НАУКОВІ ДОСЛІДЖЕННЯ ВЧЕНИХ КВГУ-КГІ-ДГІ В ГАЛУЗІ МЕТАЛУРГІЇ (1900-1930 рр.)

Перші зародки промислового вуглевидобутку на Півдні Російської імперії (Лисячий Байрак під Лисичанськом) і виробництва металу (м. Луганськ) виник-ли у 90-х роках ХVІІІ с. У наступні десятиліття ці взаємопов’язані галузі розвивалися дуже повільно. А трохи раніше спроба почати видобуток залізної руди і виплавку з неї гарматних ядер на Криворіжжі була невдалою, тому майже на сто років про ці поклади руд забули

Modelled direct causes of dust emission change (2001?2020) in southwestern USA and implications for management

North American observed atmospheric dust has shown large variability over the last two decades, coinciding with regional patterns of vegetation and wind speed changes. Dust emission models provide the potential to explain how these direct causes of vegetation and wind speed changes are related to changing dust emission. However, those dust models which assume land cover types are homogeneous over vegetation classes and fixed over time, are unlikely to adequately represent changing aerodynamic roughness of herbaceous cover, woody cover, and litter. To overcome these model limitations and explain changing (2001–2020) dust emission, we used a new MODIS albedo-based dust emission model calibrated to satellite-observed magnitude and frequency of dust emission point source (DPS) data. We focused our work on four regions of southwestern USA, identified previously as the main dust emission sources. We classified the interplay of controlling factors (wind speed and aerodynamic roughness) which created disturbance regimes with dust emission change consistent with diverse land use and management drivers. Our calibrated model results show that dust emission is increasing or decreasing, in different regions, at different times, for different reasons, consistent with the absence of a secular change of observed atmospheric dust. Our work demonstrates that using this calibrated dust emission model, sensitive to changing vegetation structure and configuration and wind speeds, provides new insights to the contemporary factors controlling dust emission. With this same approach, the prospect is promising for modelling historical and future dust emission responses using prognostic albedo in Earth System Modelling

Multiple Versus Single Antipsychotic Agents for Hospitalized Psychiatric Patients: Case-Control Study of Risks Versus Benefits

OBJECTIVE: Since use of multiple drugs to treat psychiatric patients is increasing, and research on this practice is rare, the authors carried out a retrospective case-control study of multiple versus single antipsychotic treatment in psychiatric inpatients. METHOD: Inpatient treatment groups receiving either antipsychotic monotherapy or polytherapy were matched in terms of age, sex, diagnostic category, and admission clinical ratings (Global Assessment of Functioning [GAF] and Clinical Global Impression [CGI]), which yielded 70 subject pairs. They were compared in terms of total chlorpromazine-equivalent daily dose, changes in total daily dose, length of hospitalization, incidence of adverse effects, and changes in clinical ratings (CGI, GAF, Positive and Negative Syndrome Scale score) between admission and discharge. RESULTS: Initial doses were closely similar at admission for both treatment groups, but the median total final antipsychotic dose was 78% higher for those receiving antipsychotic polytherapy versus monotherapy. Also, median length of stay in the hospital was 55% (8.5 days) longer, and risk of adverse effects was 56% higher with polytherapy, whereas clinical improvement scores were similar (within 11%) for both treatments. CONCLUSIONS: Short-term treatment with multiple antipsychotics was associated with major increases in drug exposure, adverse events, and time in the hospital but with no apparent gain in clinical benefit. These findings require further testing in controlled prospective studies

Elucidating Hidden and Enduring Weaknesses in Dust Emission Modeling

Large-scale classical dust cycle models, developed more than two decades ago, assume for simplicity that the Earth's land surface is devoid of vegetation, reduce dust emission estimates using a vegetation cover complement, and calibrate estimates to observed atmospheric dust optical depth (DOD). Consequently, these models are expected to be valid for use with dust-climate projections in Earth System Models. We reveal little spatial relation between DOD frequency and satellite observed dust emission from point sources (DPS) and a difference of up to 2 orders of magnitude. We compared DPS data to an exemplar traditional dust emission model (TEM) and the albedo-based dust emission model (AEM) which represents aerodynamic roughness over space and time. Both models overestimated dust emission probability but showed strong spatial relations to DPS, suitable for calibration. Relative to the AEM calibrated to the DPS, the TEM overestimated large dust emission over vast vegetated areas and produced considerable false change in dust emission. It is difficult to avoid the conclusion that calibrating dust cycle models to DOD has hidden for more than two decades, these TEM modeling weaknesses. The AEM overcomes these weaknesses without using masks or vegetation cover data. Considerable potential therefore exists for ESMs driven by prognostic albedo, to reveal new insights of aerosol effects on, and responses to, contemporary and environmental change projections

