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Parking Assistant is a solution that assists drivers to park their vehicles safely, using a variety of sensors that are installed strategically, such that the entire parking process is safe and easy. Sometimes drivers tend to hit the wall with their vehicles, because they cannot see what is in their blind spots or underestimate how far the wall is from their back. The garage might also be sometimes be too dark to safely park the vehicle. Therefore, building a system that can assist drivers by constantly notifying the distance between the back of the car and the wall, and can control the lighting can help reduce this risk, and assist them to park their vehicles safely. An ultrasonic sensor, such as the HC0SR04 can detect the distance from the sensor to a distant object, can be used for this purpose. A safe limit can be supplied to the program, and if the vehicle is found to be closer than the safe limit, then the driver is notified about the risk through the buzzer. Also, using relays, an automated garage automation system can be created, such that electricals in the garage can be controlled through a simple mobile application.

Search algorithms are an essential component of many artificial intelligence applications. Depth Limited Search and A* Search are two prominent search algorithms that have been widely used in various domains, including robotics, game playing, and natural language processing. The research paper presents an overview of these two algorithms, their architecture, pros and cons, and the areas of their application. A detailed comparison of these two algorithms in terms of their performance, efficiency, and effectiveness in solving various search problems is also analysed. Finally, the paper presents a case study for two approaches. Experimental results depicted that after repetitive execution of each algorithm and graph data, it was detected that while the A-star search was able to find the cheaper cost almost always, Depth Limited Search was able to find the route faster with limited node visits.

Acute kidney injury (AKI) following hyperthermic intraperitoneal chemotherapy (HIPEC) is common. Identifying patients at risk could have implications for surgical and anesthetic management. We aimed to develop a predictive model that could predict AKI based on patients preoperative characteristics and intraperitoneal chemotherapy regimen. We retrospectively gathered data of adult patients undergoing HIPEC at our health system between November 2013 and April 2022. Next, we developed a model predicting postoperative AKI using multivariable logistic regression and calculated the performance of the model (area under the receiver operating characteristics curve [AUC]) via tenfold cross-validation. A total of 412 patients were included, of which 36 (8.7%) developed postoperative AKI. Based on our multivariable logistic regression model, multiple preoperative and intraoperative characteristics were associated with AKI. We included the total intraoperative cisplatin dose, body mass index, male sex, and preoperative hemoglobin level in the final model. The mean area under the receiver operating characteristics curve value was 0.82 (95% confidence interval 0.71-0.93). Our risk model predicted AKI with high accuracy in patients undergoing HIPEC in our institution. The external validity of our model should now be tested in independent and prospective patient cohorts.

The perception of disinformation as societal risk has reached a troubling peak amid the COVID-19 pandemic, strategically targeting vulnerable audiences through digital media by mirroring characteristics of vox populi disinformation. This study investigates the conditions under which COVID-19-related disinformation referring to a polarized (refugees) and neutral (runners) out-group appears most credible. In the early stages of the pandemic, we conducted a pre-registered online survey experiment with a representative German sample (N = 1,117). Results indicated that those with low trust in the media judged subtle and completely fabricated types of disinformation as more credible than accurate information. Presenting the article as a social media post from an ordinary user, rather than an official source, had no discernible impact on credibility evaluations; participants accurately assessed the credibility of a random source. We conclude that people are generally able to recognize disinformation—unless they already mistrust the media. This paper addresses why disinformation triggers strong reactions in targeted groups and how it thrives in the participatory digital landscape.

