Programming Research Articles

Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method

Abstract With the rapidly increasing rate of microlensing planet detections, microlensing modeling software faces significant challenges in computation efficiency. Here, we develop the Twinkle code, an efficient and robust binary-lens modeling software suite optimized for heterogeneous computing devices, especially GPUs. Existing microlensing codes have the issue of catastrophic cancellation that undermines the numerical stability and precision, and Twinkle resolves them by refining the coefficients of the binary-lens equation. We also devise an improved method for robustly identifying ghost images, thereby enhancing computational reliability. We have advanced the state of the art by optimizing Twinkle specifically for heterogeneous computing devices by taking into account the unique task and cache memory dispatching patterns of GPUs, while the compatibility with the traditional computing architectures of CPUs is still maintained. Twinkle has demonstrated an acceleration of approximately 2 orders of magnitude (≳102×) on contemporary GPUs. The enhancement in computational speed of Twinkle will translate to the delivery of accurate and highly efficient data analysis for ongoing and upcoming microlensing projects. Both GPU and CPU versions of Twinkle are open-source and publicly available.

Los criptoactivos frente al smart contract

ICTs have influenced the contract from different angles. One of them is in their enforcement, by implementing a new way of executing them through so-called smart contracts. Their most common use is found in the trading of cryptocurrencies and tokens such as NFTs. This technology consists of a computer program that enables automatic contract execution. However, they raise the issue of their validity, which must be resolved based on the category of contract to which it applies. Their implementation affects the duty of information, and must ensure consumer's right to revoke acceptance, provided for in consumer legislation.

Swimming Behavior Characteristics in Horses and Their Impact On Pregnancy Rates

In this study, the swimming behaviors of 20 Thoroughbred mares living in a private horse farm in Ulukışla district of Niğde and the effect of swimming on pregnancy rate were investigated. 20 English breed horses between the ages of 4-18 and without any health problems that would prevent them from getting pregnant were included in the study. The horses included in the study had no previous swimming experience. A veterinarian specialized in equine medicine collected the data by examining the observations and camera recordings. The behaviors of the horses around and inside the pool were observed. The pregnancy rate was determined by dividing the number of pregnant horses for each group by the total number of horses. The necessary graphs and tables were created with Microsoft Excel and SPSS statistical package programs to explain and analyze the statistical descriptive characteristics of the camera recordings and observation results. In the presented study, the analysis of pregnancy rates in the swimming group and the control group was performed using the Chi-square method with the SPSS statistical program. 19 of the 20 horses (95%) that were made to swim in the pool and 7 of the 12 horses (58.33%) that were made to swim in the pool became pregnant. The results revealed a range of behaviours including initial reactions to the pool, swimming techniques and post-swim activities. In particular, horses displayed a mixture of curiosity, attention and exploration when first introduced to the water, with the majority taking a measured and cautious approach during pool entry. Swimming behaviours were characterised by alertness, directional tendencies and vocalisations reflecting natural instincts and adaptability. Post-swim activities such as tail wagging, shaking and nose touching provided information on physical adaptation, moving away from the water and potential social or self-comforting behaviours. These findings contribute to the understanding of the behaviour of horses in aquatic environments and highlight the importance of welfare considerations in water-based activities for horses. Furthermore, addressing their natural behaviours and needs improves reproductive performance by an average of 37%. Further research may explore the specific triggers behind the observed behaviours, improve our understanding of equine behaviour in aquatic environments and encourage optimal care practices.

