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Background: Digital neuropsychological tests reliably capture real-time, process-based behavior that traditional paper/pencil tests cannot detect, enabling earlier detection of neurodegenerative illness. We assessed relations between informant-based subtle and mild functional decline and process-based features extracted from the digital Trail Making Test-Part B (dTMT-B). Methods: A total of 321 community-dwelling participants (56.0% female) were assessed with the Functional Activities Questionnaire (FAQ) and the dTMT-B. Three FAQ groups were constructed: FAQ = 0 (unimpaired); FAQ = 1-4 (subtle impairment); FAQ = 5-8 (mild impairment). Results: Compared to the FAQ-unimpaired group, other groups required longer pauses inside target circles (p < 0.050) and produced more total pen strokes to complete the test (p < 0.016). FAQ-subtle participants required more time to complete the entire test (p < 0.002) and drew individual lines connecting successive target circles slower (p < 0.001) than FAQ-unimpaired participants. Lines connecting successive circle targets were less straight among FAQ-mild, compared to FAQ-unimpaired participants (p < 0.044). Using stepwise nominal regression (reference group = FAQ-unimpaired), pauses inside target circles classified other participants into their respective groups (p < 0.015, respectively). Factor analysis using six dTMT-B variables (oblique rotation) yielded a two-factor solution related to impaired motor/cognitive operations (48.96% variance explained) and faster more efficient motor/cognitive operations (28.88% variance explained). Conclusion: Digital assessment technology elegantly quantifies occult, nuanced behavior not previously appreciated, operationally defines critical underlying neurocognitive constructs related to functional abilities, and yields selected process-based scores that outperform traditional paper/pencil test scores for participant classification. When brought to scale, the dTMT-B test could be a sensitive tool to detect subtle-to-mild functional deficits in emergent neurodegenerative illnesses. [ABSTRACT FROM AUTHOR]

This paper explores the relationship between territory and urban space, discussing the joint development processes of urban and territorial morphologies. The paper argues that territorial structure is a precursor to urban design. It also discusses how landscape architecture can respond to the morphological needs of contemporary urban design as the boundaries between city and territory merge. The introduction and framework review section examines various approaches to studying the relationship between urban morphology and interstitial spaces or unbuilt geographies, which are often still considered empty spaces, physically incorporated but excluded from urban design. It also briefly discusses the role that green spaces and territorial morphologies have played, or not played, in defining urban form from antiquity to modernity. The paper then focuses on the role of hydromorphologies in shaping the urban form of Rome, Boston and Bari. These cities are analyzed as case studies to discuss 20th-century approaches to urban planning in relation to territorial layout. Finally, this study analyzes a marginal area of the metropolitan city of Bari in order to propose possible landscape morphologies of reconnection for the resulting interstitial areas. [ABSTRACT FROM AUTHOR]

This paper examines the context, precedents, contents, distribution, and socio-economic ramifications of deed restrictions in early-nineteenth century Boston, reviewing examples of restrictions' use and a comprehensive survey of the 1800–1839 deeds of five grantors. It shows how Boston's government and then private land developers began using deed restrictions in regards to building use, materials, height, and bulk in select geographies during this period. They did so to guarantee prestigious and stable home and work environments to wealthy consumers in the fast-changing urban context, in turn bringing into existence a prized and exclusive stratum of urban residential and commercial property. [ABSTRACT FROM AUTHOR]

In this paper, we prove the compressible Euler limit from the Boltzmann equation with hard sphere collisional kernel and complete diffusive boundary condition in half-space by employing the Hilbert expansion which includes interior and Knudsen layers. This rigorously justifies the corresponding formal analysis in Sone's book [ Molecular gas dynamics , Birkhäuser Boston, Inc., Boston, MA, 2007] in the context of short time smooth solutions, and also generalizes the classic Caflisch's result [Comm. Pure Appl. Math. 33 (1980), pp. 651–666] to initial-boundary problem case. [ABSTRACT FROM AUTHOR]

Many semiparametric spatial autoregressive (SSAR) models have been used to analyze spatial data in a variety of applications; however, it is a common phenomenon that heteroscedasticity often occurs in spatial data analysis. Therefore, when considering SSAR models in this paper, it is allowed that the variance parameters of the models can depend on the explanatory variable, and these are called heterogeneous semiparametric spatial autoregressive models. In order to estimate the model parameters, a Bayesian estimation method is proposed for heterogeneous SSAR models based on B-spline approximations of the nonparametric function. Then, we develop an efficient Markov chain Monte Carlo sampling algorithm on the basis of the Gibbs sampler and Metropolis–Hastings algorithm that can be used to generate posterior samples from posterior distributions and perform posterior inference. Finally, some simulation studies and real data analysis of Boston housing data have demonstrated the excellent performance of the proposed Bayesian method. [ABSTRACT FROM AUTHOR]

With the widespread application of spatial data in fields like econometrics and geographic information science, the methods to enhance the robustness of spatial econometric model estimation and variable selection have become a central focus of research. In the context of the spatial error model (SEM), this paper introduces a variable selection method based on exponential square loss and the adaptive lasso penalty. Due to the non-convex and non-differentiable nature of this proposed method, convex programming is not applicable for its solution. We develop a block coordinate descent algorithm, decompose the exponential square component into the difference of two convex functions, and utilize the CCCP algorithm in combination with parabolic interpolation for optimizing problem-solving. Numerical simulations demonstrate that neglecting the spatial effects of error terms can lead to reduced accuracy in selecting zero coefficients in SEM. The proposed method demonstrates robustness even when noise is present in the observed values and when the spatial weights matrix is inaccurate. Finally, we apply the model to the Boston housing dataset. [ABSTRACT FROM AUTHOR]

