ethicalabs/Research-Intent-Collab huggingface dataset:
A Comprehensive Review of State-of-The-Art Methods for Java Code Generation from Natural Language Text

Java Code Generation consists in generating automatically Java code from a Natural Language Text. This NLP task helps in increasing programmers' productivity by providing them with immediate solutions to the simplest and most repetitive tasks. Code generation is a challenging task because of the hard syntactic rules and the necessity of a deep understanding of the semantic aspect of the programming language. Many works tried to tackle this task using either RNN-based, or Transformer-based models. The latter achieved remarkable advancement in the domain and they can be divided into three groups: (1) encoder-only models, (2) decoder-only models, and (3) encoder-decoder models. In this paper, we provide a comprehensive review of the evolution and progress of deep learning models in Java code generation task. We focus on the most important methods and present their merits and limitations, as well as the objective functions used by the community. In addition, we provide a detailed description of datasets and evaluation metrics used in the literature. Finally, we discuss results of different models on CONCODE dataset, then propose some future directions.
Beyond the hype: Why AI still cannot replace human translators and interpreters in high-stakes contexts

Recent advances in artificial intelligence (AI) have significantly improved machine translation and real-time interpreting, fostering optimism about faster and more accessible cross-linguistic communication. However, this feature article argues that such developments pose critical limitations when applied to high-stakes public service domains such as legal, medical, immigration, and asylum contexts. In those settings, communicative failure can have profound consequences. Drawing on research from interpreting studies, sociolinguistics, and AI ethics, this study explains how language in these environments is not merely informational: it is also performative, culturally embedded, and deeply influenced by power relations, trust, and accountability. While AI systems may achieve high accuracy in non-critical interactions, they struggle with ambiguity, cultural nuance, minority languages, emotional distress, and unpredictable discourse conditions. Moreover, a range of issues including bias, confidentiality, ethical responsibility, and legal liability raise serious concerns regarding the substitution of human interpreters by AI.
Advances in Regenerative Medicine for Tendon Injuries: Stem Cells vs. PRP Therapies

Since tendons heal slowly and tend to repeat the injury, their treatment is a significant clinical issue as it commonly causes delayed healing and unfavorable results. Recent research has identified regenerative medicine as a promising therapeutic approach, with platelet-rich plasma (PRP) and stem cells being increasingly investigated. The review aims to evaluate the effectiveness of current strategies for tendon repair using regenerative medicine, assess their success and safety in clinical settings, and discuss potential future applications. PRP provides autologous growth factors that can aid in rapid tissue repair, while mesenchymal stem cells derived from various sources, such as bone marrow and adipose tissue, possess multilineage potential, modulate the immune system, and can facilitate tissue repair with the assistance of chemical signals. Preclinical and clinical studies have shown that optimal results cannot be expected from all therapies because they vary in numerous aspects. Though findings hold great promise, issues of inconsistency in cell preparation, heterogeneity in outcome measures, and difficulties with regulation persist. According to the authors, more rigorous randomized controlled trials are needed to determine the optimal practices for each tendon treatment, enabling physicians to offer evidence-based, individualized care.
Comparison of uridine and N1-methylpseudouridine mRNA platforms in development of an Andes virus vaccine

Abstract                   The rodent-borne Andes virus (ANDV) causes a severe disease in humans. We developed an ANDV mRNA vaccine based on the M segment of the viral genome, either with regular uridine (U-mRNA) or N1-methylpseudouridine (m1Ψ-mRNA). Female mice immunized by m1Ψ-mRNA developed slightly greater germinal center (GC) responses than U-mRNA-immunized mice. Single cell RNA and BCR sequencing of the GC B cells revealed similar levels of activation, except an additional cluster of cells exhibiting interferon response in animals vaccinated with U-mRNA but not m1Ψ-mRNA. Similar immunoglobulin class-switching and somatic hypermutations were observed in response to the vaccines. Female Syrian hamsters were immunized via a prime–boost regimen with two doses of each vaccine. The titers of glycoprotein-binding antibodies were greater for U-mRNA construct than for m1Ψ-mRNA construct; however, the titers of ANDV-neutralizing antibodies were similar. Vaccinated animals were challenged with a lethal dose of ANDV, along with a naïve control group. All control animals and two animals vaccinated with a lower dose of m1Ψ-mRNA succumbed to infection whereas other vaccinated animals survived without evidence of virus replication. The data demonstrate the development of a protective vaccine against ANDV and the lack of a substantial effect of m1Ψ modification on immunogenicity and protection in rodents.
Oral Presentations Abstracts: READING THE MINDS OF YOUNG PEOPLE FOR THEIR OWN GOOD – THE ETHICS OF DIGITAL PHENOTYPING FOR MENTAL HEALTH IN SCHOOLS