Software Metric Based Impact Analysis of Code Smells ‐ A Large Scale Empirical Study

ABSTRACTContextCode smells are indicators of poor design and implementation choices that negatively affect software quality and maintainability. Moreover, it is difficult and time‐consuming to work with a long list of the code smells, as not all of those smells have equal impact on the system. So, understanding the individual impact of the code smells is significant while performing refactorings on a priority basis.ObjectiveDespite significant research efforts aimed at detecting and refactoring these code smells, understanding their individual impact on software quality metrics such as size, complexity, coupling, etc. remains still unclear.MethodologyTo mitigate this research gap, we present an empirical investigation on the impact analysis of code smells based on the 25 software quality metrics such as size, cyclomatic complexity, coupling, etc. To the best of our knowledge, this is the largest empirical study about the impact analysis of code smells with respect to the number of software metrics. Particularly for this study, we identify 13 code smells in 35 open‐source software systems, and analyze (1) the relationship between code smells and software metrics, (2) which code smells are highly impactful that affect the metrics, and (3) which impactful smells occur frequently in the systems.ResultsThe results show varying degrees of correlation‐based impact between specific code smells and software metrics, with some smells showing strong correlations with multiple metrics. Three categories of impact for the code smells have been identified, namely High, Moderate and Low, where Long Method, Anti Singleton, Complex Class, Large Class and Long Parameter List smells have high impact, but their frequencies are not high except Anti Singleton; Refused Parent Bequest, Spaghetti Code and Blob have moderate impact; and rest of the smells have low impact. We also observe that perceptions about the impact of code smells vary from developer to developer and they most cases refactor the smells based on their intuition.ConclusionOur findings will help them to refactor the smells on an objective‐based instead of an intuition‐based, which will be more significant to improve the software quality. For example, refactoring the smells having a high impact on the coupling between objects metric can be an objective. Furthermore, our results will not only assist developers in prioritizing refactoring activities but also provide researchers with valuable insights to innovate tools that prioritize refactoring based on the impact of code smells. These tools will help developers target the most impactful smells and thus enhance the overall quality and maintainability of software systems.

Impact of Obesity on Short-Term Outcomes in Patients Undergoing Retroperitoneal Laparoscopic/Retroperitoneoscopic Adrenalectomy for Benign or Malignant Adrenal Diseases: A Meta-Analysis

Background and Objectives: Retroperitoneal laparoscopic adrenalectomy (RLA) is one of two laparoscopic procedures used to treat benign and malignant adrenal diseases. Obesity in patients undergoing minimally invasive adrenal surgery is a frequently discussed topic. Our meta-analysis aimed to provide updated evidence by comparing intraoperative and perioperative outcomes on non-obese (NOb) and obese (Ob) patients who underwent RLA due to benign or malignant disease. Materials and Methods: We performed a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed/MEDLINE, Scopus, Web of Science (Science and Social Science Citation Index), and Cochrane Library (Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials (CENTRAL)) databases were used to identify articles of interest. The meta-analysis was performed using RevMan [Computer program] Version 5.4. Results: The four included comparative studies (809 patients: 552 NOb versus 257 Ob) covered an approximately 15-year-study period (2007–2022). All the included studies were observational in nature. By comparing the Ob and NOb groups, shorter operative time and lower overall postoperative complication rates in the NOb population were recorded through the meta-analysis. Considering the subgroup analysis (BMI ≥ 30 kg/m2), just the operative time maintained statistical significance. Conclusions: Obesity did not appear to impact RLA safety and effectiveness. Due to important biases (small overall sample size and few analyzed events), the interpretation of our results must be a careful one. Later randomized and multi-center trials may help the confirmation of our results.

Systematic Literature Review: The Obstacles of Madrasah Aliyah Students Facing Maharatul Qiraah

Reading proficiency is one of the important aspects of language learning. Arabic language assessment is also assessed through the individual's reading proficiency. Obstacles found in one Arabic language learning proficiency are aspects that need to be considered. Students experience obstacles that affect their learning achievement. Having an in-depth identification of the problems of maharah qiraah will make it easier for teachers to teach Arabic. This study uses a qualitative approach with a systematic literature review method. Data sources are obtained from the results of research conducted by other researchers. This is done so that researchers can access more information about the problems of maharah qiraah. To produce relevant research, researchers select articles published in the last five years. Data search uses "Publish or Perish" and also "Google Scholar." Data selection is based on keywords that researchers have determined. Data collected through the two software programs will be selected for as many as seven studies. The selection is based on three important aspects, namely topic relevance, research quality, and also the year of publication. The obstacles faced by both teachers and students are equally important to know. Achievement in learning does not only depend on the teacher but also the students. Each component is involved in achieving learning goals. One of the things that teachers can do to improve students' reading skills is to implement peer groups so that they can improve each other's reading. This study is expected to help teachers find the right solution in dealing with the problem of maharah qiraah

