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At one time, the legal profession largely regulated itself. However, based on the economic notion that increased competition would benefit consumers, jurisdictions have deregulated their legal markets by easing rules relating to attorney advertising, fees, and, most recently, nonlawyer ownership of law firms. Yet, despite reformers' high expectations, legal markets today resemble those of previous decades, and most legal services continue to be delivered by traditional law firms. How to account for this seeming inertia? We argue that the competition paradigm is theoretically flawed because it fails to fully account for market failures relating to asymmetric information, imperfect information, and negative externalities. In addition, the regulatory costs imposed on sophisticated consumers such as corporate purchasers of legal services differ radically from those imposed on ordinary consumers who use legal services infrequently. Merely increasing the number and types of legal services providers cannot make legal markets more efficient. We illustrate our theoretical account with evidence from the United Kingdom, Europe, and Asia. For legal markets to better serve the public, regulators must tailor solutions by segment. Regulators should seek to minimize negative externalities associated with the delivery of legal services to the corporate segment and confront information asymmetries that lead to the maldistribution of legal services in the consumer segment. Deregulation alone is insufficient and may in fact exacerbate existing market failures. [ABSTRACT FROM AUTHOR]

Federated Learning (FL) presents a decentralized approach to model training in the agri-food sector and offers the potential for improved machine learning performance, while ensuring the safety and privacy of individual farms or data silos. However, the conventional FL approach has two major limitations. First, the heterogeneous data on individual silos can cause the global model to perform well for some clients but not all, as the update direction on some clients may hinder others after they are aggregated. Second, it is lacking with respect to the efficiency perspective concerning communication costs during FL and large model sizes. This paper proposes a new technical solution that utilizes network pruning on client models and aggregates the pruned models. This method enables local models to be tailored to their respective data distribution and mitigate the data heterogeneity present in agri-food data. Moreover, it allows for more compact models that consume less data during transmission. We experiment with a soybean yield forecasting dataset and find that this approach can improve inference performance by 15.5% to 20% compared to FedAvg, while reducing local model sizes by up to 84% and the data volume communicated between the clients and the server by 57.1% to 64.7%. Our method demonstrates the potential to use efficient models that are more environmentally friendly to support the agri-food sector's transition to net zero. Future enhancements of this method could further optimize distributed learning in agri-food, enhancing sustainability and applicability. • We propose a new federated pruning learning method for yield forecasting. • Our method can be used to improve local inference performance. • The method reduces communication costs during training and model sizes. • Our method facilitates the on-edge implementation of ML models using sparse tensor. • The method is generalizable and works with different pruning policies and schedules. [ABSTRACT FROM AUTHOR]

The bar examination has long loomed over legal education. Although many states formerly admitted law school graduates into legal practice via the diploma privilege, Wisconsin is the only state that recognizes the privilege today. The bar exam is so central to the attorney admissions process that all but a handful of jurisdictions required it amidst a pandemic that turned bar exam administration into a life-or-death matter. In this Article, I analyze the diploma privilege from a historical and empirical perspective. Whereas courts and regulators maintain that bar exams screen out incompetent practitioners, the legal profession formerly placed little emphasis on bar exams and viewed them as superfluous for graduates of accredited law schools. The organized bar turned against the diploma privilege as the legal profession began to diversify, and some states abolished the diploma privilege specifically to block Black law students from the profession. The notion that bar exams ensure a base level of competence is a relatively recent construct. A few studies have suggested that attorneys who struggle on the bar exam are more likely to commit misconduct. However, drawing on cross-state attorney complaint and charge data as well as Wisconsin attorney disciplinary cases, I demonstrate that the bar exam requirement has no effect on attorney misconduct. The complaint rate against Wisconsin attorneys is similar to that of other jurisdictions, and Wisconsin attorneys are charged with misconduct less often than attorneys in most other states. Moreover, the rate of public discipline against Wisconsin attorneys who were admitted via the diploma privilege is the same as that of Wisconsin attorneys admitted via bar exams. Bar exams as currently constituted do little to advance public protection. A carefully drafted and enacted diploma privilege would comply with the Constitution's Dormant Commerce Clause and would incentivize law schools to better prepare students for practice. States also have more direct means to address attorney misconduct than relying on ex ante measures such as bar exams. [ABSTRACT FROM AUTHOR]

