are necessary to guide clinical practice, including a broader focus on several outcome variables. The current systematic review set out to examine the effect of TF treatments in patients with a psychotic disorder and comorbid trauma symptoms on symptoms of (1) trauma, (2) psychosis and (3) anxiety, depression, and psychosocial functioning. Methods: A systematic search following the PRISMA guideline yielded 17 studies reported in 19 records, which were evaluated and presented. Results: Overall, results indicated positive effects on trauma symptoms following TF Cognitive Behavioural Therapy, Eye Movement Desensitisation Reprocessing, Prolonged Exposure, Written Emotional Disclosure, and Imagery Rescripting. Results were inconclusive but suggestive of positive effects for other outcomes. Discussion: The present findings gives preliminary support for the effect of TF treatment on trauma symptoms, but are more inconclusive for outcomes related to symptoms of psychosis, anxiety, depression, and psychosocial functioning. In addition, support was found for treatments delivered both individually and by group. The current evidence base on TF treatment in psychosis is, however, still at an early stage and challenged by methodological issues.

A document by Suryasnata Bhowmik. Click on the document to view its contents.

Clinical letter

Background: Chronic Myeloid Leukemia (CML) is a rare malignancy among children, having an incidence of 1 in a million. It is driven by the Philadelphia chromosome, resulting in the BCR-ABL1 fusion gene. Pediatric cases typically present in the chronic phase and are managed with tyrosine kinase inhibitors (TKIs) like imatinib. However, some cases progress to blast crisis, leading to life-threatening complications such as acute respiratory distress syndrome (ARDS) as in our case. Methods: We present a case report with clinical and laboratory data, along with a brief literature review. Case Presentation: We present the case of a 14-year-old female diagnosed with adult-type CML, confirmed by the presence of the Philadelphia chromosome. Initially she was managed with imatinib and remained stable for one year before presenting with blast crisis complicated with acute respiratory distress syndrome (ARDS). Laboratory findings revealed a white blood cell count of 31.3 x10 9/L and a blast count exceeding 20%. A CT scan showed hepatosplenomegaly, and the patient was treated in the ICU with antibiotics, oxygen therapy, and blood transfusions. Despite the severity of the blast crisis, the patient’s condition stabilized after three weeks of intensive care and was discharged for follow-up and resumption of imatinib. Conclusion: This case highlights the aggressive nature of pediatric CML and the potential for life-threatening complications such as ARDS during the blast crisis phase. Early detection and intervention are crucial for favorable outcomes. Although TKIs are the primary treatment for pediatric CML, hematopoietic stem cell transplantation remains the only curative option for advanced stages or refractory cases.

Transcriptomics studies are more likely to achieve predictive results when they rely on tissue- and cell-specific transcriptional data. Identification of cell types in novel model organisms by their transcriptional profiles is difficult without data on transcriptional differences among major tissues and anatomical features. Here we report the first dataset on tissue- and organ-specific transcriptomics in freshwater plankton crustacean Daphnia magna, reporting markers of embryos, hemocytes, gut, carapace, antennae-2 and head, as well as the remaining carcass. Embryos are the most transcriptionally different from adults' features and antennae and the carapace are the most differentiated among them. We demonstrate that transcriptional markers of embryos vs. adults and of various adult anatomy features can be used to provide validation and functional explanation to published differential expression in response to environmental factors like infection, hypoxia, toxicants, or kairomones, to annotate Daphnia single cell data, and to ask questions about transcriptional diversification within extended gene families.

