ethicalabs/Research-Intent-Collab huggingface dataset:
HEARSAY EVIDENCE: MEANING, KINDS, AND EXCEPTIONS IN COMMON LAW AND PAKISTANI LAW OF EVIDENCE

Hearsay evidence is an out of court statement which is presented in court to prove that the assertions made in it are true. The hearsay rule means that hearsay evidence will not be used in judicial proceedings except in exceptional cases. The definition, kinds and exceptions to hearsay rule have been explicitly discussed in various statutes and judicial decisions of common law countries. On the other hand, the definition and exceptions to hearsay evidence have not been explicitly discussed in Qanoon e Shahdat, 1984 (Pakistani law of evidence hereinafter QSO) which causes great difficulty in understanding the nature and scope of this concept. The present study, by deploying doctrinal research methods, intends to address these issues by analyzing the hearsay evidence and its exception in QSO. It is hoped that the present study will clarify the meaning and exceptions to hearsay rule in QSO. Keywords: Hearsay Evidence, Exceptions to Hearsay Evidence in Common Law, Direct Evidence, Kinds of Hearsay, Hearsay in Pakistan
Can the Kidnapping by Illegal Armed Groups in Colombia be Considered a Crime Against Humanity under International Customary Law and Article 7 of the Rome Statute of the International Criminal Court?

This thesis focuses on kidnapping in Colombia conducted by Illegal Armed Groups and investigates whether or not these kidnappings constitutes a crime against humanity according to article 7 of the Rome Statute for the International Criminal Court. My approach involve arguments for and against such categorization and investigate related sub questions, such as: How well this crime fits categories listed in article 7 of the Rome Statute? Could the effect of this crime on society be so severe that it should be considered an international crime and consequently a crime against humanity? Can kidnapping be in violation of international customary law? This thesis shows that kidnapping perpetrated by Illegal Armed Groups fits the required elements of crimes against humanity of article 7 of the Rome Statute in the categories 7 (1) (e) and 7 (1) (k) and it also constitute a violation of international customary law. The thesis concluded that kidnapping perpetrated by Illegal Armed Groups in Colombia should be considered a crime against humanity.
A photonic integrated chip for distinguishing the optical wave packets based on a neural-network

In this work, we use an optical-neural network to recognize a series of optical triangular and square wave packets. This chip is designed based on the reservoir computing, consisting of the directional couplers, phase shifters, Mach-Zehnder modulators, spiral waveguide and grating couplers. The non-linear activation function is obtained by the directional couplers. The optimization of the optical reservoir computing system is performed by tuning the voltage on the phase shifters to obtain the largest extinction ratio of the output signals for different input wave packets. The photonic integrated chip is fabricated on silicon-on-insulator and is characterized at an operation frequency of 3 GHz. The results demonstrate that the photonic integrated chip can efficiently distinguish between optical triangular and square wave packets.
Central Bank Digital Currencies: What They Are, What They Might Become, and What They Mean for Credit Unions, Report #559

Today, most CBDCs exist only as proposals, prototypes, or trials, and there is little consensus on questions around efficiency, surveillance, and financial inclusion. However, with countries around the world beginning to issue their own versions of CBDCs and the United States Federal Reserve publishing a long-anticipated report on CBDCs earlier this year, there is a growing recognition that CBDCs will have an important role to play in the digital landscape of the future. As central banks begin their journey in considering and implementing CBDCs, understanding the variety of forms CBDCs can take, as well as their associated risks and opportunities, becomes crucial for credit unions.
A hybrid Machine Learning methodology for imbalanced datasets

In the Machine Learning systems several imbalanced data sets exhibit skewed class distributions in which most cases are allocated to a class and far fewer cases to a smaller one. A classifier induced from an imbalanced data set has usually a low error rate for the majority class and an unacceptable error rate for the minority class. In this paper a synoptic review of the various related methodologies is given, a new ensemble methodology is introduced and an experimental study with other ensembles is presented. The proposed method that combines the power of OverBagging and Rotation Forest algorithms improves the identification of a difficult small class, while keeping the classification ability of the other class in an acceptable accuracy level.
THE USE OF MATHEMATICAL MODELS FOR THE OPTIMIZATION OF TRANSPORTS FROM THE COMPANY’S LOGISTICS AND OF FORRESTER MODELING TECHNIQUES ON TRAFFIC PROBLEMS

The optimization of transport from the company’s external logistic entails, besides the use of mathematical models based on linear programming, a correlation with the system’s dynamic functioning models. The purpose is minimizing delays in road traffic, thus having the material resources present in time for the production process. The use of Forrester techniques for this optimizes the ratio between the demands of the market for different products made by the company and the means of supplying them.
State of Indigenous Peoples', Local Communities', and Afro-descendant Peoples' Carbon Rights in Tropical and Subtropical Lands and Forests