This paper explores a novel high-dimensional sparse multiplicative model, which deal with data with positive responses, particularly in economical and biomedical researches. The proposed regularized method is conducted on the least product relative error (LPRE), and can be applied on various penalties including adaptive Lasso, SCAD, and MCP. An adjusted ADMM algorithm is adopted to obtain the estimators based on LPRE loss. Additionally, we prove the consistency and compute the convergence rates of the estimator. To validate the effectiveness of the proposed method, we conduct extensive numerical studies and real data analysis, yielding valuable insights and practical applications, utilizing well-known datasets of the Boston housing data and gold price data. [ABSTRACT FROM AUTHOR]

The urban radio‐frequency (RF) noise generated by our cities continues to change with time. Although models exist to describe the RF noise as functions of frequency and urban land use types, very few models describe the spatial character or structure of the noise on the scales of city blocks (50–150 m). The goal of this work is to investigate the connection between urban morphology and the higher‐order spatial statistics of the noise field. To achieve this goal, a large measurement campaign was conducted in Boston, Massachusetts. Many spatial measurements allowed for calculation of spatial correlation functions of noise power in three different neighborhoods, which were used to quantify the spatial structure of the fields. A statistical point source model is then developed, with adjustable parameters relating to urban morphology. Good agreement between the model and the experimental correlation functions suggests the 25 MHz urban noise field is well described by a random network of fixed point sources, radiating with a 1/r power law behavior. Plain Language Summary: Our modern cities are filled with electronic devices. Each device can emit radiation and contribute to what is called the urban radio‐frequency noise field. The noise field is the combined effect from all these devices. If the noise field is strong enough it can negatively impact wireless communication, and the use of other electric devices. It is important to better understand the nature of the noise field in order to mitigate and plan for its negative effects. This paper describes in detail how the noise field is distributed in space, or its spatial structure. A theoretical model or tool is developed to help predict how the noise field looks spatially. Key Points: Radio‐frequency noise spatial correlation functions were calculated for three different neighborhoods in Boston, MassachusettsGood theoretical agreement suggests the noise field is well described by a random network of point sources radiating with a 1/r behavior [ABSTRACT FROM AUTHOR]

This research paper presents the results of two studies investigating human mobility patterns in the 15 largest Metropolitan Statistical Areas (MSAs) in the United States. It studied 14 daily mobility parameters aggregated at the MSA level, derived from four primary mobility parameters: Number of Visited Locations (N_LOC), Number of Unique Visited Locations (N_ULOC), Radius of Gyration (R_GYR), and Distance Traveled (D_TRAV) over a 30-day period. The first study was conducted on data from two large MSAs, one coastal and one inland (Boston and Atlanta, respectively). The aim was to examine associations between daily values of mobility parameters aggregated at the MSA level and identify those carrying similar or identical information. Results of factor analysis showed that these could be adequately described by two independent factors, pointing to one or two of the mobility parameters as sufficient to represent the whole set in analyses based on associations. These could either be D_TRAV, as it had high loadings on both factors, or N_LOC and R_GYR due to their high loadings on the two extracted factors. The second study was conducted on daily mobility datasets from the 15 MSAs. The aim was to compare daily mobility patterns of these MSAs and group them based on their mobility pattern similarities. Factor analysis of the aggregated mean daily distances (D_TRAV) across different MSAs over the studied period classified them into two distinct groups: one predominantly composed of inland MSAs and the other primarily of coastal MSAs. Strong weekly cycle trends emerged in these groups. Specifically, individuals from the inland MSA group tended to travel the furthest on Fridays and the least on Sundays, whereas those from the coastal MSA group traveled the most on Saturdays and the least on Mondays. This weekly pattern was robust, with 7-day lag autocorrelations of mean daily parameter values ranging between 0.81 to 0.99, excluding the mean daily N_LOC. These findings offer a foundational understanding of MSA mobility patterns, paving the way for more detailed studies on the nuances of these patterns. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a new class of heterogeneous spatial autoregressive models (heterogeneous SAR models) where the variance parameters are modeled in terms of covariates. In order to estimate the model parameters, as well as their corresponding standard error estimates, we proposed a computational efficient MCMC method which combines the Gibbs sampler with Metropolis-Hastings algorithm. The proposed estimate method is illustrated through numerous simulations and is applied to the Boston housing data. [ABSTRACT FROM AUTHOR]

It is well known that the increase in coastal flood hazard is expected to continue due primarily to climate change. While, previous studies have advanced probabilistic approaches for estimating future coastal flood hazard, two seminal issues have received little attention: (1) sea level trend projections that arise as a consequence of climate change not being incorporated in nonstationary coastal flood frequency analysis and (2) traditional stationary approaches that estimate return periods are not suited for analysis of nonstationary water levels. In this paper, a regression approach for sea level rise estimation is proposed to detrend water levels. The peak-over-threshold approach is used to analyze the probabilistic behavior of detrended water levels via a generalized Pareto distribution. Two interpretations of return period—the expected waiting time until an exceedance event occurs and the time associated with the expected number of exceedance events equal to one—are elaborated in a nonstationary context. By incorporating the existing sea level trend projections and using two interpretations of return period, flood hazard curves with uncertainty (i.e., water levels vs. return periods) are developed to describe the probabilistic behavior of future coastal flood hazards. Two case studies are conducted: one for Boston, Massachusetts, and one for New York City, New York. [ABSTRACT FROM AUTHOR]

