bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mandibular overdenture with a single implant in the canine region (c-SIMO): a feasibility study
Authors: Maniewicz Sabrina , Curado Thalita Fernandes Fleury , Srinivasan Murali , Leles Cláudio Rodrigues , Müller Frauke 
Published: May 2024

Abstract
Objectives
The aim of this multi-center pilot study was to assess the viability and feasibility of a novel treatment concept – the canine-positioned single implant mandibular overdenture (c-SIMO), with the single implant placed on the patient's preferred chewing side instead of the midline.

Materials and methods
Participants received a single implant in the canine region of their preferred chewing side, based on an Asymmetry Index observed during mastication. The pre-existing mandibular denture was transformed into a c-SIMO on a spherical attachment. The primary outcome was oral health-related quality of life (OHRQoL), measured with GOHAI and OHIP-EDENT. Secondary outcomes included denture satisfaction index (DSI), chewing efficiency (CE), maximum bite force (MBF), implant survival and success, and prosthetic maintenance. Data analysis included descriptive statistics and bivariate comparison tests.

Results
Fifteen participants received the c-SIMO treatment (mean age: 69.9 ± 7.0). Implant success and survival rates were 100% at 1 year. Patient-reported outcome measures improved significantly compared to pre-treatment values (OHIP-EDENT: p = 0.001; DSI: p = 0.001; GOHAI: p = 0.002). Masticatory outcomes also improved significantly (CE: p = 0.001; overall MBF: p = 0.005). Post-implant, MBF was significantly higher in the ipsilateral side compared to the contralateral side at 2 weeks (p = 0.019) and 3 months (p = 0.015), but no longer at T3 (p = 0.730). Common prosthodontic events included denture base adjustments (n = 17) and matrix activation (n = 9).

Conclusions
This pilot study concludes that c-SIMO is a promising treatment option, and a potential alternative to the single midline implant overdenture.

Clinical relevance
The novel treatment concept of a canine-positioned single implant mandibular overdenture could be a viable treatment alternative to the midline positioning.
A meta-analysis of the efficacy and safety of trofinetide in patients with rett syndrome
Authors: Abo Zeid Mohamed , Elrosasy Amr , Mohamed Rashad G. , Ghazou Alina , Goufa Elarbi , Hassan Nourhan , Abuzaid Yasmine 
Published: May 2024

Abstract
Background
Rett syndrome (RTT) is an uncommon inherited neurodevelopmental disorder that affects brain development, mostly in females. It results from mutation in MECP2 gene in the long arm (q) of the X chromosome.

Objective
Trofinetide is a recently developed drug that has a neuroprotective effect on neurons, and it is our aim in this meta-analysis to evaluate its efficacy and safety in treating Rett syndrome patients.

Methods
We searched 5 databases (PubMed, Scopus, Embase, Web of Science, and Cochrane Library databases) to identify randomized controlled trials (RCTs) comparing Trofinetide and placebo in patients with Rett syndrome until August 13, 2023.Our primary outcomes were the Clinical Global Impression-Improvement (CGI) and the Rett syndrome Behavior Questionnaire (RSBQ). We used Risk of Bias Assessment tool-2 (ROB2) to assess the methodological quality of the included randomized controlled trials.

Results
Three RCTs with a total of 325 patients were included with a follow-up duration ranging from one month to three months. 186 patients received the intervention drug (Trofinetide) and 138 received the placebo. Trofinetide was found to reduce CGI and RSBQ significantly more than placebo (MD = -0.35, 95% CI [-0.52 to -0.18], P 0.0001), (MD = -3.40, 95% CI [-3.69 to -3.12], P 0.00001) respectively. Most adverse events did not show any statistical difference between Trofinetide and the placebo.