Intelligence is not deception: from the Turing test to community-based ascriptions

Abstract The Turing test has a peculiar status in the artificial intelligence (AI) research community. On the one hand, it is presented as an important topic in virtually every AI textbook, and the research direction focused on developing AI systems that behave in human-like fashion is standardly called the “Turing test approach”. On the other hand, reports of computer programs passing the Turing test have had relatively little effect. Does this mean that the Turing test is no longer relevant as a test, doomed to be a theoretical notion with little connection to AI practice? In this paper, I argue that there is one problem in particular with common traditional versions of the Turing test, namely their focus on deception. The criterion for passing the Turing test is standardly connected to an AI system’s ability to deceive the interrogator about its identity. But why should we connect intelligence to the ability deceive? Here I present a revised version of an intelligence test that is not based on deception. In what I call the Community-based intelligence test (CBIT), an AI is introduced to a community of human subjects. If after a sufficient number of interactions within that community the humans are not able to identify the AI system as a computer, it is considered to have passed CBIT. I discuss whether that should be enough to ascribe intelligence to the AI, and if not, what more would be needed?

The Interaction Mechanisms of Swimming Biomimetic Fish Aligned in Parallel Using the Immersed Boundary Method

In natural environments, fish almost always swim in groups. Investigating the coupled mechanism of biomimetic fish exhibiting autonomous swimming capabilities advances our understanding of fish schooling phenomena and simultaneously aids in refining the structural and formation configurations of underwater robotic vehicles. This work innovatively develops an algorithm based on the Direct-Forcing Immersed Boundary Method (DF-IBM) and implements it in an efficient, modular software program written in C++. The program accelerates the calculation process by using a multigrid method. Validation against a benchmark case of flow around a cylinder, with comparison to data from the existing literature, verifies the program’s precision with discrepancies of less than 3.6%. Based on this algorithm, the paper analyzes the incompressible viscous flow during the movement of parallel-aligned biomimetic fish. It uncovers the interaction between the fish’s motion and the surrounding flow field and also reveals the hydrodynamic mechanisms of the group motion of the parallel-aligned biomimetic fish. The flow field under varying spacing and phases between the parallel-aligned biomimetic fish proves that the interaction between the flow fields induced by the two fish bodies becomes increasingly significant when decreasing the lateral spacing from 1.4L to 0.6L. Notably, an initial lateral convergence of the fish bodies is observed, followed by a sideways swimming pattern at a particular pitch angle, accompanied by a decrement in their forward swimming velocity as they approach each other. Additionally, this study compares flow field alterations in parallel-aligned biomimetic fish with identical lateral spacing but opposing flapping phases. The findings indicate that, irrespective of the phase, the fish exhibit an initial convergence followed by a sideways motion at a specific pitch angle. However, due to disparities in the tail’s flow field, a larger pitch angle is generated when the fish swim in unison. All the findings above will provide a solid theoretical foundation for the design and optimization of underwater robotic vehicles.