Ride-hailing services such as Lyft, Uber, and Cabify operate through smartphone apps and are a popular and growing mobility option in cities around the world. These companies can adjust their fares in real time using dynamic algorithms to balance the needs of drivers and riders, but it is still scarcely known how prices evolve at any given time. This research analyzes ride-hailing fares before and during the COVID-19 pandemic, focusing on applications of time series forecasting and machine learning models that may be useful for transport policy purposes. The Lyft Application Programming Interface was used to collect data on Lyft ride supply in Atlanta and Boston over 2 years (2019 and 2020). The Facebook Prophet model was used for long-term prediction to analyze the trends and global evolution of Lyft fares, while the Random Forest model was used for short-term prediction of ride-hailing fares. The results indicate that ride-hailing fares are affected during the COVID-19 pandemic, with values in the year 2020 being lower than those predicted by the models. The effects of fare peaks, uncontrollable events, and the impact of COVID-19 cases are also investigated. This study comes up with crucial policy recommendations for the ride-hailing market to better understand, regulate and integrate these services. [ABSTRACT FROM AUTHOR]

In this paper, it is aim to propose an instrumental variable rank estimation method for varying coefficient spatial autoregressive models. The newly proposed method provides a highly efficient and robust alternative to the existing quasi-maximum likelihood estimation or GMM estimation, and can be implemented using the existing R software package conveniently. Under mild conditions, the consistency and asymptotic normality of the resulting estimators are established. The finite sample properties of the proposed method are investigated through Monte Carlo simulation studies. Finally, the Boston house price data and crime data of Tokyo are analyzed to illustrate the usefulness of the proposed estimation method. [ABSTRACT FROM AUTHOR]

Over the past 40 years, college graduates in the USA have become increasingly concentrated in a small number of cities. This paper uses qualitative interviews to explore the processes bringing recent graduates of elite universities to one such city, metropolitan Boston, after graduation. Most respondents reported that their move to Boston was not driven by a clear preference for living there. Rather, they saw themselves as simultaneously choosing a job and a location in one bundled decision, with the job generally determining where they ended up. To reduce the cognitive complexity of the joint job-and-location search, graduates eliminated most options with minimal consideration. The options that remained were disproportionately in cities where the graduates or their universities had preexisting connections—even when the graduates themselves would have preferred to live elsewhere. The social nature of the post-college job search thus served to geographically concentrate these graduates beyond what either their own preferences or the geography of job opportunities would require. [ABSTRACT FROM AUTHOR]

Children experience and grapple with the ongoing effects of climate change in their daily lives. While they did not cause climate change nor should they have to solve it, children deserve educational opportunities to understand why and how it occurs as they prepare to address it. In this Methods and Strategies article, we share how children engaged in place-based art, science, and literacy activities designed to support them in further cultivating relationships with their ecological community and to communicate their findings with other children engaging in the same process across the three coastal communities of Boston, Toronto, and San Diego. Specifically, we highlight how crafting representations of their noticings and wonderings from family walks in their ecological communities supported children to analyze the interactions within ecosystems and express concern and care for the natural world as they engaged in the science practice of asking questions. We share how elementary teachers can support children in cultivating relationships with their local community as they make observations and ask questions to understand how climate change impacts their ecological communities. [ABSTRACT FROM AUTHOR]

High-dimensional feature selection is of particular interest to researchers. In some domains, such as microarray data, it is quite common for a group of highly correlated explanatory variables to be of equal importance for inclusion in the predictive model. This paper proposes a new hybrid feature selection approach that integrates feature screening based on Kendall's tau and Elastic Net regularized regression (K -EN). K -EN as an approach that embeds the Elastic Net, has the advantage of the grouping effect, which automatically includes all the highly correlated variables in the group. The K -EN approach offers insightful solutions to high-dimensional regression problems and improves Elastic Net performance since the screening phase is preceded by a step that further reduces the number of explanatory variables by removing those that disagree with the target based on Kendall's tau. The use of Kendall's tau further enhances Elastic Net performance, as it is robust enough to handle heavy-tailed distributions, non-parametric models, outliers, and non-normal data with greater ease. K -EN is therefore a time-saving approach. The proposed algorithm is evaluated on four simulation scenarios and four publicly available datasets, including riboflavin, eyedata, Longley, and Boston Housing, and achieves 0.2528, 0.0098, 0.1007, and 0.4121 respectively as the Mean Squared Error (MSE). K -EN's MSEs are the best compared to those achieved by the state-of-the-art approaches reviewed in this paper. In addition, K -EN selects up to 100% of relevant features when run on simulated data. [ABSTRACT FROM AUTHOR]

Tatiana Erukhimova, an Instructional Professor at Texas A&M University, has been awarded the 2024 David Halliday and Robert Resnick Award for Excellence in Undergraduate Physics Teaching. Erukhimova is known for her approach to teaching, which focuses on creating a strong sense of community and personal connection with her students. She uses innovative and research-backed pedagogy, including interactive lectures, problem-solving, peer instruction, and experimental demonstrations. Erukhimova has received numerous awards for her teaching and has also mentored graduate students pursuing instructional faculty positions. Additionally, she has created outreach programs that provide experiential learning opportunities for students beyond the classroom. Chandralekha Singh, a Distinguished Professor at the University of Pittsburgh, has been awarded the 2024 John David Jackson Excellence in Graduate Physics Education Award. Singh is recognized for her research in physics education and her contributions to graduate physics education at the national and international level. She has published high-quality papers and served on various committees within the American Association of Physics Teachers (AAPT). Singh's research focuses on quantum mechanics, cognitive issues in learning physics, and improving equity and inclusion in physics learning environments. She has also conducted workshops and conferences on these topics. [Extracted from the article]