Conclusion
Trofinetide offers promise as a potential effective and safe therapeutic opportunity for a population without many available treatments, with improvements seen on both CGI and RSBQ assessments and no severe adverse effects reported.
Evaluation of the effects of different photosensitizers used in antimicrobial photodynamic therapy on tooth discoloration: spectrophotometric analysis
Authors: Şahin Özge Hür , Korucu Hulde , Aydin Zeliha Uğur 
Published: May 2024

Abstract

Background
Tooth discoloration is a common concern in antimicrobial photodynamic therapy (aPDT) using various photosensitizers (PS). Toluidine Blue (TB), Methylene Blue (MB), Phthalocyanine (Pc), and 2-mercaptopyridine-substituted zinc phthalocyanine (TM-ZnPc) are among those studied, but their relative impacts on tooth discoloration remain unclear.

Aim
This study aimed to compare the effects of TB, MB, Pc, and TM-ZnPc in aPDT on tooth discoloration, utilizing a controlled experimental setup.

Materials and Methods
The study comprised seventy-five single-rooted incisors with root canals. Following meticulous preparation, a standardized area on the crown surface was designated for examination, and precise measurements of the initial tooth colors were recorded. Samples were randomly divided into five groups: Negative control, MB, TM, Pc, and TM-ZnPc. Photoactivation was performed using LED light, and color measurements were taken at multiple time points up to 90 days. Data were converted to Lab* color values of the CIE Lab* color system (International Commission on Illumination, Vienna, Austria), and ΔE values were calculated. Statistical analysis was performed using Two-way ANOVA and Post-Hoc Tukey tests (p < 0.05).

Results
At day 7 and 30, TM-ZnPc and Pc caused less discoloration compared to MB and TB. TM-ZnPc caused more tooth discoloration compared to Pc (p < 0.05). Compared to baseline, MB and TM-ZnPc caused more tooth discoloration at 30 days and TB caused more tooth discoloration at 90 days (p < 0.05). No significant difference was observed in terms of tooth discoloration at all periods evaluated after Pc application (p > 0.05). All photosensitizers tested in the study caused tooth coloration.

Conclusion
All PS induced clinically detectable tooth discoloration, with TB and MB causing more significant discoloration compared to Pc and TM-ZnPc at certain time points. TM-ZnPc and Pc demonstrated more stable coloration levels over time, suggesting their potential reliability in aPDT applications. This study highlights the importance of selecting appropriate PS to minimize tooth discoloration in aPDT, with Pc showing promise in this regard.
When is neoadjuvant chemotherapy indicated in rectal neuroendocrine tumors? An analysis of the National Cancer Database
Authors: Gefen R. , Emile S. H. , Horesh N. , Garoufalia Z. , Freund M. R. , Wexner S. D. 
Published: May 2024

Abstract
Background
Rectal neuroendocrine tumors (rNET) are rare and challenging to manage. While most patients with small rNET can be definitively treated with local excision, the role of chemotherapy in general and neoadjuvant therapy particularly in managing advanced rNET has not been well established. Therefore, this study aimed to determine which patients with rNET may gain a survival benefit from neoadjuvant chemotherapy.

Methods
A retrospective cohort analysis of all patients who underwent surgical resection of rNET in the US National Cancer Database (NCDB) (2004–2019) was performed. First, univariate and multivariate Cox regression analyses were performed to determine the independent predictors of poor overall survival (OS) and define the high-risk groups. Afterward, stratified OS analyses were performed for each high-risk group to assess whether neoadjuvant chemotherapy had a survival benefit in each group.

Results
A total of 1837 patients (49.8% female; mean age 56.6 ± 12.3 years) underwent radical resection of a rNET. Tumors > 20 mm in size, clinical T4 tumors, poorly differentiated tumors, and metastatic disease were independent predictors of worse OS and were defined as high-risk groups. Neoadjuvant chemotherapy did not have a significant survival benefit in any of the high-risk groups, except for patients with high-grade rNETs where neoadjuvant therapy significantly improved OS to a mean of 30.9 months compared with 15.9 months when neoadjuvant therapy was not given (p = 0.006).

