bluuebunny/crossref_metadata_2025_split huggingface dataset:
Physicochemical and heavy metal pollution level in Hindon River ecosystem: An implication to public health risk assessment
Authors: Singh Bhanu Pratap , Samanta Palas , Choudhury Moharana , Gupta Piyush , Chadha Utkarsh , Eticha Tolera Kuma 
Published: June 2024

AbstractThe study was conducted to determine heavy metal contamination and physicochemical parameters in Hindon River's water. The parameters evaluated included cadmium (Cd), copper (Cu), chromium (Cr), iron (Fe), manganese (Mn), zinc (Zn), and lead (Pb), as well as pH, electrical conductivity (EC), turbidity (TUR), total dissolved solids (TDS), total hardness (TH), total alkalinity (TA), dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), chloride (Cl−), calcium (Ca), sulfate () and nitrate (). The findings showed the distribution of metals in river water. Some of the values of Cd, Cu, Cr, Fe, Mn, Zn, and Pb in surface water were above the standards set by the Bureau of Indian Standards (BIS). The mean concentrations of physicochemical parameters in surface water sometimes exceeded the BIS standards due to untreated effluent discharge. All the Water Quality Index (WQI) values were above 100; therefore, the water was unsuitable for human consumption. The heavy metal pollution index (HPI) showed that Station 1 (S1) is the most polluted, followed by the S3 and S5. Multivariate statistical analysis showed that most heavy metals (HMs) in river water originated from artificial or anthropogenic sources, that is, human sources. The calculated hazard quotient (HQ) and hazard index (HI) showed that the oral ingestion route could be dangerous to humans (both adults and children) since the HQ and HI values were higher than the acceptable limits (HQ > 1). Dermal exposure assessment showed that the S1 was more dangerous to children's and adults' health than the S3 and S5. This trend showed that the Hindon River was polluted due to many untreated industrial effluents being discharged. The research highlights the pollution level in the Hindon River, and there is a need for proper monitoring and control to maintain the sustainability of the river ecosystem.
Role of heavy metals in species composition of moss: An insight study in contaminated mining sites of Eastern India
Authors: Nanda Swayam Prakash , Panda Bibhu Prasad , Panigrahi Kishore C. S. , Pradhan Abanti 
Published: June 2024

AbstractMining activities are significant contributors to heavy metal pollution in the environment, which poses risks to both the natural ecosystem and human health. Thus, the purpose of this study is to determine the extent to which mining‐affected regions of Eastern India have undergone heavy metal‐induced changes to ecosystem composition, specifically in soil heavy metal contamination and moss diversity. The relationship between the abundance of moss species and the heavy metal content of the soil in the study regions has been studied. A total of 48 soil samples were taken throughout the study areas, and 41 moss species spanning 14 families were identified. The identification process of mosses in sampling sites involves meticulously scrutinizing their morphological characteristics. Pottiaceae and Fissidentaceae were the most accountable families at the species level. The Shannon diversity index revealed variations in moss diversity among the regions. The concentrations of heavy metals were determined using AAS (Systronics, model No. 816), chromium (Cr), iron (Fe), and manganese (Mn) were the most noticeable metal in SP1 (Chromite mining areas in Jajpur), SP2(Iron mining area in Keojhar's Joda‐Barbil), and SP3(manganese mining areas in Sundargarh's Koira‐Joda), respectively. The metal concentrations were highest in the storage area and lowest at 1–3 km. Correlation analysis showed positive relationships among the metals and negative relationships between metals and mosses. Moss family, like Bruchiaceae, exhibited significant negative correlations with specific metals like Cr. These research findings help to understand the effects of mining on soil contamination, and moss diversity.
Modeling the effect of wind speed and direction shear on utility‐scale wind turbine power production
Authors: Mata Storm A. , Pena Martínez Juan José , Bas Quesada Jesús , Palou Larrañaga Felipe , Yadav Neeraj , Chawla Jasvipul S. , Sivaram Varun , Howland Michael F. 
Published: June 2024