Background: Asians and Asian Americans have the lowest rate of mental health service utilization (25%) in the US compared to other racial/ethnic groups (39 − 52%), despite high rates of depression, anxiety, and suicidal ideation. The lack of culturally-responsive mental health trainings hinders access to mental health services for these populations. We assessed the mental health priorities of Asian communities in Greater Boston and evaluated cultural responsiveness of the Mental Health First Aid (MHFA), a first-responder training teaching participants skills to recognize signs of mental health and substance use challenges, and how to appropriately respond. Methods: This is community-based participatory research with the Boston Chinatown Neighborhood Center (BCNC), Asian Women For Health (AWFH), and the Addressing Disparities in Asian Populations through Translational Research (ADAPT) Coalition. We conducted focus groups with community-based organization staff and community members to assess mental health priorities of Asian populations in Boston, MA. We then evaluated the utility and cultural-responsiveness of the English-language MHFA for Asian populations through pre- and post-training questionnaires and focus groups with community participants. Paired t-tests were used to evaluate questionnaire responses. Thematic analysis was used to analyze interviews. Results: In total, ten staff and eight community members participated in focus groups, and 24 community members completed the MHFA and pre- and post-training questionnaires. Common mental health challenges in the Asian communities reported by participants were loneliness, high stigma around mental illnesses, academic pressure, and acculturation stress. Compared to pre-training, MHFA participants demonstrated lower personal mental health stigma (p < 0.001) and higher mental health literacy (p = 0.04) post-training. Participants also noted the lack of data statistics and case studies relevant to Asian populations in the training, and desired the training be offered in languages spoken by Asian ethnic subgroups (e.g., Chinese, Vietnamese). Conclusion: Cultural-responsiveness of the MHFA for Asian populations could be improved with the inclusion of data and case studies that capture common mental health challenges in the Asian communities and with translation of the MHFA to non-English languages predominant in Asian communities. Increasing the cultural relevance and language accessibility of the MHFA could facilitate wider adoption of these trainings across communities and help to reduce mental health stigma and gaps in literacy and service utilization. [ABSTRACT FROM AUTHOR]

To inform clinical trial design and real-world precision pediatric oncology practice, we classified diagnoses, assessed the landscape of mutations, and identified genomic variants matching trials in a large unselected institutional cohort of solid tumors patients sequenced at Dana-Farber / Boston Children's Cancer and Blood Disorders Center. Tumors were sequenced with OncoPanel, a targeted next-generation DNA sequencing panel. Diagnoses were classified according to the International Classification of Diseases for Oncology (ICD-O-3.2). Over 6.5 years, 888 pediatric cancer patients with 95 distinct diagnoses had successful tumor sequencing. Overall, 33% (n = 289/888) of patients had at least 1 variant matching a precision oncology trial protocol, and 14% (41/289) were treated with molecularly targeted therapy. This study highlights opportunities to use genomic data from hospital-based sequencing performed either for research or clinical care to inform ongoing and future precision oncology clinical trials. Furthermore, the study results emphasize the importance of data sharing to define the genomic landscape and targeted treatment opportunities for the large group of rare pediatric cancers we encounter in clinical practice. Mutation profiling of pediatric cancers can help determine treatment options, however, large-scale datasets are rare. Here, the authors describe an institutional application of targeted sequencing to pediatric solid tumours, and identify potential therapeutic implications for identified mutations. [ABSTRACT FROM AUTHOR]

Background: Social needs inhibit receipt of timely medical care. Social needs screening is a vital part of comprehensive cancer care, and patient navigators are well-positioned to screen for and address social needs. This mixed methods project describes social needs screening implementation in a prospective pragmatic patient navigation intervention trial for minoritized women newly diagnosed with breast cancer. Methods: Translating Research Into Practice (TRIP) was conducted at five cancer care sites in Boston, MA from 2018 to 2022. The patient navigation intervention protocol included completion of a social needs screening survey covering 9 domains (e.g., food, transportation) within 90 days of intake. We estimated the proportion of patients who received a social needs screening within 90 days of navigation intake. A multivariable log binomial regression model estimated the adjusted rate ratios (aRR) and 95% confidence intervals (CI) of patient socio-demographic characteristics and screening delivery. Key informant interviews with navigators (n = 8) and patients (n = 21) assessed screening acceptability and factors that facilitate and impede implementation. Using a convergent, parallel mixed methods approach, findings from each data source were integrated to interpret study results. Results: Patients' (n = 588) mean age was 59 (SD = 13); 45% were non-Hispanic Black and 27% were Hispanic. Sixty-nine percent of patients in the navigators' caseloads received social needs screening. Patients of non-Hispanic Black race/ethnicity (aRR = 1.25; 95% CI = 1.06–1.48) and those with Medicare insurance (aRR = 1.13; 95% CI = 1.04–1.23) were more likely to be screened. Screening was universally acceptable to navigators and generally acceptable to patients. Systems-based supports for improving implementation were identified. Conclusions: Social needs screening was acceptable, yet with modest implementation. Continued systems-based efforts to integrate social needs screening in medical care are needed. [ABSTRACT FROM AUTHOR]

Background: In carpal tunnel syndrome (CTS), conservative management did not show satisfactory results, and some patients required revision surgery due to persistent or recurrent symptoms. Ultrasound (USG)-guided median nerve (MN) hydrodissection with a 5% dextrose injection is an advanced approach for treating symptoms of CTS. We prospectively investigated the patients to demonstrate the safety and effectiveness of this approach. Aims and Objectives: This study aims to evaluate the effect of USG-guided nerve hydrodissection using single injection of 5% dextrose on pain, MN conduction parameters, and functional status in patients with CTS of mild–to-moderate grade. The study also predicts about the safety of the procedure. Materials and Methods: A study was performed in the pain clinic of the tertiary care teaching institute of India for one year. The study included 15 patients diagnosed with mild-to-moderate CTS. The diagnosis was done on the basis of history, physical examination, and a nerve conduction velocity (NCV) study. Patients were given analgesics and NSAIDS and enrolled in the procedure. Parameters used for statistical analysis were Visual Analog Scale (VAS) scores, NCV study data (sensory conduction velocity [SNCV] and distal motor latency [DML]), and Boston carpal tunnel questionnaire (BCTQ) scores. Pre-injection parameters were compared with parameters 3 months after the injection to show the usefulness of this procedure. Results: A statistically significant reduction in VAS score was found in 74% of the cases (P<0.05). The nerve conduction study parameters have shown significantly higher SNCV and lower DML latency in 60% of cases (P=0.001 and P=0.001, respectively). Improved BCTQ scores were found in 80% of cases (for the symptom severity scale, P=0.001 and for the functional status scale, P<0.01). No complications such as allergic reactions, sensory loss, or paresis were recorded post-injection. However, transient injection site pain was present in all patients which did not last for more than 24 h. Conclusion: MN hydrodissection using a single injection of 5% dextrose under USG is a safe and effective approach offering pain relief, better MN conduction, and improved functional status in patients with CTS of mild-to-moderate grade. [ABSTRACT FROM AUTHOR]

