Abstract: Law enforcement is a prerequisite for realizing legal protection in Indonesia. Law enforcement in Indonesia is a complex and ongoing issue, involving various structural, cultural, and political factors. Although Indonesia has a clear legal framework, the implementation of law enforcement often does not reflect the principles of justice and transparency. This research is a normative research. Normative legal research has a tendency to portray law as a prescriptive discipline where it only looks at law from the perspective of its norms which are of course descriptive. This research was conducted in real conditions with the aim of being able to find existing facts to be used as data filler in this research so that later the problem will be found. Implementation of the Supremacy of Law in Indonesia: Fact or Illusion that in the realization of law enforcement there are several obstacles, especially obstacles from the legal system itself. It is hoped that students are able to overcome and improve by channeling their aspirations in solving these obstacles. Students as academics must implement their actions to advance this country and represent the aspirations of the community because basically students uphold the interests of the community.

Exploring work motivation in High and Intensive Care wards with the confession booth: An innovative approach.

Dynamic modeling and integrated control framework for an eye-like robot with torsional–positional decoupling and Listing’s law enforcement

Economic exclusion and criminal adaptations: A qualitative study of youth unemployment in Ghana

Rulers’ agents: Localism of law enforcement leaders and the patterns of trade

Evaluating the impacts of law enforcement and market outreach campaigns on the Indonesian caged bird trade in Kalimantan

Mobile crisis services offer a community-based alternative to law enforcement and emergency departments for individuals experiencing behavioral health crises. Medicaid claims represent a promising but underused tool for national surveillance of these services. Despite growing federal investment and expansion of crisis response systems, there is no standardized method for identifying mobile crisis encounters in administrative claims, limiting the ability to monitor access, evaluate implementation, or compare delivery across states. To develop and evaluate claims-based approaches for identifying mobile crisis service delivery in Medicaid administrative data. We conducted a cross-sectional analysis of 2021 Medicaid claims from the Transformed Medicaid Statistical Information System Analytic Files. We used the 2022 KFF Behavioral Health Services Survey data as the most recent standardized benchmark for Medicaid mobile crisis coverage. We tested 3 claims-based identification approaches that combine national and state-specific procedure codes (eg, H2011) with mobile-relevant place-of-service (POS) codes: strict [POS 15 (mobile unit)], moderate [POS 15 (mobile unit), POS 12 (home), or POS 04 (homeless shelter)], and inclusive [POS 15, POS 12, POS 04, or POS 99 (other)]. We additionally constructed a claims-based score summarizing state-level use of mobile-relevant POS codes and examined its alignment with reported coverage in exploratory analyses. Among 44 states and the District of Columbia with complete survey data, 33 reported Medicaid coverage of mobile crisis services. We identified 97,088 claims under the strict approach, 395,141 under the moderate approach, and 1,152,653 under the inclusive approach. Across all approaches, states reporting coverage had higher median claim counts than noncoverage states, though substantial overlap remained. Under the strict approach, median claim counts were 0 in both coverage and noncoverage states. The moderate approach demonstrated the greatest separation (median, 1324 vs. 364), while the inclusive approach captured larger volumes overall but with greater overlap between groups. Predicted probabilities derived from a claims-based score increased monotonically across score values, indicating stronger directional alignment with reported coverage at higher score levels. A claims-based approach combining mobile unit (POS 15), home (POS 12), and homeless shelter (POS 04) codes with crisis intervention procedure codes provides a practical framework for identifying billed mobile crisis encounters in Medicaid data. This moderate approach showed the strongest directional alignment with state-reported coverage and may support cross-state monitoring of crisis service delivery. Further work is needed to validate these methods using provider-level or encounter-level data.

How have liberalized drug policies impacted international policing practices across urban and rural jurisdictions? A scoping review.

Utility of Embedding a Physical Therapist in a United States National Park: A Pilot Program.

This data article presents an image dataset compiled for the purpose of machine learning-based identification and prediction of adulteration levels in Teff (Eragrostis tef (Zucc.) Trotter) flour. The dataset includes images of pure white, mixed, and red Teff flour varieties, as well as these flours adulterated with wood flour (sawdust) and gypsum (calcium sulfate) powder. Adulteration levels range from 10% to 40% in 5% increments. The data collection process involved preparing Teff flour from naturally dried and milled Teff grains. Samples of 100 grams of each Teff flour variety were then mixed with the adulterants at the specified concentrations. A total of 5,000 raw images were captured using an 18-megapixel Canon EOS 7D camera under controlled studio lighting (300 W incandescent lamps), with the samples placed 30 cm from the camera lens in a 10 cm x 10 cm plastic box. To enhance the dataset's diversity and quantity, 25,000 augmented images were generated by shuffling image pixels' locations with various block sizes (1 × 1, 2 × 2, 4 × 4, 8 × 8, and 16 × 16). This dataset is a valuable resource for researchers and students in Teff adulteration using image processing and feature extraction. It also holds potential for use by Food and Drug Administration Authorities and law enforcement to develop automated methods for detecting Teff flour adulteration, offering an alternative to time-consuming physio-chemical laboratory tests. The dataset's structure and augmentation methods are detailed to ensure reproducibility and encourage further research into robust machine learning models for food quality control.