AbstractWind speed and direction variations across the rotor affect power production. As utility‐scale turbines extend higher into the atmospheric boundary layer (ABL) with larger rotor diameters and hub heights, they increasingly encounter more complex wind speed and direction variations. We assess three models for power production that account for wind speed and direction shear. Two are based on actuator disc representations, and the third is a blade element representation. We also evaluate the predictions from a standard power curve model that has no knowledge of wind shear. The predictions from each model, driven by wind profile measurements from a profiling LiDAR, are compared to concurrent power measurements from an adjacent utility‐scale wind turbine. In the field measurements of the utility‐scale turbine, discrete combinations of speed and direction shear induce changes in power production of −19% to +34% relative to the turbine power curve for a given hub height wind speed. Positive speed shear generally corresponds to over‐performance and increasing magnitudes of direction shear to greater under‐performance, relative to the power curve. Overall, the blade element model produces both higher correlation and lower error relative to the other models, but its quantitative accuracy depends on induction and controller sub‐models. To further assess the influence of complex, non‐monotonic wind profiles, we also drive the models with best‐fit power law wind speed profiles and linear wind direction profiles. These idealized inputs produce qualitative and quantitative differences in power predictions from each model, demonstrating that time‐varying, non‐monotonic wind shear affects wind power production.
Real Estate Appraisal
Authors: Del Giudice Vincenzo 
Published: June 2024

AbstractThis chapter summarizes the research activities and main outcomes of the unit engaged in the fields of Real Estate Appraisal, in the decade 2013–2023, concerning the development of methodologies for the evaluation of programs/plans/projects, as well as the assessment of economic value of assets and rights, or the rates of return in public and private decision-making processes.
Fluid Machinery, Energy Systems and Power Generation
Authors: Manna Marcello , Senatore Adolfo 
Published: June 2024

AbstractThe chapter summarizes the research activities and main outcomes of the fluid machinery, energy systems and power generation groups, occurred during the 2013–2023 decade. The focus is on the theoretical, experimental, and numerical analysis of power generation systems either from hydrocarbons or from renewables, and more in general, on fluid machinery devices and components.
Statistics for Experimental and Technological Research
Authors: Giorgio Massimiliano 
Published: June 2024

AbstractThis chapter provides a synthetic overview of research activities and main outcomes of members of the scientific-disciplinary sector “SECS-S/02—Statistica per la Ricerca Sperimentale e Tecnologica” at the University of Naples Federico II, in the decade 2013–2023. Research activities of the group focus on modern statistical problems arising in the field of experimental sciences (statistics and probability calculus, design, and analysis of experiments), notably in engineering (reliability, statistical quality control). The main fields of application concern technology, safety, environment, territory, production processes, products, and natural resources.
LLM Controls Execution Flow Hijacking
Authors: Vogelsang Terry 
Published: June 2024

AbstractLLMs can be vulnerable to prompt injection attacks. Similar to how code injections can alter the behavior of a given program, malicious prompt injection can influence the execution flow of a specific business logic. This is due to their reliance on user-provided text for controlling execution flow. In the context of interactive systems, this poses significant business and cybersecurity risks. Mitigations such as prohibiting the use of LLMs in critical systems, developing prompt and resulting API calls verification tools, implementing security by designing good practices, and enhancing incident logging and alerting mechanisms can be considered to reduce the novel attack surface presented by LLMs.
Enhancing Security Awareness and Education for LLMs
Authors: Panichella Sebastiano 
Published: June 2024

AbstractLarge Language Models (LLMs) have gained widespread use in multiple applications, making end-user education and training a vital security component. Education involves creating awareness of the security concerns related to LLMs, such as data privacy concerns, bias, and cyberattacks, to encourage ethical and responsible use. Training can teach users to detect and mitigate security threats, configure security settings, and perform regular system updates to prevent vulnerabilities.
Towards Privacy Preserving LLMs Training
Authors: Buesser Beat 
Published: June 2024

AbstractPrivacy-preserving training of machine learning models aims to avoid or minimize (mitigate) the exact or similar reproduction (leakage) of information contained in the training data. This chapter introduces pre-processing methods (filtering and de-duplication) that prepare the training data to minimize information leakage, followed by a discussion of training and deployment methods (differentially private fine-tuning, noisy knowledge transfer) that provide empirical or theoretical guarantees for the achieved privacy protection with a focus on Large Language Models (LLMs).
Adversarial Evasion on LLMs
Authors: Guerraoui Rachid , Pinot Rafael 
Published: June 2024