The advent of artificial intelligence has provoked considerable speculation about the future of the American workforce, including highly educated professionals such as lawyers and doctors. Although most commentators are alarmed by the prospect of intelligent machines displacing millions of workers, this is not so with respect to the legal sector. Media accounts and some legal scholars envision a future where intelligent machines perform the bulk of legal work, and legal services are less expensive and more accessible. This future is purportedly at hand as lawyers struggle to compete with technologically savvy alternative legal service providers. This Article challenges the notion that lawyers will be displaced by artificial intelligence on both empirical and normative grounds. Most legal tasks are inherently abstract and cannot be performed by even advanced artificial intelligence relying on deep-learning techniques. In addition, lawyer employment and wages have grown steadily over the last twenty years, evincing that the legal profession has benefited from new technologies, as it has throughout its history. Lastly, were large-scale automation of legal work possible, core societal values would counsel against it. These values are not merely aspirational but are reflected in the multifaceted role of lawyers and in the way that the legal system is structured. [ABSTRACT FROM AUTHOR]

The 2008 economic recession had a seismic impact on the legal market. In this article, we empirically assess whether the recession has made law an unsatisfying career. Relying on survey data from over 11,000 active members of the State Bar of Texas, we find that only 13.5 percent of all attorneys and 11.5 percent of full-time attorneys are dissatisfied with their careers. Newer attorneys report greater career dissatisfaction than more experienced attorneys, yet they too are largely satisfied. We also determine using logistic regression that three factors are highly predictive of lawyers’ career dissatisfaction: (1) comparatively low incomes; (2) working in private practice as opposed to in government or non-profit/public interest; and (3) law firm employment in a non-partnership role. Equally important, debt and lower class rank only slightly increase the odds of career dissatisfaction; and race, gender, years of practice experience, and firm size have no effect. [ABSTRACT FROM AUTHOR]

In order to achieve high results in sports, it is necessary to provide an adequate status of an athlete in according to various factors, among which the body structure is one of greater importance. The aim of this research is to define the most discriminated indicators of body structure indexes, thanks to which a specific change of physical structure can be observed according to a branch of sport and type of combat sport. Variables in the research were: body height, body mass, body mass index, free fat mass index, fat mass index, protein mass index, skeletal muscle mass index, percent of body fat, percent of skeletal muscle mass and protein fat index. The measuring of the body composition is realized by using multichannel segmental bioimpedance with InBody 720 apparatus, applied on the total of 112 male high level senior-age athlete members of different national team's member of Republic of Serbia (62 judokas, 29 Greco-Roman style wrestlers and 21 karatekas). The discriminative analysis has shown that subsamples of the athletes statistically differ in morphology on Wilks' lambda level (0.435, p = 0.000), and that following variables have the highest discrimination compared to athlete respondents in sport function: percent of skeletal mass (0.34), percent of body fat (0.28) and protein fat index (0.26), as the first isolated factor (p = 0.000) by which is explained 86.3%, that is body weight (0.74), skeletal muscle index (0.73), protein mass index (0.72), body mass index (0.72) and free fat mass index (0.70), as the second factor (p = 0.030) by which 13.7% variability of measured body structure space is explained. By establishing body structure models of judokas, wrestlers and karatekas for variables examined and by using modern technological method of measuring (InBody 720, 2008) we got new information that characterize specificity of the sport, which all contribute to spreading and improving already existing knowledge in the sports sciences and sport body morphology area. [ABSTRACT FROM AUTHOR]

Study after study has concluded that the United States suffers from a lack of access to justice because most legal issues are addressed without attorney involvement. To better serve Americans who cannot currently afford legal assistance, scholars have argued that corporations should be permitted to offer legal services. England and Australia already allow corporations to own law firms and deliver legal services. Whatever the merits of corporate delivery of legal services, its impact on access to justice has been overstated. The cost of legal services plays a minor role in decisions to not obtain legal assistance. Moreover, many legal services are relatively affordable, and those that are currently cost-prohibitive such as complex litigation cannot be delivered ethically at significantly lower prices. Whereas the legal profession has largely assumed that legal services are very valuable and highly sought after, low- and middle-income people also appear to not prioritize legal assistance and may not benefit from assistance in some situations. To expand access to justice, the legal profession should educate the public about common legal problems and reconsider ethical rules that hinder attorneys from soliciting business and marketing their services. Legal aid and pro bono resources should be targeted to significant legal problems that cannot be addressed without attorney involvement. Increasing the supply of low-cost legal services providers would merely exacerbate existing inequalities in the legal system while failing to address the need for high quality legal representation with respect to complex matters. [ABSTRACT FROM AUTHOR]