This brief summarizes findings from a study undertaken by the Rights and Resources Initiative and McGill University to systematically analyze the carbon rights held by Indigenous Peoples, local communities, and Afro-descendant Peoples in 33 countries in Africa (11), Asia (9), and Latin America (13) that cover over 35% of the world’s forest. We examine whether and how countries protect the rights necessary for communities to manage, control, and benefit from carbon on their lands and to access compensation and justice when they are affected by carbon trading initiatives. We collected data on 35 indicators from domestic laws and policies related to land, carbon, and resource rights across several sectors, including constitutional law; land tenure administration; and forest, climate, and environmental law. Across these 33 countries, our analysis refers to the legal rules that govern 96 community-based tenure regimes (CBTRs) identified by RRI in these countries.
[Analysis for spatial distribution of Oncomelania snail in mainland China by geographic information system(GIS) database].

To analyze spatial distribution of Oncomelania snail populations in mainland China by geographic information system (GIS) database.Genetic variation experiment data and experimental data of susceptibility of 34 snail populations were collected from nine provinces in China, to set up a database. A world digital map was linked with the database in a software ArcView Release 3.0 a to be used to divide zones with ArcView spatial analyze function and GIS overlaying function. AVHRR NDVI satellite images were collected to form a new one for prevalent season, which were overlaid with distribution maps of heterozygous indices of snail populations, polymorphic locus percentage and infection rates of snail population with schistosome for classifying the images.Spatial analysis showed that distribution maps of genetic heterozygous indices of snail, percentage of polymophic loci and infection rate of snail can be divided into two large zones, i.e., east zone and west zone, both with varied pictures. Analysis for overlaying three-stratum distribution map with AVHRR NDVI satellite image showed four distinctly different spatial zones, including west Sichuan zone, west Yunnan zone, middle zone of river, lake and marshland, and southeast coastal zone.It is the first time using GIS to analyze data of Oncomelania population genetics and confirmed the population structure of Oncomelania snails presented discrete sub-population model, which supports the theory of sub-species of Oncomelania spp. Exited in mainland China.
Horizon 2020 Societal Challenge 2 “Food Security, Sustainable Agriculture and Forestry, Marine, Maritime and Inland Water Research, and the Bioeconomy” Advisory Group Recommendations Programming Period 2018-2020

The Horizon 2020 Societal Challenge 2 Programme was created to develop and implement an EU research and innovation policy for more sustainable and resource efficient agriculture, forestry, inland water and marine systems that supply European society with sufficient food, feed, biomass, and other raw materials, as well as ecosystems services, and support thriving rural and coastal livelihoods. The European Commission has established Societal Challenge Advisory Groups to provide consistent and consolidated advice - by way of opinions, recommendations and reports - on relevant research objectives and scientific, technological and innovation priorities for its strategic and annual work programmes. Our Societal Challenge 2 Advisory Group includes a wide range of members with remarkably rich and diverse backgrounds and affiliations, including researchers, academics, former policymakers - stakeholders covering the whole spectrum of relevant research and innovation domains. Our Advisory Group has met twice formally since our establishment in February 2016, and has used other opportunities for extensive discussion and engagement on the issues surrounding this Societal Challenge. We see Societal Challenge 2 as not only extremely important as a challenge in itself, but also strongly linked with other Societal Challenges such as health, demographic change and wellbeing, climate action, environment, resource efficiency and raw materials, and inclusive, innovative and reflective societies in a changing world. And as the agriculture, forestry, fisheries and food sectors comprise a very large number of smaller businesses – themselves serving large scale processing and retail business sectors – there are strong links between our contribution and the input of groups advising on innovation in small and medium-sized enterprises, international cooperation, nanotechnologies, advanced materials and advanced manufacturing and processing. Our Advisory Group‘s first task has been to prepare this report to answer five specific questions posed by the Commission and provide input into the strategic programming cycle of the Work Programme for 2018-2020. We have identified some overriding strategic priorities, and backed those with the results of a more detailed analysis of the gaps that need to be addressed. And we highlight the cross-cutting nature of this programme and the importance of an integrated approach to maximise the overall impact of the current Horizon 2020 programme. We hope that the insights in this report may also assist in the identification and prioritisation of research needs and strengthen the Commission‘s strategic and impact-oriented approach in future years.
Data, Knowledge and Discovery