Seismic evaluation and retrofit of reinforced concrete structures

The destructive earthquakes in the world clearly reveal the importance of the seismic behavior of the structures. The current study proposes and numerically investigates a systematic technique for the seismic assessment and retrofit of reinforced-concrete buildings according to both material strain limit approach and Quadrants assessment method. In this study numerical analysis were made for two three-dimensional building models, namely a single-storey 30 years old existing RC building in Koyna-Warna area (Zone-IV) in India, and an earthquake-resistant designed 4-story RC building. The structural analyses were performed for two 3-D models of the selected buildings are analysed. Nonlinear static adaptive pushover analysis method was used in Seismostruct software program for two different buildings. While one of the buildings is an existing building, the other is chosen as a new building. Structural characteristics and deficiencies of the investigated single-storey existing reinforced-concrete structure necessitated seismic evaluation. The deficiencies include pitched roofs, re-entrant corners, and structural distress such as structural element cracking and cover concrete spalling, among others. The single-story RC building is retrofitted with RC jacketing and fiber-reinforced polymer sheet wrapping, while the four-storey RC building does not need to be retrofitted based on the Quadrants assessment method. Also, the significant seismic design parameters are evaluated before and after the retrofit. The results show that the material strain limit technique when combined with the Quadrants assessment method makes a more efficient technique for seismic assessment and retrofit purpose. Also, the ultimate capacity and over strength factor of the retrofitted single-storey RC existing building are found 2.04 times and 1.82 times increased in X and Y direction as compared to the building without retrofit, because of the RC jacketing and FRP sheet wrapping.

EXPRESS: Natural Affect DEtection (NADE): Using Emojis to Infer Emotions from Text

Emotions are central to consumer communications, and extracting them from user-generated online content is crucial for marketers, considering that such consumer opinions significantly shape brand perceptions, influence purchase decisions, and provide essential insights for marketing analytics. To leverage vast user-generated data, marketers and researchers require advanced text-to-emotion converters. However, existing tools for fine-grained emotion extraction face several limitations: Lexica are constrained by their dictionaries, machine learning models by human-annotated training data, and large language models by insufficient validation. As a result, marketing research still tends to rely on mere sentiment detection instead of extracting more nuanced emotions from text. This paper introduces Nade (Natural Affect DEtection), a novel text-to-emoji-to-emotion converter that first “emojifies” language and then converts these emojis into intensity measures of well-established, theory-grounded emotions. This approach addresses the limitations of existing tools by leveraging the inherent emotional information in emojis. Using human raters and state-of-the-art converters as benchmarks, the authors establish the benefits of exploiting emojis, validate Nade, and demonstrate its use in several marketing applications using data from various social media platforms. Users can apply the proposed converter through an easy-to-use online app and programming packages for Python and R.

Generating Value by Working With User Communities: An Analysis of Financial Market Returns to Corporate Open Source Code Contributions

ABSTRACTUsers are an important source of innovation. Scholars suggest that established firms can gain product‐related insights by working with user communities and studies documenting various ways of working with users, as well as managers' interest in doing so. However, the link between working with user communities for product development purposes and its value for firms is not established. Coupling the use of event study methodology and regression analysis, I examine stock market reactions to corporate announcements stating that the firm is contributing software code to the community. I find that when firms state that generating insights from users regarding new and improved features and functionality is a motivation for contributing code, the market's reaction to the announcement is greater than for announcements that do not state this goal. Additional analysis provides evidence supporting the hypothesis that firms can and do benefit by working with user communities and achieve increased R&D efficiency, which leads to greater firm value.

Accelerated Modeling of Transients in Electromagnetic Devices Based on Magnetoelectric Substitution Circuits

During switching in electrical systems, transient electromagnetic processes occur. The resulting dangerous current surges are best studied by computer simulation. However, the time required for computer simulation of such processes is significant for complex electromagnetic devices, which is undesirable. The use of spectral methods can significantly speed up the calculation of transient processes and ensure high accuracy. At present, we are not aware of publications showing the use of spectral methods for calculating transient processes in electromagnetic devices containing ferromagnetic cores. The purpose of the work: The objective of this work is to develop a highly effective method for calculating electromagnetic transient processes in a coil with a ferromagnetic magnetic core connected to a voltage source. The method involves the use of nonlinear magnetoelectric substitution circuits for electromagnetic devices and a spectral method for representing solution functions using orthogonal polynomials. Additionally, a schematic model for applying the spectral method is developed. Obtained Results: A method for calculating transients in magnetoelectric circuits based on approximating solution functions with algebraic orthogonal polynomial series is proposed and studied. This helps to transform integro-differential state equations into linear algebraic equations for the representations of the solution functions. The developed schematic model simplifies the use of the calculation method. Representations of true electric and magnetic current functions are interpreted as direct currents in the proposed substitution circuit. Based on these methods, a computer program is created to simulate transient processes in a magnetoelectric circuit. Comparing the application of various polynomials enables the selection of the optimal polynomial type. The proposed method has advantages over other known methods. These advantages include reducing the simulation time for electromagnetic transient processes (in the examples considered, by more than 12 times than calculations using the implicit Euler method) while ensuring the same level of accuracy. The simulation of processes over a long time interval demonstrate error reduction and stabilization. This indicates the potential of the proposed method for simulating processes in more complex electromagnetic devices, (for example, transformers).