Background & Aims: A new nomenclature and subclassification for steatotic liver disease (SLD) was recently introduced. We validated the prognostic value of SLD subclasses in a Finnish population-based cohort and explored the impact of metabolic risk factors and alcohol consumption on liver-related outcomes and death. Methods: The study included 23,910 individuals (47% men, mean age 50.5 ± 14.0 years, BMI 27.0 ± 4.7 kg/m2) from the FINRISK and Health 2000 health examination surveys with healthcare registry linkage for severe liver-related outcomes and deaths. SLD was identified by alanine aminotransferase (ALT) levels >20 U/L in women and >30 U/L in men (primary analysis) or fatty liver index (FLI) ≥60 (sensitivity analysis). Results: The prevalence of ALT-defined SLD was 43% (n = 10,380), with subclass rates of 34.5% for metabolic dysfunction-associated steatotic liver disease (MASLD), 4.2% for coexistent MASLD and alcohol-related liver disease (ALD) (i.e., MetALD), and 1.8% for ALD. During a median 13.3-year follow-up, we observed 129 liver-related events. MetALD and ALD increased the age- and sex-adjusted liver-related outcome risk by fourfold (HR 3.83, 95% CI 2.51–5.84, p

Abstract Movement performance of insects is an important measure of physiological fitness and is likely affected by novel stressors associated with global change. Reduced fitness can lead to smaller foraging areas and thus to decreasing abundance, diversity and nutritional quality, which could weaken insect populations and contribute to global insect decline. Here, we combined two different methods: An experimental semi‐field design applying treatments in outdoor flight cages and a follow‐up experiment conducted in the laboratory, in which different parameters of movement performance, such as (a) velocity, (b) duration and (c) distance of an insect's flight can be quantified. We kept colonies of the bumblebee Bombus terrestris under contrasting nutritional conditions and measured treatment effects on the movement performance of individuals. Monophagously fed bumblebees showed reduced movement performance than polyphagously fed bumblebees. In particular, they stopped more frequently during flight, flew shorter distances and showed less often flight duration of 20 min. Our results suggest that nutritional deficiency due to a monophagic diet leads to reduced flight performance, which can have dramatic negative consequences for bees. Reduced flight performance may result in decreased availability of host plants, which may negatively affect stress resistance of bees and brood provisioning, facilitating extinction of insects. Although food of great nutritional value is an important compensator for the negative effects of different novel stressor, such as pesticides, it is not much known how to compensate for the effects of nutritional stress, especially in landscapes dominated by monocultures. However, our experimental approach with semi‐field and laboratory components has high potential for further studies investigating the impact of different stressors on the physiological fitness of insects but also body mass, or reproductive success and to find factors that may mitigate or even overcome the negative effect of stressors on insects.

Abstract Acute kidney injury (AKI) following hyperthermic intraperitoneal chemotherapy (HIPEC) is common. Identifying patients at risk could have implications for surgical and anesthetic management. We aimed to develop a predictive model that could predict AKI based on patients’ preoperative characteristics and intraperitoneal chemotherapy regimen. We retrospectively gathered data of adult patients undergoing HIPEC at our health system between November 2013 and April 2022. Next, we developed a model predicting postoperative AKI using multivariable logistic regression and calculated the performance of the model (area under the receiver operating characteristics curve [AUC]) via tenfold cross-validation. A total of 412 patients were included, of which 36 (8.7%) developed postoperative AKI. Based on our multivariable logistic regression model, multiple preoperative and intraoperative characteristics were associated with AKI. We included the total intraoperative cisplatin dose, body mass index, male sex, and preoperative hemoglobin level in the final model. The mean area under the receiver operating characteristics curve value was 0.82 (95% confidence interval 0.71–0.93). Our risk model predicted AKI with high accuracy in patients undergoing HIPEC in our institution. The external validity of our model should now be tested in independent and prospective patient cohorts.

Potassium (K) is an essential mineral that is necessary for normal cell and membrane function and for maintaining both fluid balance and acid-base balance. Potassium is furthermore very important for normal excitation, for example in nerves and muscle. It is widely available in several food products, with the most important dietary sources being potatoes, fruits, vegetables, cereal and cereal products, milk and dairy products, and meat and meat products. Potassium deficiency and toxicity is rare in healthy people, but dietary potassium is associated with other health outcomes. Results from observational studies have shown that a potassium intake above 3500 mg/day (90 mmol/day) is associated with a reduced risk of stroke. Similarly, intervention studies provide evidence that this level of potassium intake has a beneficial effect on blood pressure, particularly among persons with hypertension and in persons with a high sodium intake (>4 g/day, equivalent to >10 g salt/day).