View of Volume 66, Special Issue, September 2021 Across the globe the phenomenon of digital phenotyping – the collection and analysis of digital data for mental health – is growing increasingly popular within the education sector. Schools enter collaborations with health care providers, often with the aim to support young people and to reduce the risk for severe mental health challenges, self-harm, and suicide. In developing technologies for these purposes, algorithms and artificial intelligence (broadly construed) could be utilized to provide as rich and accurate data as possible. The data can then be used to flag up at-risk individuals within the system. Despite the increasing interest in digital mental health tools in many educational systems, there has been remarkably little written about the ethical issues that accompany the emergence of digital phenotyping. Arguably more alarming is that almost no research has been conducted on the acceptability and ethics of these technologies in stakeholder populations: we have not asked young people about their values in this context. In this paper, we present results from a large quantitative study from the UK, showing what young people value and choose in scenarios involving digital phenotyping in schools. We highlight clear discrepancies between what young people value – and how they conceptualize those values – and how the literature describes the ethical implications of related technologies in schools. We argue that policymakers and ethicists urgently need to learn to recognize and respect the moral boundaries of young people.
Rechtsstaatlichkeit in Europa: Unabhängigkeit der Justiz und wirksame Rechtsmittel | Rule of Law in Europe: Judicial independence and effective remedies | État de droit en Europe: indépendance de la justice et recours effectif

This special issue is the result of a conference organized in cooperation with the University of Luxembourg by SIPE on the very notion of the Rechtsstaatlichkeit in Europa / the rule of law in Europe / l’État de droit en Europe focusing therein on judicial independence and effective remedies. The contributions reflect various perspectives on the notions of the rule of law in Europe, especially its protection by the hands of courts and tribunals as independent bodies designed to review executive and, in most states, also legis-lative action for their compliance with constitutional principles and values. The contributions all display a broad understanding of notions contained in the rule of law obliging to ensure a separation of powers, an effective judicial protection, principles of a system of democratic government as well as the protection of individual human rights and fundamental freedoms. The rule of law in this understanding goes well beyond an adherence to the principle of legality and reaches also into substantive norms and institu-tional and structural principles of the organisation of the exercise of public powers.The existence and defense of this broad understanding of the rule of law is also deeply embedded in the very existence of the Council of Europe and its Convention on Human Rights.  With contributions by Prof. Dr. Maria Lúcia Amaral | Prof. Dr. Constance Grewe | Prof. Dr. Herwig C.H. Hofmann, M.Jur. (Oxon) | Prof. em. Dr. Julia Iliopoulos-Strangas | Prof. Dr. Irena Lipowicz | Prof. Dr. Eleftheria Neframi | Prof. DDr. Angelika Nußberger | GA Athanasios Rantos | Präs. Dean Spielmann | Prof. Dr. Elena Simina Tanasescu | Prof. Dr. Jacques Ziller
A Pilot Study of Surgical Training Using a Virtual Robotic Surgery Simulator

Our objectives were to compare the utility of learning a suturing task on the virtual reality da Vinci Skills Simulator versus the da Vinci Surgical System dry laboratory platform and to assess user satisfaction among novice robotic surgeons.Medical trainees were enrolled prospectively; one group trained on the virtual reality simulator, and the other group trained on the da Vinci dry laboratory platform. Trainees received pretesting and post-testing on the dry laboratory platform. Participants then completed an anonymous online user experience and satisfaction survey.We enrolled 20 participants. Mean pretest completion times did not significantly differ between the 2 groups. Training with either platform was associated with a similar decrease in mean time to completion (simulator platform group, 64.9 seconds [P = .04]; dry laboratory platform group, 63.9 seconds [P < .01]). Most participants (58%) preferred the virtual reality platform. The majority found the training "definitely useful" in improving robotic surgical skills (mean, 4.6) and would attend future training sessions (mean, 4.5).Training on the virtual reality robotic simulator or the dry laboratory robotic surgery platform resulted in significant improvements in time to completion and economy of motion for novice robotic surgeons. Although there was a perception that both simulators improved performance, there was a preference for the virtual reality simulator. Benefits unique to the simulator platform include autonomy of use, computerized performance feedback, and ease of setup. These features may facilitate more efficient and sophisticated simulation training above that of the conventional dry laboratory platform, without loss of efficacy.
Minimalist Vision with Freeform Pixels