Quality of Headache Management in Inpatients.

Headache is a prevalent and highly disabling neurological disorder. There are no data on its prevalence in and impact on hospitalized patients. The objective of this study was to describe the prevalence of headache in hospitalized patients, triggers associated with headaches in this population, and compliance with documentation in the electronic medical record system (EMRS). This was a prospective, descriptive, observational, cross-sectional study. Inpatients who agreed were included. Demographic data, admission-related data, and headache data were collected. Data were obtained from the EMRS and direct interviews with patients. Data were collected at three time points in 2021 and 2022. Statistical analysis, comprising primary and secondary data analysis, was performed with R. Of the 403 admitted patients, 65.5% (264 of 403) participated. A total of 39% (103 of 264) had presented with headache during their hospitalization, of whom 48.5% (50 of 103) had experienced headache in the preceding 24 hours. Of these, 35.9% (37 of 103) identified stress and 26.2% (27 of 103) identified noise as the most frequent triggers and 24.3% (25 of 103) identified headache as a secondary symptom derived from the cause of admission. During the daily follow-up by the nurse, 95.5% (252 of 264) of patients indicated that they had been asked about pain in general and 11.4% (30 of 264) indicated that they had been asked specifically about headache. No records were obtained from the computer program because although some patients were asked about headache, answers were not recorded in the prespecified "headache" item in the EMRS. Headache is a prevalent symptom in hospitalized patients. Health care professionals should ask, register, and care about headache routinely to improve patients' well-being.

Design and Research on Evaluation System of Computer Pro-gramming Code Quality

With the ongoing development of software engineering and programming education, the demand for evaluating programming code quality is increasing. High-quality code not only en-hances software maintainability and performance but also helps developers and learners optimize their coding skills. This paper focuses on the design and implementation of an evaluation system for computer programming code quality, proposing a multi-dimensional evaluation method that includes readability, complexity, efficiency, and security. The system combines static analysis with machine learning to automate code analysis and optimization recommendations, providing users with objective feedback on code quality. Additionally, this paper explores application cases of the system in programming education and software development, demonstrating its effectiveness in improving code quality and enhancing users' programming skills. Finally, the research contribu-tions are summarized, and directions for future improvements are proposed to further enhance the system’s intelligence and applicability.

Computer-aided design and fabrication of statistically shaped nasal prostheses: A feasibility study.