Increasingly it is data, vast amounts of data, that drives scientific discovery. At the heart of this so-called "fourth paradigm of science" is the rapid development of large scale statistical data fusion and machine learning methods. While these developments in "big data" methods are largely driven by commercial applications such as internet search or customer modelling, the opportunity for applying these to scientific discovery is huge. This talk will describe a number of applied machine learning projects addressing real-world inference problems in physical, life and social science areas. In particular, I will describe a major Science and Industry Endowment Fund (SIEF) project, in collaboration with the NICTA and Macquarie University, looking to apply machine learning techniques to discovery in the natural sciences. This talk will look at the key methods in machine learning that are being applied to the discovery process, especially in areas like geology, ecology and biological discovery.
SELECTION AND BENEFITS OF HUMAN RESOURCE INFORMATION SYSTEM (HRIS)

Human Resources Information System (HRIS) is essential for companies to manage their benefits plans and their employee information. Companies must use the Human Resources Information System (HRIS) to handle their employee data and benefit schemes. Benefits management technology is becoming a "need to have," not a "nice to have," as HR must handle a deluge of data and the cost of benefits plans while working with constrained resources [6]. The recruitment, evaluation, development, retention, and use of human resources to meet organizational and personal goals is known as human resources management, or HRM. The integration of Information Systems (IS) with Human Resources Management (HRM) is known as HRIS. HRISs provide HR professionals with the technological tools they need to carry out HR tasks more methodically and effectively. It is the system that gathers, stores, manipulates, examines, retrieves, and disseminates relevant data about the human resources of an organization [7]. Over the past 20 years, there has been an exponential increase in the number of computer-based information systems in both public and private sector businesses. A new sector of the computer products and services business has emerged to supply the tools required to build computer-based information systems. Even though a sizable workforce is engaged in the design and operation of information systems, a much larger number of people use or are "consumers" of information systems [1]. There are some cutting-edge technology solutions that are available for HR departments, right from quantitative representation of employee data to the current trend of building behavior models that can be used as predictive tools. “Commercial applications are available in the markets that help capture information and build models [8]. In this article researcher has explained the numerous benefits of HRIS and outline key features to look for when choosing such a system.
Statistical mechanics methods and phase transitions in optimization problems

Review article, 80 pages, uses elsart.cls
A polarizable interatomic force field for TiO$_2$ parameterized using density functional theory

We report a classical interatomic force field for TiO$_2$, which has been parameterized using density functional theory forces, energies, and stresses in the rutile crystal structure. The reliability of this new classical potential is tested by evaluating the structural properties, equation of state, phonon properties, thermal expansion, and some thermodynamic quantities such as entropy, free energy, and specific heat under constant volume. The good agreement of our results with {\em ab initio} calculations and with experimental data, indicates that our force-field describes the atomic interactions of TiO$_2$ in the rutile structure very well. The force field can also describe the structures of the brookite and anatase crystals with good accuracy.
Fractional Policy Gradients: Reinforcement Learning with Long-Term Memory

We propose Fractional Policy Gradients (FPG), a reinforcement learning framework incorporating fractional calculus for long-term temporal modeling in policy optimization. Standard policy gradient approaches face limitations from Markovian assumptions, exhibiting high variance and inefficient sampling. By reformulating gradients using Caputo fractional derivatives, FPG establishes power-law temporal correlations between state transitions. We develop an efficient recursive computation technique for fractional temporal-difference errors with constant time and memory requirements. Theoretical analysis shows FPG achieves asymptotic variance reduction of order O(t^(-alpha)) versus standard policy gradients while preserving convergence. Empirical validation demonstrates 35-68% sample efficiency gains and 24-52% variance reduction versus state-of-the-art baselines. This framework provides a mathematically grounded approach for leveraging long-range dependencies without computational overhead.
Implementing a Pediatric Rapid Response System to Improve Quality and Patient Safety

Life-threatening events are common in today's hospitals, where an increasing proportion of patients with urgent admission are cared for by understaffed, often inexperienced personnel. Medical errors play a key role in causing adverse events and failure to rescue deteriorating patients. In-hospital cardiac arrest outcomes are generally poor, but these events are often preceded by a pattern of deterioration with abnormal vital signs and mental status. When hospital staff or family members observe warning signs and trigger timely intervention by a rapid response team, rates of cardiac arrest and mortality can be reduced. Rapid response team involvement can be used to trigger careful review of preceding events to help uncover important systems issues and allow for further improvements in patient safety.
Research on the Implications of the Establishment of the International Organization for Mediation for the Reform of Dispute Settlement Mechanism of the World Trade Organization