Conclusions
Neoadjuvant chemotherapy improved the OS of patients with high-grade rNET by 15 months and may be indicated for this group.
Risk overbounding for ionospheric gradient monitor using geometry-free double differenced carrier phase measurements
Authors: Li Wang , Jiang Yiping 
Published: May 2024

AbstractIonosphere anomaly can cause large spatial gradients in the double-differenced carrier phase (DDCP) measurements. Taking advantage of this characteristic, the ionospheric gradient monitor (IGM) is designed with multiple ground reference stations to detect threatening ionospheric gradients for safety of life applications. An optimal IGM should be most sensitive to ionospheric gradients and least sensitive to other errors. However, current IGM suffers from the influence of tropospheric error, which can degrade monitor performance under extreme weather conditions by causing risks of false alarms and missed detections. To address this issue, an alternative IGM is proposed using the geometry-free combination of DDCP as the test statistic. Ambiguity resolution procedure is designed for estimating the ambiguity term in the test statistic. The risk induced by the wrong ambiguity fix and tropospheric error are analyzed and bounded with required averaging period and minimum baseline length. The results show that the proposed theoretical IGM is capable of achieving probability of false alarm of 10–8 and probability of missed detection of 10–6 with a filtering period of 612 s and baseline length of 371.7 m or a filtering period of 544 s and baseline length of 384.4 m. The experimental results using data collected from Hong Kong Satellite Positioning Reference Station Network demonstrate that the performance of the proposed theoretical IGM is comparable to that of the existing detection algorithm.
The impact of government policies and regulations on the subjective well-being of farmers in two rural mountain areas of Italy
Authors: Whitaker Sarah H. 
Published: May 2024

AbstractThe sustainable development of rural areas involves guaranteeing the quality of life and well-being of people who live in those areas. Existing studies on farmer health and well-being have revealed high levels of stress and low well-being, with government regulations emerging as a key stressor. This ethnographic study takes smallholder farmers in two rural mountain areas of Italy, one in the central Alps and one in the northwest Apennines, as its focus. It asks how and why the current policy and regulatory context of agriculture affects farmer well-being. Interviews and participant observation were conducted with 104 farmers. Three common scenarios emerged that negatively affect farmer well-being. First, policies and regulations designed for lowland areas do not always make sense when applied in the mountains. Second, when subsidies are put into effect at the local level, the reality of their implementation can veer away from the original goals of the funding program and have unintended effects on farmer well-being, agricultural practices, and the environment. Finally, when regulations are implemented on farms in rural mountain areas, the primacy of a techno-scientific knowledge system over other, local and place-based knowledge systems is exposed. These three scenarios affect well-being by eliciting feelings of stress, frustration, and disillusionment; by reducing farmer control over their work; and by fostering the perception that farming is not valued by society. They also create conditions of inequality and insecurity. The ways in which government policies and regulations play out on mountain farms can erode trust in government institutions, lead to an us versus them mentality, and contribute to the further abandonment of agriculture and rural areas.
n-Ary aggregation operators on function spaces: perspective of construction
Authors: Qiao Junsheng 
Published: May 2024

AbstractFor disposing numerous practical application problems involving expert systems, decision-making, image processing, classifications and etc, the investigations on the constructions and basic properties ofn-ary aggregation operators (nAAOs) have always been a hot research topic with important research value and significance at theoretical investigations on aggregation operators (AOs). Herein, first, we propose a method for constructing nAAOs on function spaces via a family of known ones defined on a bounded poset, where those function spaces are composed by all fuzzy sets with that bounded poset as the truth values set. This method is different from the existing construction methods of nAAOs on bounded posets and provides a unified way of constructing usual nAAOs (like t-norms, uninorms, overlap functions, etc.) on function spaces via a family of known ones. Second, we present notion of representable nAAOs on function spaces and afford their equivalent characterization. Third, we discuss some vital properties of representable nAAOs on function spaces. Fourth, it is worth noticing that the obtained results cover the cases of nAAOs on function spaces composed of all interval-valued fuzzy sets and type-2 fuzzy sets when underlying bounded poset is taken as the corresponding truth values set, respectively. As a consequence, the theoretical results obtained herein have certain promotion and basic theoretical value for the mining of new potential applications of nAAOs in real problems, especially in expert systems, decision-making, image processing and etc.
Robust, extended goal programming with uncertainty sets: an application to a multi-objective portfolio selection problem leveraging DEA
Authors: Mohseny-Tonekabony Naeem , Sadjadi Seyed Jafar , Mohammadi Emran , Tamiz Mehrdad , Jones Dylan F. 
Published: May 2024