A nasal prosthesis may compensate for a partial or complete defect of the nose associated with trauma or amputation. However, the design and production is time-consuming, expensive, and expertize-dependent. Computer-generated prosthesis models and 3D printing can optimize the process. The purpose of this pilot study was to evaluate a novel method for nasal prosthesis design utilizing statistical shape modeling (SSM) on a cohort of participants. The prosthesis shapes were generated by a design algorithm and fabricated through a 3-dimensionally (3D) printed mold. Combining a semi-automated algorithm with 3D printing reduced the dependence on expertize. A proof-of-concept assessment was conducted by enrolling 20 participants with total nose amputation with a conventionally created prosthesis (Cp). The faces of the participants were scanned with an optical scanner to acquire 3D surface scans that were loaded into the algorithm to create the statistically shape modeled prosthesis (SSMp). Participants were asked to digitally modify the SSMp by changing 9 parameters using the Scalismo Lab software program, allowing them to shape their preferred nose model, the patient-preferred prosthesis (PPp). The SSMps were fabricated using 3D printed molds and mailed to the participants for testing. They were asked to complete questionnaires comprising three FACE-Q modules: satisfaction with the nose and psychological and social function. In addition, the SSMp and Cp were compared with the PPp using anthropometric measurements. Fifteen participants were able to fit the SSMp and complete the questionnaire. The median satisfaction, psychological, and social function scores were 56, 67, and 62, respectively. All 20 participants filled out the questionnaires on their Cp, with scores of 71, 67, and 62, respectively. Anthropometric measurements comparing the SSMp with the PPp showed that the algorithm generates noses with a wider nasal root, a larger nostril floor width to nasal width ratio, a smaller columella length to nasal width as well as nostril floor width ratio than the patients prefer according to their set PPp. Comparing the Cp with the PPp showed a larger nasal width to nasal height ratio and nasal root width to intercanthal distance ratio. SSM can facilitate the design and fabrication of nasal prostheses. Using the current models, however, patients were less satisfied than with prostheses made by the anaplastologist in consultation with the patient. Improving the SSM algorithm and incorporating patient manipulations into the resulting model should increase patient satisfaction and enable the production of nasal prostheses with minimal expert dependence.

Long-range trajectory reconstructions using the point mass model.

In shooting incident reconstructions, forensic examiners usually deal with scenes involving short-range trajectories, typically ≤30 m. Insituations such as this, a linear trajectory reconstruction model is appropriate. However, a forensic expert can also be asked to estimate a shooter's position by reconstructing a long-range trajectory where the bullet's path becomes arced as a result of gravity and the greater time in flight. In this study, the point mass model (PMM) was used, because it is accessible and considered sufficiently accurate. A computer program using PMM can perform long-range trajectory reconstructions starting from an impact point. The reconstruction results in an area where the shot is expected to be fired from, not a single location. This is caused by varying the input parameters of the PMM. The aim of this study is to assess the accuracy of the method and discuss the influence of the most relevant parameters. The model has been validated by comparing its performance with 20 handgun bullet trajectories that were determined using Doppler radar measurements over long ranges, i.e. from 500 m to 1800 m. Comparison between the area calculated using the model and the actual shooter position demonstrates the limits of these reconstructions, particularly at high incident angles. The differences between the reconstructed deflections and the deflections measured by the tracking radar are rather large. This phenomenon is caused by either measurement errors in the cross wind as a function of height or inaccuracy of the radar's deflection measurements.

Unveiling the role of artificial intelligence applied to clear aligner therapy: A scoping review.

To conduct a scoping review on the application of artificial intelligence (AI) in clear aligner therapy and to assess the extent of AI integration and automation in orthodontic software currently available to orthodontists. A systematic electronic literature search was performed in the following databases: PubMed, Embase, Web of Science, Cochrane Library, and Scopus. Also, grey literature resources up to March 2024 were reviewed. English-language studies on potential AI applications for clear aligner therapy were included based on an independent evaluation by two reviewers. An assessment of the automation steps in orthodontic software available on the market up to March 2024 was also conducted. Out of 708 studies, 41 were included. Sixteen articles focused on tooth segmentation, four on registration of digital models, 13 on digital setup, and eight on remote monitoring. Moreover, 13 aligner software programs were identified and assessed for their level of automation. Only one software demonstrated complete automation of the steps involved in the orthodontic digital workflow. None of the 13 identified aligner software programs were evaluated in the 41 included studies. However, AI-based tooth segmentation achieved 98% accuracy, while AI effectively merged CBCT and IOS data, supported digital measurements, predicted treatment outcomes, and showed potential for remote monitoring. AI applications in clear aligner therapy are on the rise. This scoping review enables orthodontists to identify AI-based solutions in orthodontic planning and understand its implications, which can potentially enhance treatment efficiency, accuracy, and predictability.