AbstractWhile Machine Learning (ML) applications have shown impressive achievements in tasks such as computer vision, NLP, and control problems, such achievements were possible, first and foremost, in the best-case-scenario setting. Unfortunately, settings where ML applications fail unexpectedly, abound, and malicious ML application users or data contributors can trigger such failures. This problem became known as adversarial example robustness. While this field is in rapid development, some fundamental results have been uncovered, allowing some insight into how to make ML methods resilient to input and data poisoning. Such ML applications are termed adversarially robust. While the current generation of LLMs is not adversarially robust, results obtained in other branches of ML can provide insight into how to make them adversarially robust. Such insight would complement and augment ongoing empirical efforts in the same direction (red-teaming).
LLMs Red Teaming
Authors: Ruiu Dragos 
Published: June 2024

AbstractPrompt red-teaming is a form of evaluation that involves testing machine learning models for vulnerabilities that could result in undesirable behaviors. It is similar to adversarial attacks, but red-teaming prompts appear like regular natural language prompts, and they reveal model limitations that can cause harmful user experiences or aid violence. Red-teaming can be resource-intensive due to the large search space required to search the prompt space of possible model failures. Augmenting the model with a classifier trained to predict potentially undesirable texts is a possible workaround. Red-teaming LLMs is a developing research area, and there is a need for best practices, including persuading people to harm themselves or others and other problematic behaviors, such as memorization, spam, weapons assembly instructions, and the generation of code with pre-defined vulnerabilities. The challenge with evaluating LLMs for malicious behaviors is that they are not explicitly trained to exhibit such behaviors. Therefore, it is critical to continually develop red-teaming methods that can adapt as models become more powerful. Multi-organization collaboration on datasets and best practices can enable smaller entities releasing models to still red-team their models before release, leading to a safer user experience across the board.
Fundamental Limitations of Generative LLMs
Authors: Kucharavy Andrei 
Published: June 2024

AbstractGiven the impressive performances of LLM-derived tools across a range of tasks considered all but impossible for computers until recently, the capabilities of LLMs seem limitless. However, there are some fundamental limitations to what they can or cannot do inherent to the current architecture of LLMs. I will attempt to review the most notable of them to give the reader an understanding of what architectural modifications will need to take place before a given problem is solved. Specifically, I discuss counterfactual generation, private information leakage, reasoning, limited attention span, dependence on the training dataset, bias, and non-normative language.
Vulnerabilities Introduced by LLMs Through Code Suggestions
Authors: Panichella Sebastiano 
Published: June 2024

AbstractCode suggestions from generative language models like ChatGPT contain vulnerabilities as they often rely on older code and programming practices, over-represented in the older code libraries the LLMs rely on for their coding abilities. Advanced attackers can leverage this by injecting code with known but hard-to-detect vulnerabilities in the training datasets. Mitigation can include user education and engineered safeguards such as LLMs trained for vulnerability detection or rule-based checking of codebases. Analysis of LLMs’ code generation capabilities, including formal verification and source training dataset (code-comment pairs) analysis, is necessary for effective vulnerability detection and mitigation.
Freezing and BPS jumping
Authors: Kim Sung-Soo , Li Xiaobin , Nawata Satoshi , Yagi Futoshi 
Published: June 2024

Abstract
We report a novel BPS jumping phenomenon of 5d $$ \mathcal{N} $$
N
= 1 supersymmetric gauge theories whose brane configuration is equipped with an O7-plane. The study of the relation between O7+-plane and O7−-plane reveals that such BPS jumps take place when the Higgsing is triggered near the O7-plane upon a particular parameter tuning of the theories. We propose two types of gauge theories whose BPS spectra jump. One is the SU(2N + 8) gauge theory with a symmetric hypermultiplet converted to the SU(2N) gauge theory with an antisymmetric hypermultiplet. The other is pure SO(2N + 8) gauge theory jumping to pure Sp(N) gauge theory. We explicitly confirm our proposal through the (un)refined instanton partition functions. Furthermore, we discuss feasible generalizations involving an Op-plane for supersymmetric gauge theories of eight supercharges in four and three dimensions (p = 6, 5 respectively).
$$ \mathcal{N} $$ = 2 supersymmetry in the twistor description of higher-spin holography
Authors: Lang Julian , Neiman Yasha 
Published: June 2024