AbstractThis study presents a two-phase approach of Data Envelopment Analysis (DEA) and Goal Programming (GP) for portfolio selection, representing a pioneering attempt at combining these techniques within the context of portfolio selection. The approach expands on the conventional risk and return framework by incorporating additional financial factors and addressing data uncertainty, which allows for a thorough examination of portfolio outcomes while accommodating investor preferences and conservatism levels. The initial phase employs a super-efficiency DEA model to streamline asset selection by identifying suitable investment candidates based on efficiency scores, setting the stage for subsequent portfolio optimization. The second phase leverages the Extended GP (EGP) framework, which facilitates the comprehensive incorporation of investor preferences to determine the optimal weights of the efficient assets previously identified within the portfolio. Each goal is tailored to reflect specific financial factors spanning both technical and fundamental aspects. To tackle data uncertainty, robust optimization is applied. The research contributes to the robust GP (RGP) literature by analyzing new RGP variants, overcoming limitations of traditional and other uncertain GP models by incorporating uncertainty sets. Robust counterparts of the EGP models are accordingly developed using polyhedral and combined interval and polyhedral uncertainty sets, providing a flexible representation of uncertainty in financial markets. Empirical results, based on real data from the Tehran Stock Exchange comprising 779 assets, demonstrate the superiority of the proposed approach over traditional portfolio selection methods across various uncertainty settings. Additionally, a comprehensive sensitivity analysis investigates the impact of uncertainty levels on the robust EGP models. The proposed framework offers guidance to investors and fund managers through a pragmatic approach, enabling informed and robust portfolio decisions by considering efficiency, uncertainty, and extended financial factors.
Analyzing the robustness of decentralized horizontal and vertical federated learning architectures in a non-IID scenario
Authors: Sánchez Sánchez Pedro Miguel , Huertas Celdrán Alberto , Martínez Pérez Enrique Tomás , Demeter Daniel , Bovet Gérôme , Martínez Pérez Gregorio , Stiller Burkhard 
Published: May 2024

AbstractFederated learning (FL) enables participants to collaboratively train machine and deep learning models while safeguarding data privacy. However, the FL paradigm still has drawbacks that affect its trustworthiness, as malicious participants could launch adversarial attacks against the training process. Previous research has examined the robustness of horizontal FL scenarios under various attacks. However, there is a lack of research evaluating the robustness of decentralized vertical FL and comparing it with horizontal FL architectures affected by adversarial attacks. Therefore, this study proposes three decentralized FL architectures: HoriChain, VertiChain, and VertiComb. These architectures feature different neural networks and training protocols suitable for horizontal and vertical scenarios. Subsequently, a decentralized, privacy-preserving, and federated use case with non-IID data to classify handwritten digits is deployed to assess the performance of the three architectures. Finally, a series of experiments computes and compares the robustness of the proposed architectures when they are affected by different data poisoning methods, including image watermarks and gradient poisoning adversarial attacks. The experiments demonstrate that while specific configurations of both attacks can undermine the classification performance of the architectures, HoriChain is the most robust one.
The Ethical Embeddedness of the Economic Inequality Debate
Authors: Ketokivi Mikko , Fosse Sebastien M. , Kawalek Peter 
Published: May 2024