Satellites reveal Earth's seasonally shifting dust emission sources

Establishing mineral dust impacts on Earth's systems requires numerical models of the dust cycle. Differences between dust optical depth (DOD) measurements and modelling the cycle of dust emission, atmospheric transport, and deposition of dust indicate large model uncertainty due partially to unrealistic model assumptions about dust emission frequency. Calibrating dust cycle models to DOD measurements typically in North Africa, are routinely used to reduce dust model magnitude. This calibration forces modelled dust emissions to match atmospheric DOD but may hide the correct magnitude and frequency of dust emission events at source, compensating biases in other modelled processes of the dust cycle. Therefore, it is essential to improve physically based dust emission modules. Here we use a global collation of satellite observations from previous studies of dust emission point source (DPS) dichotomous frequency data. We show that these DPS data have little-to-no relation with MODIS DOD frequency. We calibrate the albedo-based dust emission model using the frequency distribution of those DPS data. The global dust emission uncertainty constrained by DPS data (±3.8 kg m−2 y−1) provides a benchmark for dust emission model development. Our calibrated model results reveal much less global dust emission (29.1 ± 14.9 Tg y−1) than previous estimates, and show seasonally shifting dust emission predominance within and between hemispheres, as opposed to a persistent North African dust emission primacy widely interpreted from DOD measurements. Earth's largest dust emissions, proceed seasonally from East Asian deserts in boreal spring, to Middle Eastern and North African deserts in boreal summer and then Australian shrublands in boreal autumn-winter. This new analysis of dust emissions, from global sources of varying geochemical properties, have far-reaching implications for current and future dust-climate effects. For more reliable coupled representation of dust-climate projections, our findings suggest the need to re-evaluate dust cycle modelling and benefit from the albedo-based parameterisation

Use of combinations of antipsychotics: McLean Hospital inpatients, 2002

Background The empirical use of combinations of antipsychotic agents appears to be increasing with little research support for the relative efficacy, safety or cost-effectiveness of this practice. Such treatment was evaluated in hospitalized psychiatric patients. Methods Samples of consecutive inpatients treated with > 2 ('polytherapy') vs 1 antipsychotic ('monotherapy') were matched on age, sex, diagnosis and admission clinical ratings, and these groups were compared on total daily chlorpromazine-equivalent doses, days in hospital, and changes in clinical ratings between admission and discharge. Results The study sample included 69 polytherapy and 115 well-matched monotherapy subjects. Despite matching for initial CGI and GAF ratings, polytherapy was associated with high PANSS subscale scores of positive symptoms among affective psychosis, and relatively greater PANSS subscale ratings of excitement-agitation among patients diagnosed with schizophrenia. Estimated clinical improvement during hospitalization was similar among poly- and monotherapy patients, but total daily CPZ-eq doses at discharge averaged twice-greater with polytherapy, and hospitalization lasted 1.5 times longer. Conclusions Antipsychotic polytherapy as well as the types of agents combined may reflect clinician responses to particular symptom patterns. The value of specific combinations of antipsychotic agents and their comparison with monotherapies requires specific, prospective, randomized and well-controlled trials that consider matching on clinical characteristics and truly comparable doses across regimens. Copyright (c) 2005 John Wiley & Sons, Ltd

The Evolution and Future of Targeted Cancer Therapy: From Nanoparticles, Oncolytic Viruses, and Oncolytic Bacteria to the Treatment of Solid Tumors

While many classes of chemotherapeutic agents exist to treat solid tumors, few can generate a lasting response without substantial off-target toxicity despite significant scientific advancements and investments. In this review, the paths of development for nanoparticles, oncolytic viruses, and oncolytic bacteria over the last 20 years of research towards clinical translation and acceptance as novel cancer therapeutics are compared. Novel nanoparticle, oncolytic virus, and oncolytic bacteria therapies all start with a common goal of accomplishing therapeutic drug activity or delivery to a specific site while avoiding off-target effects, with overlapping methodology between all three modalities. Indeed, the degree of overlap is substantial enough that breakthroughs in one therapeutic could have considerable implications on the progression of the other two. Each oncotherapeutic modality has accomplished clinical translation, successfully overcoming the potential pitfalls promising therapeutics face. However, once studies enter clinical trials, the data all but disappears, leaving pre-clinical researchers largely in the dark. Overall, the creativity, flexibility, and innovation of these modalities for solid tumor treatments are greatly encouraging, and usher in a new age of pharmaceutical development