Abstract
We study the holographic duality between higher-spin (HS) gravity in 4d and free vector models in 3d, with special attention to the role of $$ \mathcal{N} $$
N
= 2 supersymmetry (SUSY). For the type-A bosonic bulk theory, dual to spin-0 fields on the boundary, there exists a twistor-space description; this maps both single-trace boundary operators and linearized bulk fields to spacetime-independent twistor functions, whose HS-algebra products compute all boundary correlators. Here, we extend this description to the type-B bosonic theory (dual to spin-1/2 fields on the boundary), and to the supersymmetric theory containing both. A key role is played by boundary bilocals, which in type-A are dual to the Didenko-Vasiliev 1/2-BPS “black hole”. We extend this to an infinite family of linearized 1/2-BPS “black hole” solutions. Remarkably, the full supersymmetric theory (along with the SUSY generators) fits in the same space of twistor functions as the type-A theory. Instead of two sets of bosonic bulk fields, the formalism sees one set of linearized fields, but with both types of boundary data allowed.
Page curve of AdS-Vaidya model for evaporating black holes
Authors: Chou Chia-Jui , Lao Hans B. , Yang Yi 
Published: June 2024

Abstract
We study an evaporating black hole in the boundary conformal field theory (BCFT) model under the fully time-dependent AdS-Vaidya spacetime geometry. We introduce the time-dependent finite bath termed the effective Hawking radiation region. This is described by a nontrivial BCFT solution that acts as a time-dependent brane which we call the moving end-of-the-radiation (METR) brane that leads to a new type of Hubeny-Rangamani-Takayanagi surface. We further examine the island formulation in this particular time-dependent spacetime. The Page curve is calculated by using Holographic Entanglement Entropy (HEE) in the context of double holography.
Spinorial description for Lorentzian $$ \mathfrak{hs} $$-IKKT
Authors: Steinacker Harold C. , Tran Tung 
Published: June 2024

Abstract
We introduce a novel spinorial description for the higher-spin gauge theory induced by the IKKT matrix model on an FLRW spacetime with Lorentzian signature, called Lorentzian $$ \mathfrak{hs} $$
hs
-IKKT theory. The new description is based on Weyl spinors transforming under the space-like isometry subgroup SL(2, ℂ) of the structure group SO(2, 4) ≃ SU(2, 2). It allows us to exploit the full power of the spinor formalism in Lorentzian signature, in contrast to a previous formalism based on the compact subgroup SU(2)L × SU(2)R of SU(2, 2). Some cubic vertices of the Yang-Mills sector and the corresponding scattering amplitudes are computed. We observe that the n-point (for n ≥ 4) tree-level amplitudes are typically non-trivial on-shell, but exponentially suppressed in the late-time regime. While Lorentz invariance of the higher-spin amplitudes is not manifest, it is expected to be restored by higher-spin gauge invariance.
Giant correlators at quantum level
Authors: Jiang Yunfeng , Wu Yu , Zhang Yang 
Published: June 2024

Abstract
We compute four-point functions with two maximal giant gravitons and two chiral primary operators at three-loop order in planar $$ \mathcal{N} $$
N
= 4 Super-Yang-Mills theory. The Lagrangian insertion method, together with symmetries of the theory fix the integrand up to a few constants. Under the additional assumption of planarity, all these constants can be determined by lower loop data. The obtained result can be regarded as the planar diagram contribution to the full four-point function and is written in terms of the known three-loop conformal integrals. From the four-point function, we extract the OPE coefficients of two giant gravitons and one non-BPS twist-2 operator with arbitrary spin at three-loops, given in terms of harmonic sums. We observe an intriguingly simple relation between the giant graviton OPE coefficients and the OPE coefficients of three single-trace operators.
Analysis of welding conditions at synchronous operation of resistance welding machines
Authors: Mikno Zygmunt , Stepien Mariusz 
Published: June 2024