The performance enhancement of an inverter-based grid-connected system necessitates a fast and accurate dynamic response in terms of estimating three-phase grid voltage attributes. The synchronous reference frame phase-locked loop (PLL) and/or the frequency-locking (i.e., frequency-locked loop) approaches are widely used in practical applications. However, due to the phase/frequency feedback loops, the aforementioned parameter estimation schemes may experience instability and provide a slow dynamic response. This work presents a PLL-less grid synchronization solution for three-phase applications to counter the slower dynamic response and demonstrate better immunity against the nonideality of a three-phase grid. In order to remove even and odd-order harmonics and extract the fundamental frequency positive sequence (FFPS), the proposed method employs a combination of band pass filters (CBPFs). Additionally, a novel frequency estimation algorithm is developed, which accurately estimates the angular three-phase grid frequency. Furthermore, the phase angle and amplitude are adaptively estimated using an off-line error-resolving approach, which is derived from the transfer function of the proposed prefiltering solution. Finally, the experimental findings validate the robustness of the current proposal.

Blood pressure (BP) rises along with increasing sodium intake from early childhood to late adulthood, and leads to hypertension among most men and women living in Nordic and Baltic countries. Elevated BP is the leading global risk factor for premature deaths and disability-adjusted life-years. A reduction in sodium intake is essential in the prevention of hypertension in individuals, in the lowering of BP levels, in the treatment of hypertensive individuals, and in decreasing risks associated with elevated BP. There is a progressive linear dose-response relationship between sodium intake and BP beginning from a sodium intake of less than 0.8 g/day. Sodium reduction decreases BP linearly by a dose-response manner down to a sodium intake level of less than 2 g/day. Randomised intervention studies with a duration of at least 4 weeks confirm the efficiency and safety of reducing blood sodium intake to a level of less than 2 g/day. Results from prospective cohort studies show that higher sodium intake is positively associated with an increased risk of stroke and cardiovascular events and mortality among the general adult population, and the associations are linear in studies using proper sodium assessment methods. Analyses assessing sodium intake using at least two 24-h urine samples have shown a linear positive relationship between sodium intake and the risk of a cardiovascular event or death. Based on an overall evaluation of the available data, a limitation of the sodium intake to 2.0 g/day is suggested for adults. The optimal sodium intake level would be probably about 1.5 g/day. Sodium intake recommended for children can be extrapolated from the recommended sodium intake for adults. According to national dietary surveys, the average sodium intakes in Nordic countries range in adult men from 3.6 to 4.4 g/day and in adult women from 2.6. to 3.2 g/day, and in Baltic countries in men from 2.6 to 5.1 g/day and in women from 1.8 to 3.6 g/day.

Abstract Background Intraoperative 3D imaging using cone-beam CT (CBCT) provides improved assessment of implant position and reduction in spine surgery, is used for navigated surgical techniques, and therefore leads to improved quality of care. However, in some cases the image quality is not sufficient to correctly assess pedicle screw position and reduction, especially due to metal artifacts. The aim of this study was to investigate whether changing the acquisition trajectory of the CBCT in relation to the pedicle screw position during dorsal instrumentation of the spine can reduce metal artifacts and consequently improve image quality as well as clinical assessability on the artificial bone model. Methods An artificial bone model was instrumented with pedicle screws in the thoracic and lumbar spine region (Th10 to L5). Then, the acquisition trajectory of the CBCT (Cios Spin, Siemens, Germany) to the pedicle screws was systematically changed in 5° steps in angulation (− 30° to + 30°) and swivel (− 30° to + 30°). Subsequently, radiological evaluation was performed by three blinded, qualified raters on image quality using 9 questions (including anatomical structures, implant position, appearance of artifacts) with a score (1–5 points). For statistical evaluation, the image quality of the different acquisition trajectories was compared to the standard acquisition trajectory and checked for significant differences. Results The angulated acquisition trajectory increased the score for subjective image quality (p