• Data sharing in Agri-Food supply chains remains a major challenge. • Machine Learning approaches require large amounts of data to provide actionable insights, such as yield forecasting. • Federated learning and privacy preserving technologies can offer solution to this stalemate. • This paper proposes a federated learning approach, applied to soybean yield forecasting. • Our approach performs better than each of the models trained on an individual data source. Data sharing remains a major hindering factor when it comes to adopting emerging AI technologies in general, but particularly in the agri-food sector. Protectiveness of data is natural in this setting: data is a precious commodity for data owners, which if used properly can provide them with useful insights on operations and processes leading to a competitive advantage. Unfortunately, novel AI technologies often require large amounts of training data in order to perform well, something that in many scenarios is unrealistic. However, recent machine learning advances, e.g. federated learning and privacy-preserving technologies, can offer a solution to this issue via providing the infrastructure and underpinning technologies needed to use data from various sources to train models without ever sharing the raw data themselves. In this paper, we propose a technical solution based on federated learning that uses decentralized data, (i.e. data that are not exchanged or shared but remain with the owners) to develop a cross-silo machine learning model that facilitates data sharing across supply chains. We focus our data sharing proposition on improving production optimization through soybean yield prediction, and provide potential use-cases that such methods can assist in other problem settings. Our results demonstrate that our approach not only performs better than each of the models trained on an individual data source, but also that data sharing in the agri-food sector can be enabled via alternatives to data exchange, whilst also helping to adopt emerging machine learning technologies to boost productivity. [ABSTRACT FROM AUTHOR]

The article discussesd that the attorney conflicts of interest also played an underappreciated role in the financial crisis as representation of law firm Sullivan & Cromwell LLP in the bankruptcy case of financial services firm Lehman Brothers. It mentions the effectiveness of Model Rule 1.7 of the Model Rules of Professional Conduct, relationship of Sullivan with U.S. Department of Treasury and the Federal Reserve prevented it from aggressively advocating for Lehman.

The article presents information on the interrelationship between legal ethics and international criminal law based on the actions taken by the Office of the Prosecutor (OTP) of the International Criminal Court in the trials of Prosecutor v. Lubanga and Prosecutor v. Al-Bashir. The lack of specific ethics code for (OTP), the related obligations and the issues related to prosecutorial discretion are discussed. The need of specific rules for managing the conflicting duties is also discussed.

The pedagogical benefits of active learning environments such as simulations within university teaching have been widely acknowledged. This paper starts from the premise that simulations can derive benefits when used as an effective university outreach tool to widen participation in and raise aspirations towards entering higher education. We argue that European Union (EU)-related simulations involving students in secondary education can increase their interest in studying European politics and, more generally, political science and international relations at university level. This is seemingly particularly the case with students predisposed to pursuing a degree in these fields. The paper uses data gathered via a pre- and post-simulation questionnaire completed by pupils attending six secondary schools in 2016 who all participated in one of the three simulations included in the study. Empirical investigation reveals three major effects of simulations. First, the simulations can increase participants' interest in pursuing university degrees in fields cognate to EU politics. Second, simulations can increase participants' self-assessed knowledge of EU politics. Third, simulations can increase the importance participants place on understanding the workings of the EU. Taken together, these findings support our claim that EU-related simulations may be used as outreach tools to increase interest in pursuing EU-related subjects at university level. Such an increase is desirable despite—or perhaps precisely because—of the ongoing Brexit process, as the understanding of and engagement with EU politics will remain relevant for current and future generations of British students. [ABSTRACT FROM AUTHOR]

The aim of this research is to investigate the correlation of morphological characteristics, that is, body composition characteristics with the competitive performance of female basketball players of cadet (U16) age, in general and depending on the position played in the basketball team. The research involved female basketball players from the U16 section of the three best basketball clubs from the First Cadet League of Serbia (N = 30). This research consisted of measuring the characteristics of body composition, as a space of independent variables and the analysis of competitive activities where the dependent variable represents the level of achieved competitive performance. Based on the results of the Pearson Correlation Analysis, which was made for determining the degree of connection between the dependent variable and the independent variables, it can be seen that general level competitive performance is associated with the variables: percentage skeletal muscle mass, index of hypokinesy and protein-fat index. Viewed from the point of the position played in the team, the statistically significant relationship between the independent and the dependent variable was recorded only in the forwards position. Competitive and more successful forward players are distinguished by a small percentage of body fat mass, a higher percentage of muscle mass, a smaller hypokinesy index and a larger protein-fat index. The practical application of this research can be seen in the control system of applied training work, then selection, as well as in the creation of a model for morphological characteristics of players in the cadet (U16) age. [ABSTRACT FROM AUTHOR]