AbstractThe paper is devoted to analysis of power losses in a resistance welding machine including supplying system and examination of welding conditions of the welding machine current in a case of synchronous (simultaneous) operation of multiple welding machines, i.e., during the conduction of welding current. Analysis of the most important contributors of power losses generated on the current path between a power source and the welded joint is carried out. The analysis is carried out for a DC (direct current) welding machine with power electronics inverter. AC (alternating current) welding machines are also taken into account. The analysis is divided in two parts. The first one is the analysis of single welding machine operation, while in the second part, coexistence (mutual operation) of two synchronous welding machines is considered. The analysis is based on results of numerical and experimental investigations. The first one is focused on calculation of power losses in the energy path (including a Sankey type power loss distribution diagrams), and the second one is based on experimental tests carried out to determine the diameter of the weld nugget and the strength of the joints, for cases of reducing the welding current. An example of simultaneous operation of welding machines was presented and discussed. The percentage voltage drops and power losses in the entire power supply path of the resistance welder are shown. The analysis carried out is extremely important from this point quality of welded joints.
Work from home arrangements and organizational performance in Italian SMEs: evidence from the COVID-19 pandemic
Authors: Abrardi Laura , Grinza Elena , Manello Alessandro , Porta Flavio 
Published: June 2024

AbstractWe use survey data on Italian small- and medium-sized enterprises collected during the COVID-19 pandemic to explore the relationship between the adoption of work from home (WFH) practices and organizational performance. In so doing, we investigate several dimensions of organizational performance, including measures of labor productivity and workers’ concentration and motivation, the level of absenteeism, the organization of work through management by objectives (MBO), and the presence of coordination and communication costs. We obtain several results. First, we find a significantly enhanced capability of firms that adopted WFH during the pandemic to sustain the overall organizational performance, particularly when such a work practice is used intensively. Less deteriorated labor productivity and workers’ concentration and motivation, decreased absenteeism, and a substantial rise in the adoption of MBO practices seem to be important aspects behind the detected benefits related to WFH. Third, when WFH is used at medium levels of intensity, it is associated with augmented coordination and communication costs, which nonetheless do not appear to overcome the benefits associated with WFH.
Molecular mechanisms underlying methotrexate-induced intestinal injury and protective strategies
Authors: Ali Gaber F. , Hassanein Emad H. M. , Mohamed Wafaa R. 
Published: June 2024

AbstractMethotrexate (MTX) is a folic acid reductase inhibitor that manages various malignancies as well as immune-mediated inflammatory chronic diseases. Despite being frequently prescribed, MTX’s severe multiple toxicities can occasionally limit its therapeutic potential. Intestinal toxicity is a severe adverse effect associated with the administration of MTX, and patients are significantly burdened by MTX-provoked intestinal mucositis. However, the mechanism of such intestinal toxicity is not entirely understood, mechanistic studies demonstrated oxidative stress and inflammatory reactions as key factors that lead to the development of MTX-induced intestinal injury. Besides, MTX causes intestinal cells to express pro-inflammatory cytokines like interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α), which activate nuclear factor-kappa B (NF-κB). This is followed by the activation of the Janus kinase/signal transducer and activator of the transcription3 (JAK/STAT3) signaling pathway. Moreover, because of its dual anti-inflammatory and antioxidative properties, nuclear factor erythroid-2-related factor 2/heme oxygenase-1 (Nrf2/HO-1) has been considered a critical signaling pathway that counteracts oxidative stress in MTX-induced intestinal injury. Several agents have potential protective effects in counteracting MTX-provoked intestinal injury such as omega-3 polyunsaturated fatty acids, taurine, umbelliferone, vinpocetine, perindopril, rutin, hesperidin, lycopene, quercetin, apocynin, lactobacillus, berberine, zinc, and nifuroxazide. This review aims to summarize the potential redox molecular mechanisms of MTX-induced intestinal injury and how they can be alleviated. In conclusion, studying these molecular pathways might open the way for early alleviation of the intestinal damage and the development of various agent plans to attenuate MTX-mediated intestinal injury.
Graphical Abstract