Communitarians argue that social identity is formed through the connection between individuals and their communities. The purpose of this study is to examine how the institution of journalism functions as part of a larger community. Media influence and are influenced by the larger social, cultural, legal, political, and economic systems in which they operate. This textual analysis focused on the breakdown of four Boston institutions—the Catholic Church, the police force, the justice system, and the daily newspaper—depicted in the film Spotlight. These institutions failed their community, allowing decades of sexual abuse to go unrecognized and unpunished—at least until the Spotlight team investigated allegations against Catholic priests. Through the lens of communitarian ethics, the researchers argue that stakeholders must recognize the need for a strong community from which the press can report, explain, correct, and connect. [ABSTRACT FROM AUTHOR]

People experiencing homelessness are more likely to utilize emergency departments than their non-homeless counterparts. However, obtaining a bed in a homeless shelter for patients can be complex. To better understand the challenges of finding a safe discharge plan for homeless patients in the emergency department, our team conducted interviews with emergency department social workers and homeless shelter case managers in the Boston area. We identified and mapped the stages in the processes performed by both parties, identifying challenges with successful placement into a shelter. Furthermore, we assembled a data dictionary of key factors considered when assessing a patient's fit for a homeless shelter. By identifying bottlenecks and areas of opportunity, this study serves as a first step in enabling homeless individuals to receive the post-discharge assistance they require. [ABSTRACT FROM AUTHOR]

Background: Endovascular treatment of lower-extremity peripheral disease (PAD) is associated with higher complication rates and suboptimal outcomes in women. Atherectomy has shown favourable outcomes in calcified lesions, minimising the incidence of stent placement caused by recoil or flow-limiting dissection. To date, there are no published mid-term outcomes evaluating the performance of atherectomy differentiated by sex. This study aims to evaluate sex-specific outcomes and prognostic factors affecting the results of atherectomy-assisted endovascular treatment in severe PAD. Methods: A retrospective analysis was conducted at a single centre in Germany, initiated by physicians and not sponsored by industry, on patients presenting with Rutherford categories ranging from III to V and featuring de novo occlusive or stenotic lesions of the superficial femoral (SFA) and/or popliteal arteries. The intervention involved rotational atherectomy-assisted angioplasty utilising the Jetstream (Boston, US®) device. The point of interest of this study was postinterventional clinical improvement as well as mid-term outcomes, including primary patency, over a targeted 2-year follow-up period. Statistical analysis utilised Cox regression (survival analysis) to calculate hazard ratios according to sex category. Comparative survival analysis was performed using the log-rank test and visually represented through Kaplan–Meier curves. Risk factors associated with absence of clinical improvement were examined across both sex groups utilising the chi-square or Fisher exact test, as appropriate. Results: A total of 98 patients (103 limbs) were initially included, with >75% having moderate-to-severe lesion calcification (>50%). A total of 84 patients (97 limbs, 62 male and 35 female) proceeded to a 2-year follow-up (mean 16.4 months for males and 16.1 for females) after a successful index procedure. Age distribution, Rutherford class, diabetes, chronic kidney disease (CKD), target vessel, lesion type, and length were balanced among both groups. Similar primary patency rates, of 89% among female and 91% among male limbs, were observed (p = 0.471). Female patients exhibited a lower rate of clinical improvement based on the Rutherford scale in comparison to males (80.6% vs. 94.5%, p = 0.048). CDK was the only significant prognostic factor across pooled data (odds ratio for CKD: 15.15, p < 0.001). Conclusions: Rotational atherectomy showed comparably high rates of mid-term primary patency, with low rates of bailout stent placement. These findings highlight the beneficial use of atherectomy in female patients who are per se at risk for higher rates of complications during and after endovascular interventions. [ABSTRACT FROM AUTHOR]

Bike sharing systems gain traction worldwide, but previous research pay less attention to the more detailed operating characteristics at station level. This study aims to fill this void in the literature by looking into the stations' performance with considering systemic intervention and user-driven usage. Methodologically, an innovative approach that captures the underlying relevance of trip records is proposed firstly to identify the bicycle-based operating states in its lifecycle, such as being redistributed, parked, or used. From bike to station, all the bicycle-based operating status information can be linked to associated stations, consequently, station vitality and station pattern are refined into stations' operating performance. In addition to rational classification and discussion of operating features, this study has explored the impact of surrounding built environment on these specific operating features instead of simple trip intensity. To test the proposed methodology, trip record data from the bike sharing system of Boston in 2019 is used. The results indicate that user-driven and manual-scheduling bike movements are all particularly relevant to keeping stations' sustainable daily operation, but vary across the stations in their ratio. In terms of station vitality and station pattern, some stations would embody the nature of high-output-scheduling, low-bike-turnover, or high-input-scheduling relative to the baseline scenario of operating performance. Heterogeneity of stations in operating is also proved to be caused by the surrounding built environment. The outcomes and methodological framework would facilitate the assessment of bike sharing system operating state at station level, as well as instilling new insights into bike sharing system design. [ABSTRACT FROM AUTHOR]