Seizure-to-market ratios and the resilience of the drug markets in France (2010-2023).

"Stigmatisation for poppers use is a sexualised mode of governance": Lived experiences and counter-narratives of gay men who use poppers in mainland China.

The rapid development of information and communication technologies has significantly increased both the number and complexity of cybercrime cases. These crimes often involve sophisticated technical processes that exceed the professional competence of investigators, prosecutors, and judges who are primarily trained in legal sciences. As a result, the effectiveness of cybercrime investigations largely depends on the proper use of expert examinations based on specialized technical knowledge. This study aims to analyze the role and significance of cyber expertise in solving cybercrime cases, identify the shortcomings of existing computer-technical (digital forensic) expertise, and justify the need for a more comprehensive and specialized classification of expertise in the field of information and communication technologies. The research employs doctrinal legal analysis, comparative analysis, and a descriptive-analytical method. National legislation of the Republic of Uzbekistan, law enforcement and judicial practice, and foreign experience in the application of cyber and digital forensic expertise were examined, alongside technical aspects of telecommunication networks, information systems, software, cryptography, and communication quality. The findings demonstrate that the prevailing reliance on computer-technical expertise is insufficient to address the multifaceted nature of cybercrimes, which frequently involve telecommunication infrastructure, encryption technologies, software applications, and communication quality issues beyond the traditional scope of digital forensics. The study substantiates the need to introduce specialized types of expertise, including telecommunication network and infrastructure expertise, information systems and computer data expertise, software and application expertise, cryptographic expertise, communication coverage and quality expertise, and cyber forensic auditing. Particular emphasis is placed on cyber forensic auditing as a mechanism for ensuring the admissibility and reliability of digital evidence. The study concludes that the current forensic framework should be expanded and systematized, and recommends developing specialized expert training and updating procedural legislation to enhance the effectiveness of cybercrime investigations.

ABSTRACT Practitioners’ preparedness for working with technology-facilitated child sexual abuse (TF-CSEA) has attracted limited attention in Australia. This study maps the capacity of the Australian sexual assault sector to support victims of TF-CSEA, including victims of child sexual abuse material (CSAM) and online child sexual extortion. A national survey of 124 practitioners was conducted to assess individual, organisational, and systemic dimensions of sector capacity. Practitioners’ self-reported experiences were treated as indicators of the sector’s collective readiness. Quantitative data from closed questions were analysed descriptively, and qualitative responses were coded thematically. Most practitioners reported only moderate preparedness to support victims, and few had access to specialist training or TF-CSEA-specific resources. Services predominantly relied on traditional “in-person” child sexual abuse (CSA) frameworks that offer limited guidance for managing digital evidence, online harms, and cross-jurisdictional issues. Practitioners identified systemic barriers, including fragmented interagency coordination, unclear referral pathways, and insufficient policy support. The findings highlight that sector capacity limitations reflect structural and policy constraints rather than practitioner deficits. This underscores the need for investment in specialist training, national coordination frameworks, and updated service systems that address online forms of abuse in Australia. IMPLICATIONS Advanced, accredited training can help social workers and related professionals keep pace with effective supports for children and adults who have experienced technology-facilitated child sexual abuse. Extending existing child sexual abuse practice frameworks to include online harms can strengthen social work and allied practice in responding to legal, digital, and psychological complexities. Clearer collaboration between social workers, law enforcement, and online safety agencies can improve referral pathways and reduce uncertainty for victims seeking support.

The increasing frequency of castor bean or ricin-induced intoxication or terror events threatens public safety and national security, making the tracing of castor bean origins critical for law enforcement and counterterrorism efforts. Chemical attribution signatures (CAS) could address this issue by providing inherent and forensic links between ricin-containing samples and their geographical origins; however, practical implementations of this approach remain scarce. Omics data sets offer substantial potential to generate comprehensive biological insights and high-dimensional data for provenance attribution, where transcriptomics and proteomics profiling are better suited to castor beans than traditional genomics and metabolomics, regarding that castor beans exhibit low genetic diversity but high phenotypic polymorphism. In this work, toward castor bean samples from 14 provinces or autonomous regions in China and three international locations, including Ethiopia, Pakistan, and South Sudan, we proposed an integrated local-global data-mining strategy by systematically integrating RNA-seq transcriptomics and data-independent acquisition quantitative proteomics, and developed a straightforward feature-screening pipeline to prioritize 59 signature peptides as provenance-related CAS with distinct interregional and international expression patterns. A subsequent machine learning model trained on these CAS achieved 93.7% classification accuracy, identifying robust discriminative patterns among samples from different global regions, as well as fine-scale differences across altitude gradients and north-south divisions in China, in which the attribution index of altitude and latitude is reported for the first time. Finally, after validation by parallel reaction monitoring in nanoLC-HRMS/MS, we confirmed a minimum signature panel of 24 peptides as molecular CAS markers for the origin attribution of castor beans.