A minimalist vision system uses the smallest number of pixels needed to solve a vision task. While traditional cameras use a large grid of square pixels, a minimalist camera uses freeform pixels that can take on arbitrary shapes to increase their information content. We show that the hardware of a minimalist camera can be modeled as the first layer of a neural network, where the subsequent layers are used for inference. Training the network for any given task yields the shapes of the camera's freeform pixels, each of which is implemented using a photodetector and an optical mask. We have designed minimalist cameras for monitoring indoor spaces (with 8 pixels), measuring room lighting (with 8 pixels), and estimating traffic flow (with 8 pixels). The performance demonstrated by these systems is on par with a traditional camera with orders of magnitude more pixels. Minimalist vision has two major advantages. First, it naturally tends to preserve the privacy of individuals in the scene since the captured information is inadequate for extracting visual details. Second, since the number of measurements made by a minimalist camera is very small, we show that it can be fully self-powered, i.e., function without an external power supply or a battery.
Asymptotic analysis and diffusion limit of the Persistent Turning Walker Model

The Persistent Turning Walker Model (PTWM) was introduced by Gautrais et al in Mathematical Biology for the modelling of fish motion. It involves a nonlinear pathwise functional of a non-elliptic hypo-elliptic diffusion. This diffusion solves a kinetic Fokker-Planck equation based on an Ornstein-Uhlenbeck Gaussian process. The long time diffusive behavior of this model was recently studied by Degond & Motsch using partial differential equations techniques. This model is however intrinsically probabilistic. In the present paper, we show how the long time diffusive behavior of this model can be essentially recovered and extended by using appropriate tools from stochastic analysis. The approach can be adapted to many other kinetic probabilistic models.
Hybridising Collaborative Filtering and Trust-aware Recommender Systems.

Recommender systems (RS) aim to predict items that users would appreciate, over a list of items. In evaluation of recommender systems, two issues can be deﬁned: accuracy of prediction which implies the satisfaction of the user, coverage which implies the percentage of satisﬁed users. Collaborative ﬁltering (CF) is the master approach in this domain, but still has some weaknesses especially about coverage. Trust-aware approach is today another promising approach in RS within social environments, whose prediction exceeds the quality of (CF). In this paper we propose several strategies to hybridize those both approaches in order to improve prediction quality, in the term of accuracy and coverage.
Sensing-Assisted Sparse Channel Recovery for Massive Antenna Systems

This correspondence presents a novel sensing-assisted sparse channel recovery approach for massive antenna wireless communication systems. We focus on a fundamental configuration with one massive-antenna base station (BS) and one single-antenna communication user (CU). The wireless channel exhibits sparsity and consists of multiple paths associated with scatterers detectable via radar sensing. Under this setup, the BS first sends downlink pilots to the CU and concurrently receives the echo pilot signals for sensing the surrounding scatterers. Subsequently, the CU sends feedback information on its received pilot signal to the BS. Accordingly, the BS determines the sparse basis based on the sensed scatterers and proceeds to recover the wireless channel, exploiting the feedback information based on advanced compressive sensing (CS) algorithms. Numerical results show that the proposed sensing-assisted approach significantly increases the overall achievable rate than the conventional design relying on a discrete Fourier transform (DFT)-based sparse basis without sensing, thanks to the reduced training overhead and enhanced recovery accuracy with limited feedback.
Health Care Access Among Mexican Americans With Different Health Insurance Coverage

This study describes the rates of health care access among Mexican Americans with different health insurance coverage. An interview questionnaire was used to collect information regarding sociodemographics, perceived health status, health insurance coverage, and sources of health care from a random sample of 501 Mexican Americans from San Antonio, Texas. Health care access was determined more by having health insurance coverage than by health care needs. Poor Mexican Americans with health insurance had higher health care access rates than did poor Mexican Americans without health insurance. Health care access may improve health care outcomes, but more comprehensive community-based campaigns to promote health and better use of health services in underprivileged populations should be developed.
Abstract A139: Preclinical characterization and prediction of human pharmacokinetics and efficacious dose for VIP236, a novel alpha V beta 3 binding small molecule-drug conjugate (SMDC)