We show the invalidity of finitary counterparts for three classification theorems: The preservation of being a Bernoulli shift through factors, Sinai's factor theorem, and the weak Pinsker property. We construct a finitary factor of an i.i.d. process which is not finitarily isomorphic to an i.i.d. process, showing that being finitarily Bernoulli is not preserved through finitary factors. This refutes a conjecture of M. Smorodinsky [ Finitary isomorphism of m-dependent processes , Amer. Math. Soc., Birkhauser, Providence, RI, 1992, pp. 373–376], which was first suggested by D. Rudolph [ A characterization of those processes finitarily isomorphic to a Bernoulli shift , Birkhäuser, Boston, Mass., 1981, pp. 1–64]. We further show that any ergodic system is isomorphic to a process none of whose finitary factors are i.i.d. processes, and in particular, there is no general finitary Sinai's factor theorem for ergodic processes. Another consequence of this result is the invalidity of a finitary weak Pinsker property, answering a question of G. Pete and T. Austin [Math. Inst. Hautes Études Sci. 128 (2018), 1–119]. [ABSTRACT FROM AUTHOR]

Engineering multilayer networks that efficiently connect sets of points in space is a crucial task in all practical applications that concern the transport of people or the delivery of goods. Unfortunately, our current theoretical understanding of the shape of such optimal transport networks is quite limited. Not much is known about how the topology of the optimal network changes as a function of its size, the relative efficiency of its layers, and the cost of switching between layers. Here, we show that optimal networks undergo sharp transitions from symmetric to asymmetric shapes, indicating that it is sometimes better to avoid serving a whole area to save on switching costs. Also, we analyze the real transportation networks of the cities of Atlanta, Boston, and Toronto using our theoretical framework and find that they are farther away from their optimal shapes as traffic congestion increases. Finding an optimal shape for transport networks, represented as multilayer structures, is a challenging problem. The authors propose analytical and computational frameworks to analyze sharp transitions from symmetric to asymmetric shapes in optimal networks, that can be applied for planning and development of improved multimodal transportation systems within a city. [ABSTRACT FROM AUTHOR]

Introduction and objective: The ailment commonly referred to as Boston exanthem disease is also known as hand, foot and mouth disease (HFMD). It is an infectious viral ailment usually of mild nature, triggered by enteroviruses and the coxsackie virus. Typical symptoms of HFMD include elevated temperature, fatigue, reduced appetite, abdominal and throat discomfort, painful mouth sores, and skin lesions. The incubation period ranges from 3-6 days, with symptoms persisting for 7-10 days. Today, the established diagnostic criteria for HFMD rely mainly on clinical symptoms and patient history. Most HFMD patients receive outpatient care with supportive measures alone, while isolation is recommended to reduce disease transmission. Generally, HFMD is mild and does not result in permanent damage. Dehydration stands as the primary complication, while the most severe consequences are associated with the central nervous system (CNS). This review was aimed at exploring the recent literature on HFMD, focusing on its epidemiology, aetiological factors, and novel strategies for its prevention and management. Material and methods: The authors' main goal was to summarise current scientific reports on the researched topic based on databases such as PubMed, Google Scholar, and taking into account their own materials (photos). Conclusions: The prevalence of this illness is rising. It is crucial to highlight its highly contagious nature, making it capable of rapid and widespread transmission. Understanding Boston exanthem disease and encompassing both typical and atypical symptoms is essential for accurate diagnosis and effective treatment protocols. This article discusses the most recent literature concerning HFMD, with a special focus on epidemiology, its defining traits and causative factors, and emerging strategies for its prevention and management. [ABSTRACT FROM AUTHOR]

In real estate valuation using the Hedonic Price Model (HPM) estimated via Ordinary Least Squares (OLS) regression, subjectivity and measurement errors in the independent variables violate the Gauss–Markov theorem assumption of a non-random coefficient matrix, leading to biased parameter estimates and incorrect precision assessments. In this contribution, the Errors-in-Variables model equipped with Total Least Squares (TLS) estimation is proposed to address these issues. It fully considers random errors in both dependent and independent variables. An iterative algorithm is provided, and posterior accuracy estimates are provided to validate its effectiveness. Monte Carlo simulations demonstrate that TLS provides more accurate solutions than OLS, significantly improving the root mean square error by over 70%. Empirical experiments on datasets from Boston and Wuhan further confirm the superior performance of TLS, which consistently yields a higher coefficient of determination and a lower posterior variance factor, which shows its more substantial explanatory power for the data. Moreover, TLS shows comparable or slightly superior performance in terms of prediction accuracy. These results make it a compelling and practical method to enhance the HPM. [ABSTRACT FROM AUTHOR]

The article discusses the symposium titled "Information Privacy Law at the Crossroads" that was held at Boston University School of Law in Boston, U.S. on November 3, 2023. Topics discussed include the impact of privacy loss on minoritized communities, the use of privacy as an antisubordination legal tool and the role of privacy in advancing values such as autonomy and equality. The attendees included Woody Hartzog, Organizer of the symposium and Editor-in-Chief, Keenan Hunt-Stone.