The development of the neocortex involves an interplay between neural cells and the vasculature. However, little is known about this interplay at the ultrastructural level. To gain a 3D insight into the ultrastructure of the developing neocortex, we have analyzed the embryonic mouse neocortex by serial block-face scanning electron microscopy (SBF-SEM). In this study, we report a first set of findings that focus on the interaction of blood vessels, notably endothelial tip cells (ETCs), and the neural cells in this tissue. A key observation was that the processes of ETCs, located either in the ventricular zone (VZ) or subventricular zone (SVZ)/intermediate zone (IZ), can enter, traverse the cytoplasm, and even exit via deep plasma membrane invaginations of the host cells, including apical progenitors (APs), basal progenitors (BPs), and newborn neurons. More than half of the ETC processes were found to enter the neural cells. Striking examples of this ETC process “invasion” were (i) protrusions of apical progenitors or newborn basal progenitors into the ventricular lumen that contained an ETC process inside and (ii) ETC process-containing protrusions of neurons that penetrated other neurons. Our observations reveal a — so far unknown — complexity of the ETC–neural cell interaction.

This article investigates the innovative role of machine learning (ML) in the development of smart cities, emphasizing the critical interrelationship between ML and urban environments. While existing studies address ML and urban settings separately, this work uniquely examines their intersection, highlighting the transformative potential of ML in urban development. Utilizing the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, a systematic and reproducible approach was employed to review 42 relevant studies. The analysis reveals four key themes: transportation and traffic optimization, people and event flow tracking, sustainability applications, and security use cases. These findings underscore ML’s ability to revolutionize smart city initiatives by enhancing efficiency, sustainability, and security. This review identifies significant research gaps and proposes future directions, positioning ML as a cornerstone in the evolution of intelligent urban environments.

Rainwater collection systems play a crucial role in enhancing water availability in regions with low precipitation. This study focused on identifying potential rainwater harvesting (RWH) locations in drought-prone areas, specifically the Borena zone of Oromia and the regional states of Somali. This research leveraged geospatial techniques and a multi-criteria decision analysis (MCDA) to assess feasible RWH sites. The dataset comprises essential factors such as rainfall, drainage density, slope, soil texture type, and land use/land cover. These thematic layers serve as inputs for analysis, with each factor being weighted using the Analytical Hierarchy Process (AHP) method based on its significance. Reclassifying factors into subclasses facilitates suitability analysis. The weighted linear combination (WLC) technique is applied to identify and prioritize potential rainwater harvesting (PRWH) locations based on four suitability classes: highly suitable, moderately suitable, low suitability, and unsuitable. Our findings reveal that 1% of the study area, covering approximately 3288 km2, is highly suitable for RWH. Areas with moderate suitability constitute approximately 12% (37,498 km2), while regions with low suitability, representing the majority, encompass about 75% (242,170 km2). Additionally, 13% (41,000 km2) of the study area is deemed unsuitable for RWH. The proposed technique for identifying suitable RWH sites is adaptable to other low-precipitation regions. However, before implementing RWH structures, further research is imperative. This study proposed the exploration of socioeconomic variables in future research and urged for an in-depth examination of various aspects of environmental sustainability. Our research paves the way for adapting rainwater harvesting systems to align with community needs and life cycles while also exploring the socio-economic and environmental dimensions of sustainability for future study. The insights offer promising solutions to address the urgent issues associated with water scarcity. This should include comprehensive site depictions, an exploration of social and economic activities, and the meticulous preparation of a cost-benefit analysis.