N6-methyladenosine RNA methylation (m6A) is the most common and abundant internal RNA modification in eukaryotic cells. It plays an important role in regulating many pathophysiological activities of eukaryotic creatures from cell metabolism to body growth and disease occurrence. There are three different kinds of m6A regulators including methyltransferases, demethylases and m6A-binding proteins which work together to complete the reversible epigenetic modification process of m6A. Bone is one of the most important organs with unreplaceable functions such as movement, load-bearing, hematopoiesis, and providing protection for other organs. Its physiological homeostasis depends on the synergistic activities of bone marrow mesenchymal stem cells (BMSCs), osteoblasts, osteoclasts and other cells. In the mean time, the treatment of bone-related diseases such as osteoporosis, osteoarthritis, rheumatoid arthritis, and bone tumors has always been a significant challenge. Here, we reviewed the composition of m6A as well as its regulatory mechanism in both physiological and pathological processes of bone.

Corneal injury is common in ophthalmology, with mild cases affecting the patient's vision and severe cases leading to permanent blindness. The current common treatment method in clinical practice is transplantation surgery supplemented by drug therapy. However, surgical sutures have a series of defects and cannot perfectly meet the needs of wound healing. The use of medical tissue adhesive effectively compensates for its shortcomings and has gradually become an alternative material to sutures. With the development of biomedical materials in recent years, modern ophthalmic tissue adhesive is no longer limited to wound closure but also has effects such as inhibiting vascular regeneration and antimicrobial properties. In addition, the integration of tissue adhesive with other disciplines has shown promising effects in drug delivery, ophthalmic disease diagnosis, and other areas. This article introduces common medical tissue adhesives and briefly describes their applications in ophthalmology, hoping that readers can be inspired by this article on tissue adhesives or clinical ophthalmic treatment.

Barrier-lagoon systems are among the most sensitive coastal environments, as they accumulate the effects of environmental changes occurring on lands and in the sea. Globally, the stability of lagoons and associated barriers is controlled by the frequency and magnitude of storms approaching the coasts, access to sediment supplies, and resilience to shifts in sea level. However, most studies refer to mid-latitude and tropical coastal zones, with limited insight into cold region lagoon responses. This study presents the first remote sensing analysis of the post-Little-Ice-Age (LIA) evolution of Svalbard's barrier-lagoon systems. A total of 430 lagoon systems were investigated to distinguish their genesis and type of connection to the sea (closed, choked, restricted, or leaky). Since the termination of the LIA, at least 98 lagoons have been formed, while 8 have disappeared. The majority of lagoons present along the modern coast of Svalbard are of the choked type (almost 48%). A new, previously unidentified lagoon type has been identified: the moraine-controlled paraglacial lagoons. These are systems formed by retreating marine-terminating glaciers, which is a dominant process of new coast formation in rapidly deglaciating Arctic.

Among the many adverse geological disasters, the surge water disaster in karst area causes the greatest damage to underground engineering construction, so there is an urgent need to carry out relevant research on the management of surge water disaster in karst pipeline. However, the grouting material in the blocking process of karst surge water disaster often has the problems of low retention and low blocking efficiency. In order to improve the efficiency of dynamic groundwater plugging in karst area, a new type of cement-water glass slurry was developed by taking ordinary silicate cement as the base material and adding water glass to get cement-water glass slurry, and then using polyacrylamide, Fe 3O 4 magnetic powder, xanthan gum and guar gum as the additives. The response surface regression model was constructed by Design-Expert software to analyse the effects of the four admixtures, namely, polyacrylamide, Fe 3O 4 magnetic powder, xanthan gum and guar gum, on the setting time, retention rate and compressive strength of the new type of cement-water glass slurry, and combined with the craving function to obtain the optimal proportioning of the new type of cement-water glass slurry. The results show that: the interaction of each two admixtures has a significant effect on the setting time of the slurry; while xanthan gum and Fe 3O 4 magnetic powder have a significant effect on the retention rate of the slurry as a single factor; the effect of single factor on the compressive strength of the slurry is more significant, and the polyacrylamide admixture has the greatest effect.The model predicts the optimal ratios: 0.6% polyacrylamide, 0.7% of xanthan gum, 0.4% of guar gum, and 29.96% of Fe 3O 4 powder, which can be used as a reference for the multi-objective optimisation of the mixing ratio of the new type of cement-water glass slurry.