Abstract
How do scholars formulate arguments about economic inequality? What is the role of empirical analysis? In what ways, if any, is the debate informed by ethical considerations? In this paper, we address these questions by evaluating one of the main arguments in Thomas Piketty’s 2014 book Capital in the Twenty-First Century, along with its endorsements and rebuttals. Applying Stephen Toulmin’s model of arguments to Piketty unearths a complex argument structure that must be understood for an evaluation to be possible. Of particular importance are the warrants that Piketty used to justify his conclusions from the empirical material. Our analysis revealed that the most influential rebuttals were targeted not at Piketty’s empirical inferences but the way he used these inferences to justify his claims. We also found value judgments to be an essential part of the justification process, making Piketty’s claims ultimately embedded in ethical considerations. We conclude that value judgments are intrinsic to scholarly arguments not only in economic inequality debates but also more broadly.
Activation of lipophagy ameliorates cadmium-induced neural tube defects via reducing low density lipoprotein cholesterol levels in mouse placentas
Authors: Zhang Yu-Feng , Zhang Shuang , Ling Qing , Chang Wei , Tan Lu-Lu , Zhang Jin , Xiong Yong-Wei , Zhu Hua-Long , Bian Po , Wang Hua 
Published: May 2024

AbstractNeural tube defects (NTDs) represent a prevalent and severe category of congenital anomalies in humans. Cadmium (Cd) is an environmental teratogen known to cause fetal NTDs. However, its underlying mechanisms remain elusive. This study aims to investigate the therapeutic potential of lipophagy in the treatment of NTDs, providing valuable insights for future strategies targeting lipophagy activation as a means to mitigate NTDs.We successfully modeled NTDs by Cd exposure during pregnancy. RNA sequencing was employed to investigate the transcriptomic alterations and functional enrichment of differentially expressed genes in NTD placental tissues. Subsequently, pharmacological/genetic (Atg5-/- placentas) experiments confirmed that inducing placental lipophagy can alleviate Cd induced-NTDs. We found that Cd exposure caused NTDs. Further analyzed transcriptomic data from the placentas with NTDs which revealed significant downregulation of low-density lipoprotein receptor associated protein 1(Lrp1) gene expression responsible for positive regulation of low-density lipoprotein cholesterol (LDL-C) transport. Correspondingly, there was an increase in maternal serum/placenta/amniotic fluid LDL-C content. Subsequently, we have discovered that Cd exposure activated placental lipophagy. Pharmacological/genetic (Atg5-/- placentas) experiments confirmed that inducing placental lipophagy can alleviate Cd induced-NTDs. Furthermore, our findings demonstrate that activation of placental lipophagy effectively counteracts the Cd-induced elevation in LDL-C levels. Lipophagy serves to mitigate Cd-induced NTDs by reducing LDL-C levels within mouse placentas.
Intersectional fair ranking via subgroup divergence
Authors: Pastor Eliana , Bonchi Francesco 
Published: May 2024

AbstractSocietal biases encoded in real-world data can contaminate algorithmic decisions, perpetuating preexisting inequalities in domains such as employment and education. In the fair ranking literature, following the doctrine of affirmative action, fairness is enforced by means of a group-fairness constraint requiring “enough” individuals from protected groups in the top-k positions, for a ranking to be considered valid. However, which are the groups that need to be protected? And how much representation is “enough”? As the biases affecting the process may not always be directly observable nor measurable, these questions might be hard to answer in a principled way, especially when many different potentially discriminated subgroups exist. This paper addresses this issue by automatically identifying the disadvantaged groups in the data and mitigating their disparate representation in the final ranking. Our proposal leverages the notion of divergence to automatically identify which subgroups, defined as combination of sensitive attributes, show a statistically significant deviation, in terms of ranking utility, compared to the overall population. Subgroups with negative divergence experience a disadvantage. We formulate the problem of re-ranking instances to maximize the minimum subgroup divergence, while maintaining the new ranking as close as possible to the original one. We develop a method which is based on identifying the divergent subgroups and applying a re-ranking procedure which is monotonic w.r.t. the goal of maximizing the minimum divergence. Our experimental results show that our method effectively eliminates the existence of disadvantaged subgroups while producing rankings which are very close to the original ones.