Abstract                VIP236 is a small molecule drug conjugate (SMDC) consisting of an alpha v beta 3 (αvβ3) integrin binder linked to an optimized camptothecin (optCPT) payload via a protease sensitive peptide sequence. The overall drug design strategy for VIP236 is targeted delivery to the tumor microenvironment (TME) with extracellular release of the opCPT by neutrophil elastase (NE) present in the TME. VIP236 is anticipated to kill tumor cells while reducing effects to normal tissue. VIP236 was characterized in preclinical pharmacokinetic (PK) and efficacy studies to predict its human PK and efficacious dose.  Briefly, VIP236 was administered intravenously (IV) to mice, rats, and dogs to characterize both its in vivo PK (1-2 mg/kg) and its routes of excretion (bile-duct cannulated [BDC] rat at 10 mg/kg).  VIP236 was evaluated in vitro for its protein binding characteristics and as a substrate of human drug transporters.   In addition, VIP236 was dosed to MX-1 (breast cancer) xenografted mice at doses ranging from 26-40 mg/kg IV on a 3 days on/4 days off regimen to characterize its antitumor activity. VIP236 had low plasma clearance in mice, rats, and dogs (CL=2.7-4.4 mL/min/kg) and low volume of distribution (Vss = 0.11 to 0.25 L/kg).  Terminal half-life ranged from 0.93 hour in mice to 3.07 hours in dogs. In BDC rats, VIP236 was primarily excreted in bile with biliary clearance accounting for essentially all the total body CL. There was minimal to no metabolites in rat bile and urine.  In vitro VIP236 exhibited low permeability in MDCKII cell monolayers and was identified as a substrate of BSEP and MRP2. VIP236 was highly protein bound to plasma protein with fraction unbound being &amp;lt;5% in all species tested. VIP236 showed robust tumor regression in MX-1 xenografted mice at all doses tested.  Allometric methods were used to predict a low human VIP236 CL (0.87-2.68 mL/min/kg) and Vss (0.10 L/kg). Translational pharmacokinetic/pharmacodynamic modeling was used to predict human efficacious doses and exposures by benchmarking VIP236 against irinotecan antitumor activity in MX-1 xenograft mice after 5 cycles of dosing.  Based on this analysis, predicted human doses ranged from 1-5 mg/kg IV on a 2 days on/5 days off regimen.  VIP236 is currently being evaluated in a first-in-human study in patients with advanced or metastatic solid tumors (NCT05712889).                Citation Format: Harvey Wong, Beatrix Stelte-Ludwig, Hans-Georg Lerchen, Amy J Johnson, Melanie M Frigault, Raquel Izumi, Ahmed Hamdy. Preclinical characterization and prediction of human pharmacokinetics and efficacious dose for VIP236, a novel alpha V beta 3 binding small molecule-drug conjugate (SMDC) [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A139.
Additional file 4 of Acupuncture for combat post-traumatic stress disorder: trial development and methodological approach for a randomized controlled clinical trial

Additional file 4. Original Funding/Monitoring Documentation. DMC Charter.
A regional climate model downscaling projection of China future climate change

Climate changes over China from the present (1990–1999) to future (2046–2055) under the A1FI (fossil fuel intensive) and A1B (balanced) emission scenarios are projected using the Regional Climate Model version 3 (RegCM3) nests with the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM). For the present climate, RegCM3 downscaling corrects several major deficiencies in the driving CCSM, especially the wet and cold biases over the Sichuan Basin. As compared with CCSM, RegCM3 produces systematic higher spatial pattern correlation coefficients with observations for precipitation and surface air temperature except during winter. The projected future precipitation changes differ largely between CCSM and RegCM3, with strong regional and seasonal dependence. The RegCM3 downscaling produces larger regional precipitation trends (both decreases and increases) than the driving CCSM. Contrast to substantial trend differences projected by CCSM, RegCM3 produces similar precipitation spatial patterns under different scenarios except autumn. Surface air temperature is projected to consistently increase by both CCSM and RegCM3, with greater warming under A1FI than A1B. The result demonstrates that different scenarios can induce large uncertainties even with the same RCM-GCM nesting system. Largest temperature increases are projected in the Tibetan Plateau during winter and high-latitude areas in the northern China during summer under both scenarios. This indicates that high elevation and northern regions are more vulnerable to climate change. Notable discrepancies for precipitation and surface air temperature simulated by RegCM3 with the driving conditions of CCSM versus the model for interdisciplinary research on climate under the same A1B scenario further complicated the uncertainty issue. The geographic distributions for precipitation difference among various simulations are very similar between the present and future climate with very high spatial pattern correlation coefficients. The result suggests that the model present climate biases are systematically propagate into the future climate projections. The impacts of the model present biases on projected future trends are, however, highly nonlinear and regional specific, and thus cannot be simply removed by a linear method. A model with more realistic present climate simulations is anticipated to yield future climate projections with higher credibility.
Educational technology approach toward learning analytics

The aim of this study is to suggest more meaningful components for learning analytics in order to help learners improving their learning achievement continuously through an educational technology approach. Multiple linear regression analysis is conducted to determine which factors influence student's academic achievement. 84 undergraduate students in a women's university in South Korea participated in this study. The six-predictor model was able to account for 33.5% of the variance in final grade, F(6, 77) = 6.457, p 2 = .335. Total studying time in LMS, interaction with peers, regularity of learning interval in LMS, and number of downloads were determined to be significant factors for students' academic achievement in online learning environment. These four controllable variables not only predict learning outcomes significantly but also can be changed if learners put more effort to improve their academic performance. The results provide a rationale for the treatment for student time management effort.