Background: Pernicious anaemia (PA) and rheumatoid arthritis (RA) often co-occur and are commonly reported in clinical observational studies, but whether there is a causal relationship between the two diseases remains uncertain. Objective: The purpose of our study was to investigate the relationship between Pernicious anaemia and rheumatoid arthritis using Mendelian randomization (MR). Materials and methods: Single-nucleotide polymorphisms (SNPs) associated with diseases of PA and RA were selected as instrumental variables (IVs) at a genome-wide significance level (P < 5.0 × 10−8). Summary-level data of PA and RA were collected from large-scale genome-wide association studies, with a sample size of 397,378 and 490,025, respectively. MR analyses were performed using the random-effects inverse variance weighted (IVW) method, and sensitivity analyses were further operated to test the robustness. Results: Our study discovered a potentially causal effect between PA and RA. The presence of PA may increase the risk of RA by 78% by the IVW method [odds ratios (OR) = 1.78; 95% confidence interval (CI): 1.17–2.70; P = 0.007]. However, we found that RA was not causally associated with PA (IVW: OR = 1.25, 95% CI: 0.94–1.64, P = 0.120). Sensitivity analyses using other methods showed similar associations, and no evidence of pleiotropy was found by MR-Egger regression (P = 0.825, P = 0.774, respectively) in the bidirectional MR study. Conclusion: We found a potentially causal relationship between PA and RA in European population. Novel and satisfactory medicine for PA may be suitable to RA, and this potential warrants further investigation.

Nerea Abrego1*(nerea.n.abrego-antia@jyu.fi), Pekka Niittynen1(pekka.niittynen@helsinki.fi), Julia Kemppinen2(Julia.Kemppinen@oulu.fi) and Otso Ovaskainen1,3(otso.t.ovaskainen@jyu.fi)

Extreme hydroclimates impact sediment fluxes from mountainous catchments to the oceans. A challenge is to reconstruct paleo-sedimentary fluxes to assess the sensitivity of erosion in mountainous catchments to environmental perturbations such as climate and tectonics. Here, we study the response of catchments to the Paleocene-Eocene Thermal Maximum (PETM, ~56 Ma) using sedimentary archives and numerical modeling. In the Tremp Basin (Southern Pyrenees, Spain), our results demonstrate that depositional volumetric rates of siliciclastic sediments increased two-fold during the PETM. The BQART and Stream Power Law models indicate that changes in mean annual temperature and precipitation explain only 20% of the flux increase. This comparison between field data and model predictions suggests that other conditions, such as extreme rainfall events and landslides, may have been crucial sediment generation processes during the PETM. This is consistent with predictions of enhanced climate variability in a warmer world, leading to significant sediment flushing.

Cyber-physical systems (CPS) are thought to be among industry 4.0’s primary enablers. CPS technology bridges the gap between the physical and cyber worlds by integrating knowledge from several fields. An important use of Industry 4.0 is predictive maintenance (PdM), which can use a CPS-based strategy in intelligent operations to reduce machine downtime and related expenses. This paper discusses the application of machine learning to intelligent maintenance of Cyber Physical systems. As CPS become more complex and widespread across industries, maintaining their reliability and performance is critical. This paper further describes how machine learning algorithm can be used to predict system failure, develop repair plans and further highlights the potential significant improvements in CPS maintenance strategies.