Background: Different split regimens of polyethylene glycol are routinely used and no guidelines are available to select an optimal protocol of ingestion. This study aims to compare the efficacy and side effect profile of two different regimens of polyethylene glycol bowel preparation solution: PEG (3 + 1) vs. PEG (2 + 2). Methods: 240 patients above the age of 18 years were included in the study between June 1st and November 31st, 2023. Patients were randomly assigned either to Group A, consisting of 115 patients receiving a 3 L of PEG the night before the colonoscopy, and 1 L the same morning of the procedure. Or to group B, where 125 patients ingested 2 L the night before the procedure, and the remaining 2 L the same morning. The cleansing efficacy was evaluated by the attending endoscopist using the Boston Bowel Preparation Scale, through a score assigned for each segment of the colon (0–3). Side effects, tolerability, and willingness to retake the same preparation were listed by an independent investigator using a questionnaire administered before the procedure. Results: A higher percentage of patients had gastric fullness with the 3 + 1 vs. 2 + 2 preparation (58.3% vs. 31.2%; p <.001). A higher Boston bowel preparation score was seen in patients who took the 2 + 2 vs. 3 + 1 preparation (7.87 vs. 7.23). Using the 2 + 2 preparation was significantly associated with higher Boston bowel preparation scores vs. the 3 + 1 preparation (OR = 1.37, p =.001, 95% CI 1.14, 1.64). After adjustment over other variables (age, gender, comorbidities, previous abdominal surgeries, presence of adenoma, and time between last dose and colonoscopy), results remained the same (aOR = 1.34, p =.003, 95% CI 1.10, 1.62). Conclusion: While both (2 + 2) and (3 + 1) regimens of polyethylene glycol are a good choice for a successful colonoscopy, we recommend the use of (2 + 2) regimen for its superior efficacy in bowel cleansing. [ABSTRACT FROM AUTHOR]

Background: Carpal tunnel syndrome is a frequently observed condition affecting the wrists and fingers, characterized by numbness, tingling, and sometimes pain. Objective: To evaluate and compare the efficiency of magnetic field therapy and ultrasound therapy in rehabilitating women with carpal tunnel syndrome (CTS). Patients and Methods: Forty women with mild to moderate CTS were included in the study, and an electromyography (EMG) and examination confirmed the diagnosis. The participants were assigned into two groups. Group A received magnetic field therapy, and Group B received ultrasound therapy. Patients for each group received a six-session clinical evaluation. The outcomes included the Boston Carpal Tunnel Syndrome Questionnaire (BCTSQ), handgrip strength, wrist joint movements (flexion and extension), as well as the Visual Analogue Scale (VAS). Results: The paired t-test analyses demonstrate a significant improvement in the Boston questionnaire and VAS in both intervention groups at a P-value ≤0.05. The independent sample t-test analysis for post-intervention for both groups showed superiority for magnetic field therapy; no significant differences were observed in the improvement of wrist movement (Flexion = 0.66, Extension = 0.71); the Visual Analog Scale (VAS) has been improved in both treatment groups with dominance for ultrasound therapy. Conclusion: Both magnetic field and ultrasound therapy effectively treat women with carpal tunnel syndrome. Magnetic field therapy was statistically superior to ultrasound. [ABSTRACT FROM AUTHOR]

An improved algorithm based on tent chaotic map and difference mechanism is proposed to address the problem of poor population diversity and easily falling into local optimum in the lion swarm optimization algorithm. At first, an improved tent chaotic map is introduced to initialize the population position to increase diversity and ergodicity, thereby improving the global search capability. Second, a perturbation factor combined with a differential evolution mechanism is introduced to realize the adaptive positioning of the lioness and improve its ability to jump out of the local optimum. Following that, the proposed algorithm's superiority is tested on 10 multi-type benchmark functions and compared to six swarm intelligence algorithms. Finally, the improved algorithm is applied to optimize the initial weights and thresholds of BP neural networks. Then a new model is proposed and applied to the study of house price prediction. Experiments are conducted on two standard datasets, and results show that the proposed model's convergence speed, accuracy, and stability are better than the other three methods. On the Boston dataset, the mean square error of the training set and test set is 0.0016 and 0.0052, respectively, and the absolute error of more than 98% of the data is within 3%. On the Californian dataset, the mean square error of the training set and test set is 0.0149 and 0.0151, respectively, with more than 92.3% of the data within 5% absolute error, further validating the effectiveness, higher accuracy, and convergence performance of the proposed model. [ABSTRACT FROM AUTHOR]

Today, robotics technologies are revolutionizing surveying and construction in AEC fields, enhancing precision, safety, and efficiency and also in the realm of Cultural Heritage knowledge and protection, the integration of cutting-edge technologies is reshaping consolidated surveying methods for documentation, especially in risk scenarios. One such innovation making waves is the use of mobile mapping systems, where automation and expediency are the determining factors in technological development, both in the direction of in indoor positioning (visual/LiDAR SLAM, UWB, etc.) and 3D mapping of known and unknown spaces. The BLK ARC by Leica, equipping the Agile Mobile Robot Spot® by Boston Dynamics, as a dynamic sensing platform, is here presented and discussed. BLK ARC is part of a diverse landscape of mobile mapping systems, each offering unique features and specifications tailored to different surveying needs, from handheld devices and wearable systems, to vehicle-mounted systems, the options vary in dimension, weight, price, and technical capabilities and the recent companies and research are largely focusing on them. A preliminary evaluation takes into consideration the dual dynamic-static 3D data-types, considering local and global accuracy of the 3D data delivered from the first experimental tests in a case study. Different metrics have been considered including acquisition time, precision, resolution, density, accuracy, roughness, and completeness of the acquired data. [ABSTRACT FROM AUTHOR]

This study considers the problem of random assignment of a set of objects to a set of agents based on strict ordinal preferences of the agents. We analyze the fractional Boston rule, which is a generalization of the classical Boston rule to random assignment environments. We introduce two new axioms—stochastic dominance (sd)-rank-efficiency and equal-rank envy-freeness—which are respectively efficiency and fairness conditions that respect preference ranks. Sd-rank-efficiency implies ordinal efficiency, which is an efficiency concept defined by Bogomolnaia and Moulin (J Econ Theory 100(2):295–328, 2001) for random assignment environments in the sense of first-order stochastic dominance. Equal-rank envy-freeness implies equal treatment of equals. Sd-rank-efficiency and equal-rank envy-freeness characterize the fractional Boston rule. [ABSTRACT FROM AUTHOR]