As a specialized intergovernmental legal organization for resolving international disputes, the International Organization for Mediation (IOMed) is characterized by a treaty-based hard law nature. It adjudicates various types of disputes, incorporates flexible procedures embedded with Chinese harmony wisdom, and forges a distinctive dispute settlement model. The World Trade Organization (WTO) Dispute Settlement Mechanism (DSM) is currently confronted with multiple predicaments, including the suspension of the Appellate Body, excessive judicialization and inefficiency in adjudication procedures, dysfunctional alternative dispute resolution (ADR) mechanisms, and reform outcomes falling short of expectations. Certain distinctive arrangements in the DSM of the IOMed can provide insights for the optimization of the WTO DSM: (1) Through a confidential mediation mechanism, parties are provided with an opportunity to back down with dignity, and the panel is encouraged to guide the two sides to reach a consensus on the basis of ascertainment of facts. (2) Establish a “Mediation and ADR Center” within the WTO Secretariat, ensure the establishment of a strict information isolation system between this Center and the Legal Affairs Division serving the panels, and promulgate a detailed protocol on mediation procedures. (3) Stipulate a mandatory pre-mediation clause, and allow the panel to disclose its preliminary views on the core issues to both parties prior to issuing its report, so as to encourage them to reach a settlement. (4) When appointing panel members or arbitrators of Multi-Party Interim Appeal Arbitration Arrangement, greater consideration should be given to candidates’ cross-cultural understanding capacity; it is recommended that parties to specific types of disputes utilize the platform of the IOMed, and promote the WTO-recognized right to trade retaliation to serve as a safeguard for the enforcement of mediation agreements.
DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification

We present the data used in "DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification". Data processing and analysis pipelines in cosmological survey experiments introduce data perturbations that can significantly degrade the performance of deep learning-based models. We consider perturbations associated with two primary sources: 1) increased observational noise as represented by higher levels of Poisson noise; 2) data processing noise incurred by steps such as image compression or telescope errors as represented by one-pixel adversarial attacks. We also test the efficacy of domain adaptation techniques in mitigating the perturbation-driven errors. Successful development and implementation of methods that increase model robustness in astronomical survey pipelines will help pave the way for many more uses of deep learning for astronomy. To create our data, which emulates Vera C. Rubin LSST observations, we use GalSim (Rowe et al. 2015) and follow the same procedure as in Sanchez et al. (2021). We create two sets of survey-emulating images, by applying an exposure time directly to the raw images: 1) low-noise ten-year survey ("Y10'') - baseline data our models are trained on; 2) high-noise one-year survey ("Y1'') - noisy data. We use one-pixel attack (Su et al. 2017) to attack a 150-image test set sub-sample of Y10 images, in order to emulate pixel-level perturbations, that might naturally arise in astronomical data pipelines. Data: Images Y10: images_Y10_train.npy; images_Y10_valid.npy; images_Y10_test.npy Noisy mages Y1: images_Y1_train.npy; images_Y1_valid.npy; images_Y1_test.npy Labels valid for both Y10 and Y1: labels_train,npy; labels_valid.npy; labels_test.npy Small 150-image sub-samples: Images: images_Y10_test_150.npy; images_Y1_test_150.npy Labels: labels_test_150.npy
Quantum error correction beyond qubits

Quantum computation and communication rely on the ability to manipulate quantum states robustly and with high fidelity. Thus, some form of error correction is needed to protect fragile quantum superposition states from corruption by so-called decoherence noise. Indeed, the discovery of quantum error correction (QEC) turned the field of quantum information from an academic curiosity into a developing technology. Here we present a continuous-variable experimental implementation of a QEC code, based upon entanglement among 9 optical beams. In principle, this 9-wavepacket adaptation of Shor's original 9-qubit scheme allows for full quantum error correction against an arbitrary single-beam (single-party) error.
Adolescent social media user types and their mental health

Video abstract from Lizzy Winstone on her JCPP Advances paper 'Adolescent social media user types and their mental health and well-being: Results from a longitudinal survey of 13–14-year-olds in the United Kingdom'.
On Residual Modulation of Galactic Cosmic Rays in the Heliosphere

The residual modulation of galactic cosmic rays and its energy dependence have been investigated using data from three types of ground-based detectors and from PAMELA, AMS-02, Voyager 1, and Voyager 2 data. Quantitative estimates of the residual modulation in the range of rigidities of 4–41 GV were obtained. It was shown that the residual modulation is approximately the same in magnitude as the modulation due to the solar activity cycle that allows us to draw some conclusions about the modulation processes in the heliosphere. The energy spectrum of the residual modulation was obtained. A comparison was made with the results of other authors up to the Maunder epoch.