The sclerophyllous forest of Chile has experienced an unprecedented 14-year megadrought (2010-2022), in which, in addition, a period of hyperdrought was recorded in 2019. In this paper, we assess the following questions: 1) How has the megadrought affected the net primary productivity of the Chilean Mediterranean sclerophyll forest in its current distribution; 2) How have temperature and precipitation affected this pattern of primary productivity over time; and 3) How did a hyperdrought event affect the primary productivity of the sclerophyll forest during the megadrought? The Chilean Mediterranean sclerophyll forest was considered throughout its current distribution between 31 and 37°S. Net primary productivity was assessed using the Enhanced Vegetation Index (EVI) for the megadrought (2010 and 2022), hyperdrought (2019), and pre-megadrought (2000-2009) reference periods using Landsat satellite imagery. Subsequently, extreme EVI anomalies above or below 90 % of the phenological reference frequency (RFD) were evaluated. To assess the effect of climate on EVI, precipitation and temperature data from the CHIRPS satellite were used. To explain the contribution of precipitation and temperature on EVI, multiple linear regression models were performed. The results indicate the following: i) the northern range populations decreased EVI regardless of the period studied, ii) during the megadrought period, the northern range populations decreased EVI due to decreased precipitation. On the contrary, in the southern range populations, EVI is affected by the increase in temperature, and iii) during the hyperdrought event, a differential response of EVI was observed, in which the northern distribution and the Andean foothills populations were severely affected and maintained low EVI values in the following years. Finally, further ecophysiological studies are needed to understand the responses of these species to water and thermal stress, as future climate models predict an increase in drought in the Chilean Mediterranean, a biodiversity hotspot.

Aim: Propofol-remifentanil-dexmedetomidine-based total intravenous anesthesia is widely used, but ensuring the safety of the sleep-wakefulness transition and hemodynamic stability remains a challenge. This study aimed to investigate the influence of orexinergic neuron gene polymorphisms on interindividual variability in the time to loss of consciousness (LOC), time to wake, and cardiovascular fluctuations. Methods: A total of 250 patients were included in the study. Gene polymorphisms were detected using the Agena Bioscience MassARRAY system. Anesthesia induction began with propofol and maintained with propofol and remifentanil. Dexmedetomidine was administered before anesthesia induction. The time to LOC, time to wake, heart rate (HR), and mean arterial pressure (MAP) were documented. Results: HCRTR2 rs2292040 and rs76380807 were significantly associated with the time to LOC, and HCRTR2 rs7774031 was correlated with the time to wake. HCRTR2 rs3122162, rs3122169, and rs74296544 were correlated with HR fluctuations, and HCRTR1 rs2176807, rs2271933, rs871634, and HCRTR2 rs74296544 were associated with MAP fluctuations. Multiple linear regression analysis revealed that a TCI concentration of propofol > 4 μg ml-1 at the time of LOC and dexmedetomidine were influencing factors for the time to LOC, whereas HCRTR2 rs7774031 influenced the time to wake. Baseline HR, baseline MAP, dexmedetomidine, HCRTR2 rs3122162, and HCRTR1 rs2176807 were predictive factors for cardiovascular susceptibility. The predictive models for the time to LOC, time to wake, HR, and MAP fluctuations accounted for 41.89%, 3.36%, 35.56%, and 47.41% of variations, respectively. Conclusion: Genetic variants of orexinergic neurons may affect sleep-wakefulness transition and hemodynamic stability during propofol, dexmedetomidine, and remifentanil anesthesia.

Allopurinol is a widely prescribed medication for gout, but it carries a risk of severe hypersensitivity reactions, particularly in individuals with the HLA-B*5801 allele. This case report describes a 70-year-old Caucasian female who developed Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS) syndrome following an increase in her allopurinol dosage. The patient presented with a diffuse, erythematous maculopapular rash, acute kidney failure, and elevated liver enzymes. She was found to be positive for the HLA-B*5801 allele and used a thiazide diuretic as risk factors for allopurinol hypersensitivity. After discontinuing allopurinol and initiating treatment, her condition improved, but she later died from a ruptured aneurysm unrelated to the hypersensitivity reaction. This case highlights the potential for dose-dependent hypersensitivity reactions to allopurinol, particularly in the presence of the HLA-B*5801 allele. Despite the rarity of such reactions in Caucasian populations, clinicians should remain vigilant, especially during the initial treatment phase.