The increasingly stringent dynamics of international tax regulations, marked by the expansion of tax authorities' audit powers and low revenue target achievements, trigger the urgency to re-evaluate the determinants of tax avoidance in Indonesia. This study aims to examine the effect of foreign ownership and firm size on transfer pricing practices during the transition period of tax law enforcement. Employing a quantitative approach, the research population includes all multinational companies listed on the Indonesia Stock Exchange (IDX) during the 2022-2024 period. Through a purposive sampling technique, 78 firm-year data were selected as samples. These secondary data were then analyzed using the Panel Data Regression method, calibrated with a series of classical assumption tests and the Common Effect Model selection. Empirical evidence shows that while foreign ownership has no significant effect and firm size has significant effect on the intensity of transfer pricing practices, showing a negative coefficient direction. These findings provide literature novelty by refuting traditional assumptions regarding corporate domination power and confirming the political cost hypothesis. The study’s significance lies in its exploration of the 2022–2024 transition period under the stringent framework of PMK No. 15 of 2025, revealing that large-scale entities prioritize transparent governance to mitigate heightened litigation risks and political costs.

Detecting fraud and corruption in public procurement remains a major challenge for governments worldwide. Most research to-date builds on domain-knowledge-based corruption risk indicators of individual contract-level features and some also analyses contracting network patterns. A critical barrier for supervised machine learning is the absence of confirmed non-corrupt (negative) examples, which makes conventional machine learning inappropriate for this task. Using publicly available data on federally funded procurement in Mexico and company sanction records, this study implements positive-unlabeled (PU) learning algorithms that integrate domain-knowledge-based red flags with network-derived features to identify likely corrupt and fraudulent contracts. The best-performing PU model on average captures 32% more known positives than random guessing and has a minimum of 20% precision on the top 5% of the predictions, substantially outperforming approaches based solely on traditional red flags. The analysis of the Shapley Additive Explanations reveals that network-derived features-particularly those associated with contracts in the network core or suppliers with high eigenvector centrality-are the most important. Traditional red flags further enhance model performance in line with expectations, albeit mainly for contracts awarded through competitive tenders. This methodology can support law enforcement in Mexico, and it can be adapted to other national contexts too.

ABSTRACT Much of the original philosophical literature on immigration focused on the general question of whether borders should be open. More recently, more specific questions regarding immigration have come to the fore. This article considers an important attempt to show that consideration of one of these more specific questions, the ethical limits on the enforcement of immigration law, leads to an answer to the general question of whether borders should be open. On this indirect argument for open borders, even if we assume that states have the right to exclude, the ethical limits on the means used to enforce this right imply that borders should be open. In early 2026, with President Trump using novel tactics to enforce immigration law and anti-immigrant sentiment on the rise in many countries, it may seem that this indirect argument is correct. However, using the United States’ Chinese Exclusion Cases as an example, I argue that the ethical limits on the means used to enforce the right to exclude do not imply that borders should be open.

Environmental pollution is a serious issue affecting ecosystem sustainability and public health. Industrial activities without proper waste management are a major cause of pollution, including water, air, and soil contamination. This condition not only causes environmental damage but also leads to social and economic losses for communities. Therefore, strict and effective law enforcement is required to create a deterrent effect and prevent similar actions. This study aims to examine the regulation of environmental crimes based on Law Number 32 of 2009 concerning Environmental Protection and Management and to analyze law enforcement against offenders from the perspective of the Indonesian Criminal Code (KUHP) 2023. The research method used is normative juridical with statutory and conceptual approaches through literature study. The results show that the 2023 Criminal Code provides a more comprehensive legal basis, particularly regarding corporate criminal liability. However, in practice, law enforcement still faces challenges such as weak supervision and difficulties in proving cases. Therefore, it is necessary to strengthen supervision and ensure consistent law enforcement to achieve optimal environmental protection

ABSTRACT Encryption is a key building block of digital society protecting the security of the online environment and enabling a meaningful exercise of civil liberties. This technology endows its users with power that does not always sit well with law enforcement and intelligence authorities, which accordingly lose their control over information exchanges within society. The arguments, albeit yet to be substantiated, that this dynamic significantly impacts the fight against crime or other threats have triggered decades-long ‘crypto-wars’ that endure to this day. These crypto-tensions are compounded by the reality that at present no technological solutions are known that could grant security agencies a so-called ‘exceptional access’ to communications and data without compromising cybersecurity and fundamental rights. This paper comprehensively explores encryption policy in the EU and how these debates have been playing out in the face of the quantum threat that requires mitigation with new methods of encryption.