Trends in Dehydration in Older People: Identifying Landmark Scientific Contributions

Background: Dehydration and low fluid intake cause the most prevalent electrolyte imbalance in older adults and increase their morbi-mortality. Objective: To analyse the scientific production on dehydration in older adults. Methods: A bibliometric analysis was performed using the Web of Science Core Collection database. The data were analysed using two software programs, the Bibliometric package for RStudio version 4.2.2, and VOSviewer 1.6.18 for the analysis of the scientific production, authors, citations, countries and collaborations, journals, research areas, and keywords. Results: A total of 205 articles were selected. An increase in the number of publications has been observed since 2012, with 2021 being the most productive year. With respect to scientific production, although the USA had the most publications, the two most prolific authors were affiliated with an institution located in the UK, with this country having the most collaborations with other countries in the development of the subject matter. The co-occurrence analysis indicated that the words with the highest occurrence were dehydration (n = 103), hydration (n = 39), prevalence (n = 30), mortality (n = 29), and thirst (n = 29). Conclusions: This is the first bibliometric analysis that shows the publication trends on dehydration in older adults. Although the number of publications is limited, they have increased in number in the last few years. The research trends are centred on the prevalence of dehydration and its related factors. More studies are needed that are centred on interventions to correct the problem, to help fight against the electrolyte imbalances that occur, and to reduce the morbi-mortality associated with this condition.

MaxTemp: A Method to Maximise Precision of the Temporal Method for Estimating Ne in Genetic Monitoring Programs.

We introduce a new software program, MaxTemp, that increases precision of the temporal method for estimating effective population size (Ne) in genetic monitoring programs, which are increasingly used to systematically track changes in global biodiversity. Scientists and managers are typically most interested in Ne for individual generations, either to match with single-generation estimates of census size (N) or to evaluate consequences of specific management actions or environmental events. Systematically sampling every generation produces a time series of single-generation estimates of temporal F ( , which can then be used to estimate Ne; however, these estimates have relatively low precision because each reflects just a single episode of genetic drift. Systematic sampling also produces an array of multigenerational temporal estimates that collectively contain a great deal of information about genetic drift that, however, can be difficult to interpret. Here, we show how additional information contained in multigenerational temporal estimates can be leveraged to increase precision of for individual generations. Using information from one additional generation before and after a target generation can reduce the standard deviation of ( ) by up to 50%, which not only tightens confidence intervals around but also reduces the incidence of extreme estimates, including infinite estimates of Ne. Practical application of MaxTemp is illustrated with data for a long-term genetic monitoring program for California delta smelt. A second feature of MaxTemp, which allows one to estimate Ne in an unsampled generation using a combination of temporal and single-sample estimates of Ne from sampled generations, is also described and evaluated.

The application of the facial analysis program Face2Gene in a single genetic counseling center: a retrospective study

BackgroundFace2Gene (F2G) is a software program, widely used in clinical genetics and dysmorphology for recognizing children with genetic disorders. In order to assess its accuracy in real clinical context, we applied F2G to patients from our genetic counseling center.ResultsWe randomly selected 151 children, who were referred to genetic counseling because of dysmorphic features and later diagnosed with a particular genetic condition. A frontal photograph was uploaded to the program, and at least three phenotypic traits were selected for each case. Date of birth, sex, weight, height, and head circumference were also entered in the software. The efficacy of the program to correctly diagnose the syndrome based on the facial analysis and/or phenotypic traits was assessed. In 56% (84 cases) of the patients, the F2G program accurately identified the correct diagnosis in its top three suggestions. Forty-seven percent (71 cases) of the patients had the correct diagnosis after applying only facial analysis. There was a statistically significant difference between the two types of analysis—p = 0.001. In 19 of the cases where F2G was unable to identify the correct diagnosis among the top three options based on phenotypic and facial analysis, the diagnosis was included among the 30 suggested syndromes, yielding a total success rate of 68%. The diagnosis was found in the ultra-rare syndromes’ suggestions area in six more cases.ConclusionsOur results show that F2G has a good overall performance, but adding phenotypic features to the case under study may increase even further its diagnostic capacity.