This paper describes the situation in Belgrade, Yugoslavia, during the 1990s. An ecosystemic paradigm was used in its conceptualization and operationalization at multisystem levels of context. Description is based on research performed on 50 "normal" families under chronic stress and persistent crises, as well as on the authors' personal and professional experience, both as participants and observers faced with everyday, new stressful life events. The families have modified their system functioning on cohesion dimension (enmeshment) and on flexibility dimension (chaos), activating and mobilizing families' strengths, resources, and resilience to survive and to adapt to persistent/chronic stressful life in the context of global crisis of the society. A dramatic social transformation-greatly modified social structure, different dominant social actors, a new "logic" of functioning, and new social problems and contradictions-leave its stamp on everyday life. At the same time, families have confirmed their strengths and resilience in the past difficult times as a basis for our hope and optimism for the progress in the future. [ABSTRACT FROM AUTHOR]

The fatty acid content is a very important feature of the milk that affects the health of consumers. The aim of this study was to estimate cow's milk fatty acid composition in early vegetative, late vegetative and reproductive phase, with the simultaneous determination of the pasture biomass chemical and botanical composition. The research was conducted on Agrostis castellana semi-natural dry grassland in the vicinity of Podgorica, Montenegro. Cows were put to grazing during the whole experimental period. This pasture was assessed as moderate to good quality and botanically diversified. The chemical composition of the grassland biomass changed with the maturity phase. A significant increase in the content of DM, crude fiber, fat and a decrease in crude protein content were determined throughout three phenological phases (p < 0.05). The content of total milk fat did not show significant variability during first two phases, but it did in the third phase. The content of milk fat and protein was high in all phases, although it is a dry pasture with a poor quality of biomass in the third phase. The content of majority saturated fatty acids (SFAs) increased with grass maturity, while total content of monounsaturated fatty acids (MUFAs) decreased. The polyunsaturated fatty acids (PUFAs) content kept the same level up to the reproductive phase. The phenological phase significantly influenced the content of fatty acids in the third phase (p < 0.05). A notable number of SFAs, MUFAs end PUFAs had the highest content in the second phase. [ABSTRACT FROM AUTHOR]

Laser ablation in liquid (LAL) emerged as a versatile technique for the synthesis of nanoparticles with various structures and compositions, although the control over products remains challenging in most cases. For instance, it is still difficult to drive the size of metal oxide crystalline domains down to the level of few atom clusters with LAL. Here we demonstrate that laser ablation of a bulk iron target in aqueous solution of phosphonates gives phosphonate-grafted iron oxo-clusters polymerized into nanoaggregates with Fe:ligand ratio of 2:1, instead of the usual nanocrystalline iron oxides. We attribute this result to the strong ability of phosphonate groups to bind iron oxide clusters and prevent their further growth into crystalline iron oxide. These laser generated poly-oxo-clusters are biocompatible and trackable by magnetic resonance imaging, providing interesting features for use in biological environments, such as nano-vehicles for iron administration. Besides, this method is promising for the generation of atom-scale metal-oxide clusters, which are ubiquitary in chemistry and of interest in biochemistry, catalysis, molecular magnetism and materials science. [ABSTRACT FROM AUTHOR]

Ruptured and repaired Anterior Communicating Artery (ACoA) aneurysm canresult in devastating impairments involving memory, executive function, confabulation,and personality changes. This study tested serial position learning effects(SPEs) in patients following repaired and ruptured ACoA aneurysm, using resultson the Rey Auditory Verbal Learning Test (RAVLT). Thirty patients with rupturedaneurysms of the ACoA and 31 matched controls were included in the study.The primacy-recency effects were maintained during five learning trials inACoA group, albeit at an overall lower level than in the controls. There wasno difference in primacy-recency relation across five learning trials in ACoAgroup. On the delayed recall trial the patient group demonstrated neithera primacy, nor a recency phenomenon, reflecting a lack of recall of any partsof the word list. This kind of primacy-recency profile across learning trialsin ACoA group has no similarity with SPE results in frontal lesion groups,or with SPE distributions in other amnesic disorders, despite the fact thatmemory and executive deficits were evident in our ACoA group. [ABSTRACT FROM AUTHOR]