Determining the predictor variables that have a non-linear effect as well as those that have a linear effect on the response variable is crucial in additive semi-parametric models. This issue has been extensively investigated by many researchers in the area of semi-parametric linear additive models, and various separation methods are proposed by the authors. A popular issue that might affect both estimation and separation results is the existence of outliers among the observations. In order to address this lack of sensitivity towards extreme observations, robust estimating approaches are frequently applied. We propose a robust method for simultaneously identifying the linear and nonlinear components of a semi-parametric linear additive model, even in the presence of outliers in the observations. Additionally, this model is sparse in that it may be used to determine which explanatory variables are ineffective by giving accurate zero estimates for their coefficients. To assess the effectiveness of the proposed method, a comprehensive Monte Carlo simulation study is conducted along with an application to investigate the dataset, which includes Boston property prices dataset. [ABSTRACT FROM AUTHOR]

Langlands [ On the classification of irreducible representations of real algebraic groups , Math. Surveys Monogr., vol. 31, Amer. Math. Soc., Providence, RI, 1989, pp. 101–170] defined L-packets for real reductive groups. In order to refine the local Langlands correspondence, Adams-Barbasch-Vogan [ The Langlands classification and irreducible characters for real reductive groups , Progress in Mathematics, vol. 104, Birkhäuser Boston, Inc., Boston, MA, 1992] combined L-packets over all real forms belonging to an inner class. In the tempered setting, using different methods, Kaletha [Ann. of Math. (2) 184 (2016), pp. 559–632] also defines such combined L-packets with a refinement to the local Langlands correspondence. We prove that the tempered L-packets of Adams-Barbasch-Vogan and Kaletha are the same and are parameterized identically. [ABSTRACT FROM AUTHOR]

Cycling is a potential tool to mitigate many of the problems faced by urban populations today. Encouraging the use of bicycles as a legitimate mobility tool, however, demands adequate knowledge of current mobility patterns, such as locations of trip generation and attraction. Unfortunately, cities usually do not gather enough data to adequately understand cycling demand. We propose models based on spatial econometrics and gradient boosted regression trees which can be trained with data from cities with mature cycling cultures and then applied to cities still in their cycling infancy to supply city officials with a better estimate of potential future OD matrices. We perform a case study in the Boston Metropolitan Area and show results comparing both types of models. [ABSTRACT FROM AUTHOR]

Introduction: Carpal tunnel syndrome (CTS) is the most common entrapment neuropathy. There are several factors that influence the severity of CTS. The purpose of this study was to explore the severity of CTS in hypothyroid patients. Methods: This cross-sectional study was conducted in the university clinic. Seventy-six participants with a clinically and electrophysiological confirmed diagnosis of CTS were included in the study. The demographic data and severity of CTS were analyzed based on the presence (n=38) or the absence (n=38) of primary hypothyroid disease. Thirty-eight hypothyroid patients who were being treated were included in this study. For the assessment of the severity of CTS, the Boston questionnaire (BCTQ) and electrodiagnostic tests were used. For data analysis, an independent sample t-test and chi-squared test were carried out. A P<0.05 was considered significant. Results: The mean age of hypothyroid and non-hypothyroid CTS patients was 46.21±7.22 and 44.24±8.02 years, respectively. Body mass index (BMI) was >30 kg/m² in both groups. There was no significant difference in demographic data among the two groups. The mean score of symptom severity in hypothyroid and non-hypothyroid-CTS patients were 30.37±10.84 and 35.89±7.19, and also functional status was 21.71±9.04 and 25.92±6.62, respectively. There was a significant difference between the two groups, in terms of symptom severity scale (P=0.017, 95% CI, 31.14%, 35.48%) and functional status scale (P=0.023, 95% CI, 21.95%, 25.67%). In terms of electrophysiological findings, there was no statistically significant difference between these two groups. Conclusion: The results of this study indicated that, contrary to expectation, the severity of CTS is higher in non-hypothyroid patients than in hypothyroid patients. [ABSTRACT FROM AUTHOR]

Literature on entrepreneurial ecosystems (EEs) has grown rapidly over the past 5 years, using the concept as a framework to understand regional clusters of entrepreneurship. This article reviews, critiques, and extends the concept of the EE, arguing for its relevance in studying the political economy of urban space. To make this argument, we distinguish between niche EEs (NEEs) and growth EEs (GEEs). This distinction is based on the overlapping but distinct networks of actors and institutions forming each type of EE and also reflects broadly different relationships to growth and productivity, the entrepreneurial subject, global and local scales, and financial ecologies. We argue that EE research has largely focused on GEEs to the neglect of NEEs; by broadening the EE concept, we address shortcomings in the treatment of small businesses, financial relations, social difference, as well as urban politics within the EE literature. Drawing on the EE literature and interviews from a case study of Boston, we show that the infrastructure of GEEs and NEEs are not only "for" fast- and slow-growing businesses, respectively, but reinforce social and economic differences. While NEEs do redistribute resources to marginalized entrepreneurs, these resources are focused on building businesses and only indirectly related to the needs of marginalized communities and equitable development more generally. [ABSTRACT FROM AUTHOR]

Partially linear models find extensive application in biometrics, econometrics, social sciences, and various other fields due to their versatility in accommodating both parametric and nonparametric elements. This study aims to establish statistical inference for the parametric component effects within these models, employing a nonparametric empirical likelihood approach. The proposed method involves a projection step to eliminate the nuisance nonparametric component and utilizes an empirical-likelihood-based technique, along with the Bartlett correction, to enhance the coverage probability of the confidence interval for the parameter of interest. This method demonstrates robustness in handling normally and non-normally distributed errors. The proposed empirical likelihood ratio statistic converges to a limiting chi-square distribution under certain regulations. Simulation studies demonstrate that this method provides better inference in terms of coverage probabilities compared to the conventional normal-approximation-based method. The proposed method is illustrated by analyzing the Boston housing data from a real study. [ABSTRACT FROM AUTHOR]